Retention of HIV Positive Persons in Antiretroviral Therapy Programs in Post-Conflict Northern Uganda-Baseline Survey

of 17 Health Units

Principal Investigators:

Kenneth Mugisha, MD Andrew Ocero, MD

Edward Semafumu, MD Luigi Ciccio, MD

Roland F. Muwanika James Otim,

Med Makumbi

May, 2009.

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Executive Summary Introduction & Background The advent of antiretroviral therapy has changed the course of the AIDS epidemic and made HIV a chronic illness rather than a death sentence. However, if the therapy is to work well and minimize the possibilities of drug resistance developing, it requires that long-term retention is sustained. Long-term retention of patients in Africa's rapidly expanding antiretroviral therapy (ART) programs for HIV/AIDS is essential for these programs' success but has received relatively little attention. The aim of this study was therefore to assess the current status of retention of patients started on antiretroviral therapy at 17 sites in post-conflict northern Uganda in order to document the magnitude of the problem and help policy makers and program managers address the challenge of patient retention through generation of practical interventions for ensuring high levels of retention in NUMAT-supported ART programs. Problem Statement and Justification for the Study Northern Uganda has suffered the brunt of a cruel 20-year civil war, which has left thousands dead, millions displaced and many maimed. This region has an HIV prevalence of 10.9 %, far above the national average of 6.4 % (MOH, 2005). With the lull in war, many stakeholders in HIV/AIDS care provision have swung into action to provide services against a background of shattered physical and health infrastructure, lack of health workers; irregular supply of drugs and other medical logistics; a population in transit; fears of re-emergence of war and conflict; cultural and religious beliefs and attitudes about faith healing, psycho-social trauma; existing stigma; non-disclosure of HIV status; and biting poverty among other factors that could affect retention. The impact of these factors was not yet well elucidated. No one knew for how long patients on ART in post-conflict Northern Uganda are retained in ART programs. And if they were lost- to- follow up, no one knew the reasons why. Also needed was a better understanding of how various factors at play influenced retention of patients in ART programs in a post-conflict setting. There was inadequate baseline information on the current levels of patient retention and attrition in post-conflict Northern Uganda. As part of the strategy to further strengthen ART programs at the NUMAT-supported sites in northern Uganda, NUMAT needed to undertake this survey to assess the current levels of retention. Methods and Materials Both qualitative and quantitative data collection methods were used to generate the relevant information over a period of 10 weeks at 17 NUMAT-supported ART sites in post conflict northern Uganda. This study was conducted between January and March 2009. A total of 1032 ART Clinic Chart registers and Pharmacy Logbooks were reviewed; 17 key informant interviews conducted; and 22 Focus Group discussions held with people living with HIV/AIDS accessing ART at 17 sites across northern Uganda. Defaulter tracing was done on 35 patients who had been identified as lost to follow-up.

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Findings from the study The overall retention rate at the ART sites was found to be 51.1%. Loss-to-follow-up was found to be highest during the first 6 months of ART initiation (52.9%). At 12 months on ART, the attrition rate was 22.2%; but rose slightly to 24.8% over a 24 month period. Patients who were married had a 1.32 – fold increased hazard of getting lost- to- follow-up as compared to the single or the never married (p-value = 0.042). Patients whose ART combination was changed had a 1.6 fold increased hazard of loss-to-follow-up as compared to those who had not changed ART combination (p-value < 0.001). Patients who were residing at distances of 11 – 15 km away from the clinic had a 1.6- fold increased hazard of being lost-to-follow-up as compared to those who were residing less than 5 km away (p-value = 0.023). Patients who initiated ART at body weight of 45 kg or more had a 1.28- fold increased risk of being lost-to-follow-up (p-value = 0.024). The commonest reasons given for loss-to-follow-up were: relocation ( 16 out of 17 respondents); death ( 15 out of 17 respondents); lack of finances to meet transport costs ( 10 out of 17); and long distances from the health facility (7 out of 17 respondents). Other reasons given for attrition included: stigma at the individual, household and community levels; drug stock-outs; food shortage; ARV-related side effects; self-transfer by patients to other providers who offered other incentives; non-disclosure; alcoholism; incarceration; faith-healing beliefs, myths and misconceptions. According to the responses gathered during the focus group discussions and in-depth interviews, the following were the key factors affecting retention of HIV-positive persons in ART programs in post-conflict northern Uganda: Health systems factors Drug stock outs at the health units ; high patient loads at the health facilities have caused long waiting times. In addition, it was found that there were a significant number of patients who got lost to follow up before initiating ART because of the long process of ART initiation, coupled with the distance to the health units. It was also found that the linkage between the Antenatal clinics/ Maternity for PMTCT, and the ART Clinics was still very weak. This makes it difficult to identify which mothers would require Comprehensive HIV/AIDS Care, leading to delays in ART initiation. Community-related factors Stigma is still a very serious impediment to long term retention; particularly among school teachers, and the middle-income earners (civil servants and businessmen). Mass- Media Influence: Incidences of radio stations advertising herbalists and traditional healers who have a cure for HIV/AIDS were reported during the FGD sessions. Parents and families have not been supported to disclose to HIV infected children about their serostatus. Geographical Factors

Distance from the health facilities and lack of finances to meet transport costs is a significant barrier to retention in ART programs.

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Human Resources Factors

There is still a very acute shortage of trained health workers in this area, to offer treatment ,care and support to PLHIV. The patient provider ratio is still unacceptably high. A number of defaulters who were traced in their communities said they were not aware that ART was life-long treatment indicating that the counseling at ART initiation was inadequate. Health workers reported experiencing challenges with discordant couple. Many health workers were also reported to manifest negative attitudes towards people living with HIV/AIDS, particularly those who do not work in the HIV Clinics. Their worker motivation and remuneration was reported to be a big challenge. They were said to be too few, and are transferred frequently. The Network Support Agents (NSA) that were trained are too few (2 per Sub County); and they need to be well motivated. Socio-economic Factors

Food shortage and food insecurity at household level was reported to impact greatly on the adherence and long term retention of PLHIV in ART programs and some PLHIV tend to transfer out to other service providers on self-referral basis in order to benefit from other incentives such as food support; school fees or mosquito nets among others. Drug-related Factors Patients who get severe side effects discourage the rest of the community and they drop out of the ART program. There are also incidences of frequent ARVs and essential drugs stock outs from MOH at various units. Patient-related Factors Non-disclosure and lack of home-based support, continues to be a critical barrier to retention and adherence in ART programs. Others were found to have defaulted on treatment after registering great improvement in their health. Many patients were reported to have resorted to heavy alcohol consumption and this alcoholism is impacting greatly on their adherence. Prisoners have been found to be so prone to loss-to-follow up, especially the defilement cases. These cases are common in this region because some parents use it as an opportunity to generate income. Soldiers and police officers were also found to easily get lost to follow-up because of frequent transfers. There is poor health-seeking behavior among men living with HIV/AIDS in northern Uganda. The pregnancy rates among women who have improved on ART were reported to be ‘very high’. These women were said to be defaulting because they fear to go to the health units and face harassment by health workers. To make matters worse, most HIV positive mothers in this setting were said to have no infant feeding options apart from breastfeeding; and they end up infecting their children due to continued breastfeeding. Cultural and Religious Factors Myths and misconceptions about antiretroviral therapy still abound in this setting, particularly in regard to side effects. There are also strong beliefs about traditional healers as having a cure for HIV/AIDS. Religious leaders who preach about faith-healing also still abound.

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Conclusions Persons living with HIV infection are socially vulnerable and experience stigma and discrimination at all levels, and this poses challenges in accessing as well as remaining in care. ARV drug stock-outs are a great impediment to retention in ART programs in Northern Uganda. The retention in ART programs in Northern Uganda is poor . In order to improve the retention rates, the key priority areas for action by NUMAT include:

Strengthening the ARV drug stocks and logistics supply chain management in order to off-set shortages and stock outs caused by the inefficiencies of the National Medical stores.

The development of human resource capacity for health in their catchment areas Increased community engagement and expansion of training and deployment and

motivation of community health workers. Intensifying strategies to fight stigma and discrimination at all levels Improvement of health care infrastructure & equipment; and Provision of electronic systems for data management at health unit level.

It would be better to have more peripheral health units accredited to provide ART so as to reduce on the workload at the existing ART sites. Expand to Health Center III and II’s provided they are equipped with e.g. a clinical officer. It would also be useful to introduce outreach services, home based care by trained health workers and community drug distribution points for ARV refills delivery to reduce on the distances that clients have to travel to the health units.

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Acknowledgements The Principal Investigators for this study on the retention of HIV positive persons in ART programs in post-conflict Northern Uganda wish to acknowledge the invaluable assistance of many individuals, government institutions and the Northern Uganda Malaria AIDS Tuberculosis Program (NUMAT) in particular, for the moral, technical, financial and other forms of support provided to them during the design, development as well as the execution of this important study. In particular, the investigators do gratefully acknowledge the employees of NUMAT- Gulu Head Office, for the massive family spirit showed them throughout the execution of this study. Their commitment and dedication to facilitating various aspects of this activity is actually second to none. We would also like to thank all the respondents who took part in this study, right from the piloting of the data collection tools to the actual implementation of the study. Their will to voluntarily participate in this survey has given birth to a wealth of knowledge that could inform HIV/AIDS programming for posterity. During the design, development, and execution of this survey, we received both financial support and technical assistance from the United States Agency for International Development (USAID), through NUMAT; for which we are eternally grateful. Special thanks go to Dr. Ocero Andrew, Dr. Edward Semafumu, Mr. Alfred and Mr. James Otim, together with Mr. Med Makumbi (Chief of Party)NUMAT for ensuring that this survey was smoothly implemented. A lot of effort was put in by the Research Assistants: Odongo Emilio; Ogik Moses, Ngecha Esau, Otto Tommy; Odongo Alfred Abel; Auma Sandra; Aryemo Beatrice; Akello Judith Miriam,Amolo Jane; Mungo Abiasari; Ssenyimba Conrad; and Nampera Viola; to ensure that quality data was collected. The data entry clerks are specially appreciated for their dedication and accuracy. Our heartfelt gratitude also goes to Connie Atim (Administrative Assistant); and Miriam, the NUMAT specialist for the tremendous support and high level of cooperation and team work they exhibited. We cannot forget to thank our Statistician, Fred Roland Muwanika. He has worked tirelessly and closely with us to complete the statistical analysis. Last but not the least, all the drivers of NUMAT, who transported us safely throughout the Northern region during the period of data collection are also greatly appreciated.

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Table of contents   Executive Summary ............................................................................................................................2 Acknowledgements .............................................................................................................................6 Table of contents .................................................................................................................................7 List of abbreviations and acronyms ..................................................................................................10 Operational Definitions .....................................................................................................................11 Chapter One : ....................................................................................................................................13 Introduction and Background ...........................................................................................................13 

1.0 Introduction .............................................................................................................................13 1.1 Background: ............................................................................................................................14 

1.1.2 Children & Education ......................................................................................................15 1.1.3 Poverty & Displacement ..................................................................................................16 1.1.4. Economic Costs ..............................................................................................................16 

Chapter Two..................................................................................................................................18 Literature Review..........................................................................................................................18 2.0. Literature Review ...................................................................................................................18 2.1 Overview .................................................................................................................................18 2.2 Reasons for defaulting ............................................................................................................20 

2.2.1 Stigma and Discrimination at Individual, Household and Community Levels ...............21 2.2.2 Less loss to follow-up at primary health care sites ..........................................................22 2.2.3 Making better use of smaller primary care clinics, general practitioners and nurses ......22 2.2.4 Systems for defaulter tracing ...........................................................................................22 2.7.0 Conducting Retrospective Chart Reviews .......................................................................23 

Chapter Three....................................................................................................................................25 Statement of the Problem ..................................................................................................................25 

3.0 Statement of the Problem ........................................................................................................25 3.1 Justification for the Study .......................................................................................................25 3.2 Conceptual Framework ...........................................................................................................26 3.3. Research Questions ................................................................................................................27 

Chapter Four .....................................................................................................................................28 Study Objectives ...............................................................................................................................28 

4.0 Overall Objective ....................................................................................................................28 4.1 Specific Objectives .................................................................................................................28 

Chapter Five ......................................................................................................................................29 5. 0 Methods and Materials ...............................................................................................................29 

5.1 Study Site: ...............................................................................................................................29 5.2 Study Population .....................................................................................................................29 5.3 Study design and sampling procedures ...................................................................................29 5.4 Inclusion Criteria ....................................................................................................................30 5.5 Exclusion Criteria ...................................................................................................................31 5.6 Sample Size Determination .....................................................................................................31 5.7 Sampling frame .......................................................................................................................31 5.8 Sampling .................................................................................................................................31 5.9. Data Collection Techniques ...................................................................................................33 5.10 Data Collection Procedure ....................................................................................................33 5.11 Qualitative methods ..............................................................................................................33 5.12 Quantitative methods ............................................................................................................33 

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5.13 Measurements and Study Variables ......................................................................................34 5.14 Execution of the study in the Field .......................................................................................34 5.15 Instrument Pre-testing ...........................................................................................................35 5.16 Data Management .................................................................................................................35 5.17 Quantitative Data Analysis ...................................................................................................35 5.18 Qualitative Data Analysis .....................................................................................................37 5.19 Data Quality Control .............................................................................................................38 5.20 Study Limitations and Possible Remedial actions ................................................................38 5.21 Ethical Considerations ..........................................................................................................39 

Chapter Six........................................................................................................................................40 6.0 Results from the Study ................................................................................................................40 

6.1 Introduction: ............................................................................................................................40 6.1.1 Health Facility Distribution by level of service delivery .................................................41 6.1.2 Socio-demographic characteristics of the HIV/ART patients at the 17 health units .......41 

6.2 ART Drug Combinations in Use at the 17-Health Units: .......................................................45 6.3 Clinical factors ........................................................................................................................48 6.4 Frequency of refills for ARV drugs ........................................................................................52 6.5 Retention Levels in ART Programs At NUMAT-Supported ART Sites ................................54 6.6 Predictors of Retention in ART Programs-Bi-variate analysis ...............................................57 

6.6.1 Sex and loss to follow up .................................................................................................57 6.6.2 Age of the patient .............................................................................................................57 6.6.3 Marital status ....................................................................................................................57 6.6.4 Change of ART ................................................................................................................58 6.6.5 Body Weight of the patient at ART initiation ..................................................................58 

6.7 Kaplan-Meier Survival curves at different time intervals .......................................................59 6.7 Survival analysis for predictors of overall retention ...............................................................60 

6.7.1 Interpretation of the proportional hazards model .............................................................60 6.8 Health Systems at 17-NUMAT supported ART Sites in Northern Uganda ...........................63 

A Clinical Officer (seated) prescribing ART at Amolatar Health Center IV. ...........................64 6.8.1 Human Resources for HIV/AIDS Care Provision ...........................................................64 6.8.2 Supervision of health workers: ........................................................................................66 6.8.3 Availability of HIV care and Prevention services ...........................................................66 6.8.4 Provision of adherence-related services ...........................................................................66 6.8.5 Frequency of visits, appointments and patient loads .......................................................68 6.8.6 Proportion of visits scheduled by appointment ................................................................69 

6.9 Tracking Systems and Losses to follow-up ............................................................................69 6.9.1 Tracking of ART eligible patients not yet started on treatment .......................................70 6.9.2 Waiting Time for ART eligibility assessment .................................................................70 6.9.3 Priority reasons for waiting for eligibility assessment .....................................................71 6.9.4 Waiting time for starting ARV drugs ...............................................................................71 6.9.5 Patients waiting to start ART at time of the survey .........................................................71 

6.10 ARV treatment tools used at clinics ......................................................................................72 6.11 ART Combination Regimens ................................................................................................72 6.12 Laboratory Services Capacity: ..............................................................................................72 6.13 Current sources of support at the 17 health facilities ............................................................74 

6.13.1 Sources of support ever received ...................................................................................74 6.14 Factors affecting Retention in ART Programs in post-conflict Northern Uganda ...............75 

6.14.1 Health systems factors ...................................................................................................75 6.14.2 Community-related factors ............................................................................................78 ...................................................................................................................................................79 

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6.14.3 Geographical Factors .....................................................................................................80 6.14.4 Human Resources Factors..............................................................................................81 6.14.5 Socio-economic Factors .................................................................................................81 6.14.6 Drug-related Factors ......................................................................................................82 6.14.7 Patient-related Factors ...................................................................................................82 6.14.8 Cultural and Religious Factors .......................................................................................85 

6.15.0 Defaulter Tracing ...............................................................................................................86 6.16.0 Data Management Practices at 17-NUMAT supported sites .............................................89 6.18.0 Existing strategies for retention and adherence to antiretroviral therapy in Northern Uganda. .........................................................................................................................................92 6.19.0 Current mechanisms for monitoring retention in antiretroviral therapy programs in Northern Uganda. ..........................................................................................................................93 

Chapter Seven .................................................................................................................................106 7.0 Discussion .................................................................................................................................106 

7.1 Introduction: ..........................................................................................................................106 7.2 Data Collection and significant Findings ..............................................................................106 7.3 Strategic and Programmatically relevant findings: ...............................................................107 

7.3.1 Drug Stock-outs: ............................................................................................................109 7.3.2 CD4 Count rise and Body weight gain ..........................................................................109 7.3.3. Pregnancy and PMTCT access .....................................................................................109 7.3.4 Retention rates in the NUMAT-supported ART programs: ..........................................110 7.3.5 Demographic characteristics and loss-to-follow-up ......................................................110 7.3.6 Health System Factors in ART programs .....................................................................111 7.3.7. Reasons for loss-to-follow –up .....................................................................................111 7.3.8 Stigma and discrimination against people living with HIV/AIDS ................................111 

7. 4 Conclusions ..........................................................................................................................112 Chapter Eight ..................................................................................................................................113 

Recommendations .......................................................................................................................113 REFERENCES ...............................................................................................................................117 APPENDICES ................................................................................................................................121 

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List of abbreviations and acronyms AIDS- Acquired Immunodeficiency Syndrome ART – Antiretroviral therapy CD 4- Cluster of Differentiation FBO – Faith Based Organization FDC – Fixed Drug Combination FGD- Focus Group Discussion HIV- Human Immunodeficiency Virus HMIS – Health Management Information System ICAP – International Center for AIDS Care and Treatment IDP – Internally Displaced People’s camp IRIS – Immune Reconstitution Inflammatory Syndrome L/ C – Lead Consultant LRA – Lord’s Resistance Army MOH – Ministry of Health NGO- Non-Governmental Organization NUMAT- Northern Uganda Malaria, AIDS & Tuberculosis program PPS – Probability Proportionate to Size PEPFAR – Presidential Emergency Plan for AIDS Relief R/ A – Research Assistant RHRU – Reproductive Health Research Unit UDHS – Uganda Demographic Health Survey UNAIDS – United Nations Joint Program on HIV/AIDS USAID – United States Agency for International Development WHO- World Health Organization

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List of Tables and Charts Table 1: Number of adult HIV positive patients ever registered at the ART sites Table 2: Adult HIV positive patients currently registered at the ART sites Table 3: Number of HIV positive children ever registered by gender Table 4: Number of HIV positive children currently registered by gender Table 5: Patients on ART by gender as at 31st December 2008 at 17 ART sites Table 6: Demographic characteristics of patients on ART Table 7: Socio-demographic characteristics of patients on ART Table 8: ART Drug combinations Table 9: Reasons for change of ARV combination Table 10: Comparison of Body weight and CD4 cell counts Table 11: Body weight and CD4 count averages Table 12: Functional status and Prophylaxis state of patients on ART Table 13: HIV/AIDS and Pregnancy Table 14: Disease conditions diagnosed among patients on ART Table 15: ARVs and Co-trimoxazole drug stock-outs Table 16: Frequency of drug stock-outs in the last 6months Table 17: Overall retention rates in the ART programs Table 18: Retention rates based on Pharmacy records alone Table 19: Number of patients lost-to-follow-up at given time intervals Table 20: Predictors of overall retention (Bi-variate analysis) Table 21: Number of patients lost-to-follow-up at given time intervals(Pharmacy records) Table 22: Proportional hazards modeling Table 23: Odds ratios for predictors of overall retention Table 24: ART Clinic Managers by cadre Table 25: Cadre of staff providing HIV care Table 26: Staff availability for provision of HIV care Table 27: Availability of HIV care and prevention services Table 28: Availability of adherence related services Table 29: Proportion of visits scheduled by appointment Table 30: Tracking systems for patients on ART Table 31: Types of ART regimens available at the ART sites Table 32: Laboratory services capacity Table 33: Tests done to assess clinical progress on ART Table 34: Current sources of support for the ART programs Table 35: Defaulter tracing outcomes Table 36: Demographic characteristics of patients on ART (Complete charts only) Table 37: Socio-demographic characteristics (Complete charts only) Table 38: Retention rates (Complete charts only) Bar Chart 1: Percentage distribution of reviewed medical charts by district Bar Chart 2: Percentage of patients on ART by age group Bar Chart 3: Change of ART combination Bar Chart 4: Overall retention rates in the ART programs Bar Chart 5: Overall retention rates as per pharmacy records Bar Chart 6: Loss to follow up at given time intervals Bar Chart 7: Charts with missing and / complete data Bar Chart 8: Distribution of complete charts by district Bar Chart 9: Distribution of patients by age group Bar Chart 10: Retention Rates for complete charts only

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Operational Definitions Retention: Refers to patients known to be alive and receiving HIV/AIDS care including ART at the end of a follow-up period, in this case in quarterly periods of 3 months. Attrition: This is the discontinuation of ART including death, loss to follow-up, and stopping ARV medications while remaining in care. Loss-to-follow-up: The phrase lost-to-follow-up is frequently used in medicine to describe patients who you can no longer locate despite your best efforts. This implies that it is either the patient’s fault, or due to circumstances beyond one’s control. In this case, it refers to patients receiving ART who were more than 3 months late for a scheduled clinic or pharmacy visit and who were neither transfers-out nor relocations. Transfers-out: Patients whose care and ART treatment was transferred to another ART program, other than the NUMAT-supported ART sites. Relocations: Patients who moved to another location but who were not referred to an ART service in the new area. Non-death Losses: The sum total of transfers-out, relocations and losses-to-follow up. Antiretroviral therapy use: Is defined as the use of a triple therapy combination of antiretroviral drugs from the classes of protease inhibitors, non-nucleoside reverse- transcriptase inhibitors and /or, nucleoside reverse transcriptase inhibitors, as per the national ART treatment guidelines within 30 days of the first antiretroviral prescription.

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Chapter One

Introduction and Background 1.0 Introduction The AIDS pandemic is currently the world’s most deadly war that has killed 25 million people since it was first recognized in 1981, making it one of the most destructive epidemics in recorded history. Despite recent, improved access to antiretroviral therapy and care programs in many parts of the world, the AIDS epidemic claimed 3.1 million lives in 2005; more than half a million (570,000) were children(WHO/UNAIDS,2007). Today, over 33.2 million people are living with HIV/AIDS worldwide. Of these, over 30.8 million are adults, 15.8 million are women and 2.5 million are children under 15 years. People who were newly infected with HIV in 2007 alone are 2.5 million. A total of 2.1 million deaths due to AIDS were recorded in 2007; of which 1.7 million were adults, and 330,000 were children below 15 years (WHO/UNAIDS, 2007). A little more than one-tenth of the world’s population lives in sub-Saharan Africa, which remains hardest hit and is home to 25.8 million people living with HIV, almost one million more than in 2003. Seventy percent of people infected with HIV live in sub-Saharan Africa. In 2005 alone, there were 4.9 million new infections, of who 700,000 were children (WHO/UNAIDS, 2007) .The adult prevalence of HIV in sub-Saharan Africa is 7.2 % compared with the next highest region – the Caribbean at 1.6%. Uganda is one of the sub-Saharan African countries worst hit by the HIV/AIDS epidemic, with over 1.2 million people infected and an HIV prevalence rate of about 6.4 %. The burden of disease experienced by Ugandans has long been described by authorities as a national health concern. The post-conflict region of Northern Uganda remains hardest hit by the HIV/AIDS epidemic: HIV prevalence in North Central region (Gulu, Lira, Kitgum, Apac, Pader) is 10.9 % compared to 4.3% for North Eastern (Kaberamaido, Katakwi, Kotido, Kumi, Moroto, Nakapiripirit, Soroti) and 2.5% for North west (Moyo, Arua, Adjumani, Nebbi, Yumbe).The closest HIV prevalence to North Central’s record is found in metropolitan Kampala, at 9.1%(MOH, 2005). As the number of people living with HIV/AIDS increases, so does the need for quality clinical HIV/ AIDS care, treatment and support services, particularly in resource-limited settings. The advent of antiretroviral therapy has changed the course of the epidemic and made HIV a chronic illness rather than a death sentence. However, with Antiretroviral therapy comes a lot of responsibilities for the patient, care provider and the community as a whole: particularly, long-term adherence to treatment if the therapy is to work well and minimize the possibilities of drug resistance developing (Ammassari A. et al (2002); Nieuwkerk .P., et al (2001).This demands that when patients join antiretroviral therapy programs, long-term retention is sustained. For ART to work, HIV infected individuals whose immune systems have been damaged need to take the medications regularly as life-long treatment. If people taking ARVs stop taking their medications, they may get sicker or die, or the virus that they carry may become resistant to the antiretroviral drugs. Yet the second- line regimens are expensive and carry potential for more adverse drug reactions.

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Several studies have looked at adherence to prescribed regimens, but few have studied the long-term retention of patients in ART programs (Blower, S. et al, 2005). No one clearly knew how long patients stayed in treatment in ART programs in post-conflict northern Uganda. Neither did we know why they could drop out in such a setting. Retention rates in the Ugandan ART programs have ranged from 39.2% to 81.0%, according to recent studies (Mallory. O. J. et al, 2008). In a post-conflict setting like Northern Uganda, there are a number of factors that could affect retention of patients in ART programs. These include stigma and discrimination at individual, household, or community levels; distance from the health unit; lack of money to meet transport costs; food insecurity; poor roads and infrastructure; myths and misconceptions; cultural beliefs and attitudes about faith-healing; patient-provider relationships, quality of care provided at the health facilities, availability of drug refills; the cost of drugs, ARV drug-related side effects, non-disclosure, depression, alcoholism, the movement of people back to their homes and to transit camps following the lull in war. In addition, there is now better care and support that is as yet unequally distributed; hence some patients may prefer to seek services at particular facilities. 1.1 Background: Northern Uganda has been the center of a 20- year old civil war, which has led to deaths, displacement of thousands of people into camps and disruption of the life style traditionally known in the Acholi and Lango sub-regions. Cases of rape, violence against women and children, maiming of body parts and increasing poverty have characterized the untold suffering of the people and distorted their way of life (Ward, K., 2001). According to the Uganda National Sero-prevalence and behavioral survey of 2005, Northern Uganda remains the highest hit by the HIV epidemic, with prevalence of 10.9 % compared to the national average of 6.4%. HIV/AIDS flourishes in conflict situations. The chaotic and brutal circumstances of war aggravate all the factors that fuel the HIV/AIDS crisis. War breaks up families and communities, creating millions of refugees and placing women and children in great peril of sexual attack or systematic rape used to terrorize opposing forces. It destroys the health services that might have been able to identify the diseases associated with HIV/AIDS or screen the blood transfusions that might transmit it. Over 90 percent of all HIV- infected children under the age of 15 years started life as babies born to HIV-positive mothers. Though studies have shown that antiretroviral drugs can reduce HIV transmission at birth, without access to these drugs or other interventions around one in three HIV-positive pregnant women will pass the infection on to their babies. In conflict situations women have no choice but to breastfeed. (Graca Machel, 1998.Unpublished). And war destroys the education systems that might have been able to teach prevention and slow the spread of the disease. AIDS contributes to political instability by leaving millions of children orphaned and by killing teachers, health workers, and other public servants. Nationally, there are over 350,000 people who are in urgent need of antiretroviral therapy; but of these an estimated 150,000 people were accessing ART by October 2008(MOH, Uganda).Though statistics are not readily available, anecdotal reports indicate a disproportionate gap in ART access for northern Uganda, an area with the highest prevalence in Uganda. This has been attributed to the insecurity and its effects on health care delivery.

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The challenge of antiretroviral therapy provision is that it is a complex and highly specialized field of HIV medicine, which requires highly trained and well motivated staff, a good supply chain for drugs, and good nutrition for the population on ART. In the case of northern Uganda, availability of health services has been hampered by the instability. Because of the war situation, there has been difficulty providing medicines and supplies, as well as lack of health workers to man the health units. According to Gulu district statistics, there were over 70% vacant positions in the health units by 2006(HMIS). Furthermore, what made this study relevant are the new challenges because of a population in transition. The returnees are going back to areas with no infrastructure such as accommodation for health workers, health unit structures; poor road networks hence the difficulty to move, and lack of access to safe water among other challenges. Whereas the retention levels in ART programs in Uganda are not yet fully established, studies in resource limited settings have shown rates as low as 60% over a two-year period in many programs(Sydney,R.,et al 2007). 1.1.1 Mortality In terms of mortality, there were excess death rates in northern Uganda at the height of the insurgency; three times higher than those recorded in Darfur in October 2005.There were 918 excess deaths each week. This meant that 131 people died each day in northern Uganda as a result of violence and conditions in the camps. Mortality as a result of HIV/AIDS in northern Uganda is indeed reported to be much higher than the national average (UAC, 2006). Each month almost 25,000 people in Uganda die from easily preventable diseases. The murder rate for Northern Uganda is currently at 146 murders per week, (0.17 murders per 10,000 people per day). This is three times higher than in Iraq, where the incidence of violent death in the period following the allied invasion was estimated to be 0.052 per 10,000 people per day (Behrend, H. & Currey, J., 2000).

1.1.2 Children & Education

Each day during the insurgency, 58 children under the age of five died as a result of violence and preventable diseases. An estimated sixty six thousand children were abducted during the course of the war in Northern Uganda.

One quarter of children in northern Uganda over ten years old have lost one or both parents. Two hundred and fifty thousand children in northern Uganda receive no education at all. Fifty percent of internally displaced people in northern Uganda are children under 15 years old (Ward, K., 2001; & Sydney, R., et al, 2007). There are classrooms with 300 students for every one teacher. Nearly half (48% percent) of all children in Kitgum, northern Uganda are stunted from chronic malnutrition. Three times more children under 5 years die in northern Uganda than in the rest of the country. (The crude mortality rate for children under 5 years old in northern Uganda is 3.18 per 10,000 children per day, which is more than three times the national average of 0.98 per 10,000). About seven hundred thirty seven schools in northern Uganda (60 percent of the total) were non-functioning because of the war (De Temmerman, E., 2001; & Jackson, P., 2002).

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1.1.3 Poverty & Displacement

Between 1.8 and 2 million people were internally displaced during this civil war. This is 8 percent of the Ugandan total population and 90% of the population of northern Uganda (Currey.J, 1998; & Ginyera-Pincywa,A.G ,1989). There were over 200 camps housing displaced people across the northern Uganda region, some holding more than 60,000 people. Population densities in some camps exceeded 1,700 people per hectare, densities higher even than those in Africa's most notorious urban slums. In the districts of Amuru, Gulu, Kitgum and Pader in northern Uganda, an area nearly the size of Rwanda was depopulated. At the height of the war, 80 percent of the camps in Gulu, Kitgum and Pader could not be accessed without military escorts. By the end of 2007, over three quarters (78%) of displaced families had no access to land to farm.

1.1.4. Economic Costs

Nearly 70 percent of displaced people have no monetary income. About 95 percent of displaced people in northern Ugandan districts live in absolute poverty. The annual cost of the war to Uganda was estimated at $85 million by experts.

As a result of the need to mitigate the impacts of the HIV/AIDS epidemic in northern Uganda, a number of non-governmental agencies have made concerted efforts to provide HIV prevention, care, and treatment and support services in this region, particularly in the internally displaced people’s camps. Such agencies include Faith based Organizations, World Vision, The AIDS Support Organization (TASO) and, AIDS Information Center (AIC), among others. And because of this flurry of activities by various players, it was important to know the issues that can inform programming, linkages and coordination for various programs. The Northern Uganda Malaria AIDS and Tuberculosis Program (NUMAT) is a five-year USAID-funded program based in Gulu that is collaborating with the Ministry of Health (MOH) to improve access to ART at 23 existing MOH sites. Long-term retention of patients receiving treatment at these sites has been a key concern and is essential for the ART program success. Since the inception of large- scale ART access early in this decade, ART programs in Sub-Saharan Africa have retained about 60% of their patients at the end of the second year ((Sydney,R.,et al 2007). However, in Northern Uganda where there has been civil strife, massive displacement of populations and a breakdown in social services, retention levels in existing ART sites have been found to be even much lower. Loss to follow-up at the ART providing sites as a result of distance from the health facility; high travel costs and the long time spent traveling on rough roads to the ART sites; death, stigma and discrimination; incarceration; transit populations; travel and relocation; myths about ART; lack of disclosure and home-based support; food shortage ; staff shortages; high patient loads; poor counseling received before ART initiation; frequent drug stock-outs; alcoholism; patient’s decision; lack of patient tracing procedures and poor community support have been identified to be a major cause of patient attrition from ART programs in post-conflict northern Uganda; among other reasons. Indeed, many patients were found to have gotten lost-to- follow-up before ART initiation; probably due to the tedious process of ART preparation. The exact reasons are now clearly elucidated.

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There was inadequate baseline information on current levels of patient retention and attrition. Before this study, no one knew clearly the reasons why patients dropped out of ART programs in post-conflict Northern Uganda. As part of the process of strengthening the ART programs at the NUMAT-supported sites this survey had to be undertaken to assess the current levels of retention and find out the reasons why. Based on the available evidence, NUMAT can now take purposive action intended to ensure the highest levels of retention on treatment by co-opting both community and institutional solutions to the challenge of retention in ART programs.

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Chapter Two Literature Review

2.0. Literature Review 2.1 Overview The advent of antiretroviral therapy (ART) has transformed HIV/AIDS into a chronic disease characterized by enhanced quality of life and increased life expectancy. In countries with limited resources, expanded availability of ART through funding from the President’s Emergency Plan for AIDS Relief (PEPFAR), the Global Fund and other initiatives is extending treatment benefits to citizens living with HIV in these settings. While access to treatment must be increased to achieve the Emergency Plan goal of providing ART to two million individuals in 15 focus countries by 2008, maintenance on prescribed therapy with an unprecedented high level of adherence for the lifespan of the individual is critical for optimal viral suppression and clinical outcomes. These outcomes are required to safeguard the treatment gains made possible by the Emergency Plan and other funding opportunities. Research from developed countries reveals that incomplete adherence and early treatment discontinuations are among the strongest predictors of virological failure, drug resistance and mortality among HIV+ individuals (; Paterson DL, et al. 2000; Bangsberg DR, et al. 2000; Bangsberg DR, et al., 2001; DeOlalla P, et al., 2002; Hogg RS, et al., 2002; ).Medication adherence focuses upon maintaining the therapeutic medication regimen and is described as taking the correct drug in the correct dose with the correct frequency at the correct time. To achieve undetectable levels of the virus in the blood and prevent the development of drug-resistant virus, patients are required to maintain consistently high levels of adherence (British HIV Association, 2005).

Achieving these levels of adherence presents significant challenges for both patients and health care providers. Once initiated, ART is a life-long treatment, consisting of multiple medications to be taken with varying dietary instructions. These medications have side effects, some of which may be temporary while others may be permanent or may require a change of medications. In addition to therapy-related factors, other variables can contribute to adherence (or non-adherence), including socio-demographic factors (e.g. gender-related roles and family and social support), psychological factors (e.g. depression), disease characteristics (e.g. duration of HIV infection and opportunistic infections), security situation, and patient/provider and health system-related elements. While the predictors and biologic consequences of adherence to ART are well documented in developed countries, information from resource-poor settings is limited. Retention is a critical determinant of adherence as patients must be actively attending and participating in an ART program in order to receive their medication and to have their HIV clinical indicators monitored. A prospective study conducted in South Africa provided some important findings regarding death and non-death losses among 927 patients attending an ART program. Overall, this study found that loss to follow-up and late mortality rates among ART patients (death after 4 months of ART treatment) were low, reflecting good retention in the program and good treatment response. This study, however, followed a cohort of patients in an ART program with community-based counselors who traced patients if they missed an appointment (Etienne M., et al., 2007).

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According to Dr. Gilles Van Cutsem of Medecins Sans Frontieres, ART-scale up must be accompanied by decentralization of treatment to the most peripheral level. Appropriate systems need to be created to accommodate the ever-increasing patient load. This includes capacitating all levels of healthcare workers to deliver and monitor ART and ensuring additional adherence support by non-medical staff (Schneider M.,et al., 2007).

Since early 2007, there have been growing concerns that although most people initiating antiretroviral therapy in resource limited settings are doing well on their first-line regimen, an unacceptably large and increasing proportion of patients are being lost to follow-up and care, even at model sites, as facilities reach the limits of the number of subjects they can easily manage (http:// www.aidsmap.com/cms 1191180.asp.).

There are lessons on retention that have been learnt from South Africa’s public health services sector. With the very rapid scale up of ART programmes underway, so many HIV-infected people to serve, and health systems already strained, facilities which were not designed to provide chronic care to so many and are only now beginning to learn how to reorient their activities to do so — may surpass their capacity to offer high quality individualized support, and that, as a result, some people are lost to follow-up (Magula, N., et al., 2007).

With the increasing number of clients, management of data and loss of patients to the system had become an area of concern for the clinics (Maponyane M., et al., 2007). However, at the HIV Implementer’s Meeting in Kigali, Rwanda in July, 2007, there were numerous examples of programmes improving patient retention by moving ART delivery and support closer to the patient. This was done either by decentralizing to the most peripheral levels of the formal health sector through greater reliance on nurses and community health care workers — especially people with HIV empowered to act as members of a clinical care team — or by partnering with non-governmental organizations (NGOs), faith-based organizations (FBOs) and community-based organizations (CBOs) already providing community- and home-based care.

Recent analysis of data from another enormous PEPFAR-supported Programme operating in eight countries provides clear evidence showing that programmes that support people on antiretroviral therapy (ART) in resource-limited settings with home visits or home-based care appear to have a significantly lower percentage of loss to follow-up than when ART and adherence support are primarily facility-based (Etienne M., et al., 2007).In other words, there is something to be gained by supporting people on ART as closely as possible to their homes.

This shows that programs that seek to improve access to health care by reducing socio-cultural and geographical barriers are an important area for further study (Lippincott Williams & Wilkins, 2003).

According to Amfar AIDS Research report of November, 2007, there are inadequate retention rates in Sub-Saharan Africa ART Programs. They found that only slightly more than 60 percent of patients enrolled in antiretroviral treatment (ART) programs in sub-Saharan Africa continued treatment two years after treatment initiation. In addition, findings indicated that 40 percent of patients who stopped ART died within two years.

The study, which collected data on 13 sub-Saharan African countries, provides insights into program initiation and retention rates. It also raises concerns regarding future policies, program implementation, and resource allocation for ART protocols in resource-poor settings.

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Of those who did not maintain their treatment regimens, more than half (56 percent) were lost to a lack of provider follow-up. The study found that death typically occurred among those patients who began ART at advanced stages of their infection. Stigma, discrimination, and poverty were reported as critical barriers to testing in many sub-Saharan African nations which place limitations on early detection and treatment.

Global HIV treatment and prevention funding agencies among private, governmental, and nongovernmental organizations have provided resources and research opportunities to mitigate the scourge of HIV/AIDS by supporting in-country programs. But the findings highlight a need for thorough evaluation of geographic obstacles to treatment access, as well as any barriers that may interrupt a steady supply of treatment commodities.

According to this study, the development of an effective tracking system to reduce the proportion of patients lost to a lack of follow-up is a critical requirement for ART programs. Furthermore, improvements in the development and integration of community-based approaches and national strategies for testing, treatment, and care need to be made to ensure increased patient retention rates and continued funding—of ART programs in sub-Saharan Africa.(Source: Amfar AIDS RESEARCH at http://www.amfar.org/hill/article.aspx?id=874. Accessed 17th April 2009).

2.2 Reasons for defaulting

According to Dr Ebrahim Variava, of Klerksdorp Tshepong Hospital Complex in South Africa, when they tried to find out the reasons for loss to follow up, as far as they could ascertain, what they found was that 42% had died. Early death on ART could be due to an opportunistic infection that occurs before ART has a chance to work or pre-existing life-threatening conditions, or due to an immune reconstitution inflammatory syndrome (IRIS) related condition, but given the retrospective nature of the data collection, it was difficult to be certain whether the patients were actually taking ART at the time of death. The remaining deaths occurred after the person had defaulted for some other or unknown reason.

Of note, about 31 patients who had achieved undetectable viral loads were subsequently lost to follow up. In the majority (57%) of the defaulters, the team couldn’t determine what the cause for loss to follow-up was. About a third couldn’t be traced. Dr Variava said that cell phone numbers in South Africa proved to be both a blessing and a curse because while they make things much simpler when they work, they are constantly changing, since Tshepong serves a mining community with an unusually mobile population.

But concrete reasons for dropping out were only identifiable in a minority. These included a lack of finances, which accounted for 5% of the defaulters, travel and relocation for 5%, “patient choice” in 4% and 7% for a variety of other excuses (Variava E., 2007).

Dr Scott Worley, of the International Centre for AIDS Care and Treatment (ICAP), who has been working on a system to deal proactively with high loss to follow-up rates at some sites within the East London Medical Complex in the Eastern Cape (some of the facilities have rates as low as zero but ranging up to 22%); noted that requiring the sickest people (those who are starting ART) to travel a longer way to get their antiretroviral drugs is a big part of the problem. But evidence from their site suggested other factors such as myths about ART, competition with traditional medicine, the lack of disclosure and home based support, fears of losing one’s social grant; and at the facility level: staff shortages, high patient loads and poor counseling received upfront. He also noted that these factors were also leading to loss to follow-up in a lot of patients before starting ART.

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He indeed stressed the urgent need for solutions to ease the process of ART initiation so that people are not lost in that process (Worley S.B., et al., 2007).

In the RHRU study where around 75% of patients at Tshepong Wellness, dropped out of the ART program, one physician thought that this was due to the strict loss to follow-up criteria and that many of these people might have later come in for care. However, another physician pondered whether it had something to do with the ART preparation, saying that it could be a manifestation of the condescending way we prepare patients for ART: we treat people as children. They must come for four or five visits before ARVs and by the time you start them on ARVs, they’re lost to follow up. (Maponyane M., et al, 2007).

Anecdotal findings in South Africa have also attributed high loss to follow-up to non-disclosure and alcohol consumption (Schneider M., et al., 2007). The importance of high travel costs and the long time spent travelling to get to the ART sites has also come to light as a factor affecting retention in ART programs. But as more peripheral ART sites are accredited, Schneider argues that people can be sent to sites that are more convenient to them.

2.2.1 Stigma and Discrimination at Individual, Household and Community Levels

HIV/AIDS related stigma is a real or perceived negative response to a person or persons by individuals, communities or society. It is characterized by rejection, denial, and discrediting, disregarding, underrating and social distance. It frequently leads to discrimination and violation of human rights (A.C.O.R.D., 2004).

According to Angela Hadjipateras (2004), responses and strategies for tracking stigma and discrimination must be built on communities’ own understanding of the HIV/AIDS problem and the solutions they propose.

Stigma constitutes one of the major barriers to accessing HIV/AIDS services and treatment. If universal access to treatment is to be achieved, effective strategies for addressing stigma and discrimination must be developed as a matter of great urgency. Stronger community involvement in the process of stigma analysis and development of responses is a must do.

A wide range of actors have come together to take up the challenge of confronting the HIV/AIDS crisis head-on. However, the biggest challenge that remains to be overcome is that of HIV/AIDS related-stigma and discrimination. Despite concerted efforts to demystify and enhance awareness and understanding, many people still associate HIV/AIDS with moral decadence and promiscuity, ultimately passing moral judgment on those infected.

As a result, PLHIV face resentment, isolation, ridicule, and are often denied access to their rights and basic services. Such attitudes and behavior do not only infringe on the rights of PLHIV to respect and dignity, they also act as a strong disincentive for them to make use of any existing services for fear of being ‘branded’.

According to Denis Nduhuura (2004) - HAJAP Program Manager-A.C.O.R.D., there is no longer any dispute over the fact that challenging stigma and discrimination constitutes a critical part of the equation in the fight against HIV/AIDS. This is even truer in the light of recent developments that have helped to reduce the price of drugs, thereby enhancing the potential for ARVs to be reached by some of the poorest and most needy people living in Sub-Saharan Africa. However, unless stigma and discrimination are challenged, they are unlikely to access these life prolonging drugs.

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“The level of stigma is so high in the country and this is negatively affecting the struggle to control the spread of the virus because people are fearing to disclose their status,” Noerine Kaleeba, founder of the National NGO, The AIDS Support Organization (www.tasouganda.org) said recently during a meeting for her organization in the northern Ugandan town of Gulu. (Reuters Alert Net at http://www.IRIN news.org. Accessed on 18/03/2009).

2.2.2 Less loss to follow-up at primary health care sites

Making ART available at more convenient sites could address some of the loss to follow-up. Studies have suggested that retention on ART is better at primary healthcare sites within the heavily affected communities rather than at large centralized hospitals (http:// www.msf.org.za/docs/lusikisiki_final_report_2006 pdf).

But primary healthcare sites can come in a range of shapes and sizes and have limits (staff, space etc) to their capacity as well. “Over time, the increase in access to care has resulted in improved early outcomes, offset in part by increased loss to follow-up,” said Dr. Cloete. Indeed, Dr. Gilles Van Cutsem of the MSF, noted that this had become a problem as the primary care ART sites in Khayelitsha have become “monster sites.” Relying on just a few large primary care sites could conceivably become just as bad as using larger hospitals. Clearly, there is a need to engage a wider range of partners and other strategies to improve follow-up.

2.2.3 Making better use of smaller primary care clinics, general practitioners and nurses

Recognizing that they needed to continue enrolling high numbers of people with HIV, some HIV/AIDS care providers in South Africa have opted for down-ward referral. After ART initiation, a patient is given an option to be referred to a general practitioner at a lower level, while a centralized pharmacy system retains the responsibility of providing the medications on a named—patient basis to the lower level health units so that people don’t have to travel all the way back to the hospital to refill their script. The retention rate after referral to a GP was 99 % (Mlambo, K et al., 2007). However, it has been noted that the majority of loss to follow-up occurs within the first six months on ART, usually before people become “stable” so this system of down-referral does not address most cases of loss to follow-up.

In Lesotho, it has been found that decentralizing ART provision to the primary care level, as opposed to referring patients down from hospital to clinic, provides many more access points to treatment and reduces bottlenecks to enrolment. Various studies have also proved that empowering nurses is essential for maximizing efficiency at the primary care level. Several other countries, including Malawi and Ethiopia, are now allowing nurse practitioners to prescribe ART (Ashie M et al., 2007; & Thistle et al., 2007).

2.2.4 Systems for defaulter tracing

Regardless of what type of site ART is being delivered by, a standardized system to quickly detect loss to follow-up needs to be put in place. According to experts in the monitoring of ART programmes in low resource settings with significant loss to follow-up, problems can be improved with innovative and simple and well defined techniques.

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One of the first steps is to develop standardized tools. Pre-ART and ART registers are used in order to identify who’s lost to follow up, as well as appointment books and a tracking register to monitor tracking and re-entry to care. Some programmes are employing dedicated people to track down defaulters.

In South Africa, it has been discovered that most of the cases of loss to follow up occur within six months of ARV initiation and death; which makes it important to consider home visits in trying to track those sick patients to come in. Some ART programs have ensured integration of people with HIV and the community into the clinical team using peer educators who are themselves patients in the Programme, to do the counseling and prepare the person for ART.

According to Dr.Worley, strong support groups are a well-noted mechanism to really help retain patients in care and to help find missing members. He also recommends task shifting and the use of community-based mechanisms. The support groups have proved vital in reducing stigma and discrimination, providing treatment literacy and tracking defaulting clients (Worley SB., et al., 2007; & Chirwa, Z and Africaner E, 2007).

Defaulter tracing means more than getting someone back on treatment; it is also clinical monitoring and case detection. In the TASO-HBAC study, the defaulter tracing mechanism led to one of the highest rates of retention in care ever reported in an ART Programme (only one out of 987 adults was lost to follow-up)( Etienne M et al., 2007). 2.7.0 Conducting Retrospective Chart Reviews

For over eight decades, the systematic investigation of historical records has guided various clinical researches (Butler & Quinlan, 1958; Wu & Ashton, 1997). The scientific utilization of existing health records is common in epidemiological investigations (Haley et al., 1980; Jansen et al., 2005), quality assessment and improvement studies (Allison et al., 2000; Kirkorian, 1979), professional education and residency training (Holmboe, Gross, & Hawkins, 1996; Neidich, 1990; Pan, Fergusson, Schweitzer., & Herbert, 2005).

The advantages of conducting chart reviews include: a relatively inexpensive ability to research the rich readily accessible existing data; easier access to conditions where there is a long latency between exposure and outcome; and most importantly, the generation of hypotheses that then would be tested prospectively( Hess, 2004; VonKoss Krowchuk, Moore, & Richardson,1995; Wu & Ashton,1997; Worster & Haines, 2004). However, the limitations of incomplete documentation, including missing charts, information that is unrecoverable or unrecorded, difficulty interpreting information found in the documents e.g. jargon, acronyms, photocopies, and microfiches), problematic verification of information and difficulty establishing the cause and effect, variance in the quality of information recorded by medical professionals(Dworkin , 1987; Hess,2004; Pan et al., 2005; VonKoss Krowchuk,1995),have discouraged researchers from adopting this methodology. A standard recommendation is that data collectors remain blind to the study hypothesis to minimize “subjectivity in classification in relation to personal theories about the study’s aims” (Worster & Haines, 2004).

Data collectors blind to the hypothesis decrease reviewer bias, specifically the possibility of their assessment being swayed by knowledge of others (e.g. investigators), concern over adversely affecting the study’s outcome, or interpreting their abstraction as too lenient or too harsh( Allison et al., 2000; Chaplan , Posner, & Cheney,1991; Goldman,1992; Wu & Ashton 1997). Data collectors must become familiar with a health record, be aware where the information is located, and strive to remain objective (Haley et al., 1980; Smith, 1996). Data collectors should be carefully selected and trained with the data collection instrument and the accompanying protocols and guidelines.

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It has also been reported that the accuracy of reviewers increases when the individuals know they are being monitored (Wu & Ashton, 1997). It is also important to the reliability of the investigation to determine the inter-rater reliability of both the data collection instruments and the individual data collectors. This can be accomplished through a pilot investigation and / or random checks.

In conducting any retrospective chart review study, sampling refers to the method by which study cases or records are selected from the target population or database (Worster & Haines, 2004). Three commonly used sampling methods in retrospective chart review are convenience, quota, and systematic sampling. In convenience sampling, the most common method, suitable cases are selected over a specific time frame; in quota sampling, a predetermined number of cases are sought from each site or diagnostic determinant; in systematic sampling, every ‘nth’ case is selected from the target population. Ascertaining the most appropriate sampling method depends on a number of factors including the importance of probability sampling, the epidemiological nature and prevalence of the specific condition, population availability, research budget, and time constraints.

The management of missing data poses methodological limitations in conducting chart review research (Hellings, 2004; VonKoss K. et al., 1995). Generally, managing missing values is treated either by the deletion of the case or variable, or imputing the missing value through averaging or maximum likelihood strategies (Dworkin, 1987; Worster & Haines, 2004). In case of variable deletion from the analysis, however, this can reduce the sample size or may introduce a hidden bias (Dworkin, 1987).

Imputing missing responses through statistical analysis is more common in very large computerized databases (Worster & Haines, 2004), and assumes that missing data are randomly absent. The most common maximum likelihood strategy is assigning the missing value as one response, such as “yes” or “no” question where the absence of a “yes” results in an immediate “no”. The most effective method to determine the development of any problems from missing data is to conduct a pilot study.

In view of the above literature, it is notable that hardly any studies had been conducted to identify issues related to retention in ART programs in a post-conflict setting in Northern Uganda. This made it compelling to pursue this particular study, in order to fill in the missing links. Nevertheless, there was a lot of missing data from the systematically sampled charts. Although the reviewers made every effort to review more charts, most of them lacked the key variables of interest for conducting survival analyses. This had an effect on the sample size, albeit minimal; and could have introduced a hidden bias.

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Chapter Three

Statement of the Problem 3.0 Statement of the Problem Northern Uganda has suffered the brunt of a 20 year- old insurgency pitching the Lord’s Resistance army (LRA) against the government forces. During this conflict, there has been a breakdown in social services and infrastructure. This region has an HIV prevalence of 10.9 %, far above the national average of 6.4 % (MOH, 2005). Various agencies in the region are providing comprehensive HIV/AIDS care, including antiretroviral therapy to HIV positive persons. Efforts have been concentrated on adherence monitoring. However, most government health units have suffered the challenge of recurrent ARV drug stock-outs due to several factors. This has had an impact on the retention and adherence of patients in ART programs. No one knows for how long patients on ART in post-conflict Northern Uganda are retained in ART programs. And if they are lost- to- follow up, no one knows the reasons why. Also needed is a better understanding of how predictors such as residence, alcohol use, level of education, among others, may influence retention of patients in ART programs in a post-conflict setting. There is also self-referral of clients from one unit to another as they seek more holistic care. Consequently, the status of the different health care units and levels as well as their inherent advantages and limitations in as far as retention is concerned is as yet unknown. When patients drop out of ART programs they get sicker with severe opportunistic infections that are more expensive to treat and difficult to manage; or they die. Those who stop taking antiretroviral therapy due to various reasons that are not yet clearly elucidated; also stand the risk of developing resistance to the relatively cheaper and convenient first-line regimens. Treatment discontinuation raises some of the same concerns about drug resistance as adherence does and even worse, negates much of the benefit sought by those in treatment programs. Drug resistant strains may be spread to the general population. A high rate of attrition from treatment programs thus poses a challenge to program implementers and constitutes an inefficient use of valuable and often scarce resources. The cost of running ART programs may increase due to the need for second-line and salvage regimens, which are more expensive. Second line regimens also pose adherence challenges due to pill burden and frequency and severity of side effects. The issue of retention of patients in ART programs therefore is of public health importance. 3.1 Justification for the Study There are very few published studies about retention in ART programs in Uganda. The Ministry of health/ AIDS Control Program have just concluded a rapid assessment of retention in health units, but what was done; the objectives and targets are as yet unpublished. This baseline survey on retention of patients in ART programs will probably be the first of its kind in post-conflict Northern Uganda.

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It will document the magnitude of the problem and help policy makers and program implementers to address the challenges of patient retention. Several studies have looked at how well patients stick to their day-to-day medication schedules, but how long patients stay in treatment programs, and what they must do to prevent illness and death from AIDS, has received little attention. It is worthwhile to note that adherence studies have always tended to basically address issues of only those patients that have been retained in the Programme. Rather than calculating weighted averages that are applicable to few, if any, ART treatment programs in sub-Saharan Africa, we should identify the factors that influence patient retention both at the individual level and the level of the program – elements that can inform appropriate interventions to increase patient retention. Information generated will guide the Northern Uganda Malaria AIDS Tuberculosis program (NUMAT) on how to strengthen the logistical and systems support to the targeted 23 NUMAT-supported ART clinics in Northern Uganda. A care and treatment model that may improve retention rates in post-conflict situations could also be developed. NUMAT could also gain an insight into the factors that affect adherence to antiretroviral treatment in the region; and be able to provide problem- specific solutions in a post- conflict situation. Policy makers and planners in the Uganda Ministry of Health could also benefit from this information to address the challenges facing health care systems in Northern Uganda, particularly in the context of HIV/AIDS. 3.2 Conceptual Framework Retention of patients in antiretroviral therapy programs is dependent on a number of factors .These can be conveniently classified as socio-economic, political, provider- related, client-related, and health- care system and drug-related factors. In post-conflict Northern Uganda, political factors are central to retention in ART programs. Insecurity, with the resultant displacement of populations into squalid camp conditions, or to stay with relatives, may determine whether they can easily continue accessing antiretroviral therapy. Health care systems and drug related factors affecting retention include monitoring and evaluation systems, patient –tracing procedures, toxicities, stock-outs, availability, access to health care, pill burden, opportunistic infections management, and nutrition support. Client- related factors include the age, CD4 counts at initiation, the perceived quality of life, presence of symptoms of AIDS, cultural beliefs and attitudes particularly faith- healing, disclosure status, parenthood or orphan hood status, community support system, counseling, post-traumatic stress disorders, alcohol and drug abuse, level of education, beliefs, attitudes, and gender, among others. A patient’s health-seeking behavior may also be determined by the behavior change communication and I.E.C strategies that a given health care system provides. The CD4 count at initiation could also be influenced by the level of awareness. Socio-economic factors that affect retention of patients in ART programs include lack of transport, cost of drugs, poverty ,stigma and discrimination, occupation, gender, cultural beliefs and attitudes, disclosure of HIV sero-status, geographical location, parenthood status, orphan hood, lack of a treatment supporter, mobility of clients due to family break-ups or relocation and community support.

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Provider-related factors include knowledge and skills in ART provision, attitudes towards patients, motivation, beliefs, the quality of the service, capacity to follow-up and other patient – tracing mechanisms available. This cause and effect relationship is best illustrated in the figure below.

3.3. Research Questions

1. What factors are significantly associated with retention in antiretroviral therapy programs in

post –conflict settings?

2. What is the level of retention of patients in antiretroviral therapy programs in post- conflict northern Uganda?

3. What are the predictors of attrition in ART programs in post-conflict Northern Uganda? 4. What are the reasons underlying loss-to- follow up in antiretroviral therapy programs in

post-conflict northern Uganda?

Retention of HIV Positive persons in Antiretroviral Therapy Programs.

Political Factors: insecurity in the war affected areas, residence (IDP, transit, with relative, original village home etc); equity and access to health services.

Socio-economic Factors: stigma and discrimination, occupation, gender, cultural beliefs and attitudes, disclosure of HIV serostatus geographical location, parenthood status, orphan hood, lack of treatment supporter

Client –related Factors: Age, Starting CD4 count, Presence of symptoms, state of well-being of patient, health seeking behavior, beliefs, etc

Provider- related factors: Knowledge, attitude, motivation, beliefs, quality of services, and capacity to follow-up, patient tracing mechanisms

Health Care system and drug- related factors: Equipment, adverse drug events, M&E, patient tracing procedures, stock-outs, availability, pill burden. Access to health units.

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Chapter Four

Study Objectives 4.0 Overall Objective

To assess the current status of retention of patients started on antiretroviral therapy at 17 sites in post-conflict northern Uganda so as to generate practical interventions for ensuring high levels of retention in NUMAT-supported ART programs. 4.1 Specific Objectives

1. To identify the factors affecting retention and adherence for patients on antiretroviral therapy in post-conflict Northern Uganda.

2. To determine the retention rates for clients started on antiretroviral therapy in post-conflict

Northern Uganda. 3. To establish the existing strategies for retention and adherence to antiretroviral therapy in

post-conflict Northern Uganda. 4. To determine the current mechanisms for monitoring retention in antiretroviral therapy

programs in post-conflict Northern Uganda.

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Chapter Five

Methods and Materials 5.1 Study Site: The study was conducted in Northern Uganda at 17 NUMAT-supported ART clinics, targeting health center IVs, district hospitals and 1 regional referral hospital to cater for the various levels of care. These included Awach and Lalogi health center IVs in Gulu district; Anaka in Amuru district; Padibe, Namokora and Kitgum hospital in Kitgum district; Pajule and Pader in Pader district; Lira Regional Referral hospital, Amac, Ogur, Orum, and Alebtong in Lira district; Dokolo health center IV in Dokolo district; Amolatar health center IV in Amolatar district; Aboke and Aduku in Apac district; and Anyeke health center IV in Oyam district in Northern Uganda. All these health units are located in the northern part of Uganda, an area which has suffered armed insurgency for the last 20 years. These sites were purposively selected. 5.2 Study Population This study had two study units: the ART Clinic Managers and HIV positive patients / care givers. The ART Clinic Managers served as key informants. For the health facilities, we took a census i.e. the total sample of 17 facilities. Within the facility, we held Key Informant Interviews with the ART Clinic Managers using a checklist adapted from the Ministry of Health ART Sites Accreditation Criteria. People living with HIV/AIDS who are enrolled on ART and are registered at these 17 health units participated as respondents in the focus group discussions during the study. The respondents were found at the health center clinics, or communities. Those identified as having defaulted on ART were traced up to their homes, and reasons for their loss-to- follow up identified where possible. 5.3 Study design and sampling procedures This study was a cross-sectional survey that employed triangulation of both qualitative and quantitative research methods. Data was collected over a period of 2 months. The estimation of the retention rates was determined by conducting a retrospective review of systematically sampled medical records of ART patients at each of the health facilities. The ART Clinic registers and Pharmacy logbooks that contained the lists of all patients ever started on HAART at each selected facility were used as a basis for this record review. Each facility provided a list of all patients started on HAART from start of availability of HAART at the site till 3 months before the commencement of the study. To avoid selection bias, care was taken to identify all patients ever started on HAART at the site. This process included identifying all the sources of HAART for each study site to ensure that all lists of HAART patients were included in the sampling frame. If no complete list of all patients ever started on HAART could be prepared, a list of all patients attending at the clinic between start of availability of HAART at the site till 3 months before the planned review was used.

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Systematic sampling of every 5th patient’s chart was done for all patients who had initiated ART at least 3 months prior to this study. An anonimized list of patient identification numbers was then sent in spreadsheet format to the data coordination centre. A total of 1032 patient records were retrieved and systematically reviewed to identify the variables of interest. If a randomly selected patient’s record conformed to the study selection criteria, the data collection form would be completed based on the medical chart and pharmacy records review. If a patient that was systematically selected was not eligible for the study; the age, gender and reason for non-eligibility would be noted on the screening log. In this case, the next patient that was not already selected in the systematic sample would be selected as a replacement. Patients whose records were reviewed had to be a minimum of 12 years of age and had initiated ART treatment at least 3 months prior to the data collection. Each study site generated a list of patient ID numbers corresponding to ART patients who fitted the eligibility criteria. From that list the medical records from 1032 ART patients for review were selected using systematic sampling procedures. For each of these patients the following data were extracted from the ART Clinic Register and the pharmacy logbook and stored in a template database:

Baseline characteristics: gender, age, village (distance to ART clinic, from predefined list), and pre-treatment weight;

Clinical measures: CD4 cell count (pre-treatment, lowest ever and most recent); and stage defining conditions that occurred at last clinic visit;

ART regimen start date; Last visit date (extracted from last clinic visit date, and last pharmacy visit date); ART regimen at last visit; and reasons for changing ART regimen if different; Pregnancy state at last clinic visit; and weight at last clinic visit; TB treatment status(on TB treatment, finished TB treatment in the past, never treated for

TB); Last pharmacy ART refill visit date (to determine time to discontinuation of ART) Was patient transferred out (yes/no) and if yes, the date of the transfer and where they were

transferred Did patient die (yes/no); and the date of death if available/applicable Functional status at last clinic visit (working, ambulatory, bedridden)

The primary variable of interest was retention in the ART program, defined as having received one of the following services at least once in the previous 3 months: a clinic visit or drug refill (pharmacy). In addition, retention (continuation) on ART was studied as a secondary variable of interest. Retention on ART was defined as having had an ART drug refill during the previous 3 months. 5.4 Inclusion Criteria

• ART Clinic Managers who were employed at the 17 health units at the time of the study; • People who are living with HIV/AIDS and were 12 years of age and above. • Patients registered and enrolled onto ART at least 3 months prior to commencement of the

study (enrolled by October 2008) at the selected study sites.

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5.5 Exclusion Criteria

• Children who are on ART, but were less than 12 years of age were not interviewed. • Health workers who were absent, or, on leave, during execution of the study. • Patients who were very sick were not permitted to participate in the study. Surrogate

interviewees were used instead, where necessary. 5.6 Sample Size Determination For the patients, the Kish – Leslie (1965) formula which takes consideration of a finite population was used to determine the sample size. We used probability proportionate to size (PPS) to arrive at the actual numbers of patients’ charts to be reviewed per health facility. The formula is as follows: N = Z²pq/ d² Where n is the sample size, Z is the confidence interval, p is the proportion of patients who were retained in ART programs; q was the proportion of patients lost-to- follow up; and d was the margin of error for the 95% confidence interval. N = 1.96² x 0.85 x 0.15 / 0.05² = 3.8416 x 0.85 x 0.15/ 0.0025 = 196 Using a 50%age adjustment to cater for missing data due to poor recording and capture, an adjusted sample size estimate of 294 charts was targeted for the study. A total of 1032 charts were reviewed in all, to cater for missing data. However, after data cleaning, only 239 charts (23.2%) were found to contain all the desired variables. Therefore the anticipated sample could not be attained due to gaps in data recording at the study sites. Patients who were identified as lost to follow-up during chart review were traced up to their homes as defaulters by the survey team, with the aid of their location addresses and the Network Support Agents or community guides. Those found alive and not very sick were interviewed to find out the reasons why they left the ART program. For those patients who were absent; too weak or too ill to answer the questions, a surrogate interviewee was used. For communities still in the camps, we used the Camp Leaders to locate the defaulters to be interviewed. An attempt was made even to search for those who could have returned to their villages, through the local councils. 5.7 Sampling frame This comprised of all patients started on ART in 17 HIV/ART clinics under the NUMAT operational area. 5.8 Sampling Probability Proportional to Size (PPS) sampling procedure was used to select 294 patients. A list of all the 17 facilities together with their number of patients on ART was drawn. Another column on the list had the cumulative number of HIV positive patients per health facility.

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The overall total number of patients on ART was then divided by 294 to get the sampling interval 4. A random number (r) would then be randomly selected from the charts. From then on, every 5th chart was systematically selected for review. The selected charts were then reviewed until the number allocated per health facility was attained. Charts with a lot of missing data were excluded and instead the subsequent chart picked for review. However, because we anticipated to encounter lots of charts with missing data, more charts were reviewed at each facility. Consequently, a total of 1032 charts were reviewed. Table I: Probability Proportionate to sampling for the NUMAT-supported health Units Name of health unit Total number of patients

on ART as of October 2008

Selected numbers

1.Dokolo 526 83 2.Orum 118 26 3.Amach 992 85 4.Ogur 450 42 5. Alebtong 270 54 6. Amolatar 230 39 7. Anyeke 418 49 8. Aboke 370 60 9. Aduku 273 56 10. Lira Regional Referral 1250 269 11.Awach 40 1112.Kitgum Hospital 800 136 13. Padibe 62 29 14. Pajule 186 23 15. Atiak 146 41 16.Anaka Hospital 778 31 17. Namokora 66 19 Total 6975 1032 For the health facilities, we took a census of the total number of 17 health units. All the systematically sampled patient charts, ART Clinic registers and pharmacy logbooks from the 17 purposively selected health units were reviewed to determine loss- to- follow-up and death of clients 3, 6, 12 and 24 months from ART initiation. At each of these facilities, a key informant interview was conducted with the ART Clinic Manager (In charge) to identify the ARV commodity supply system, and the human resource gaps using a checklist for the different levels of health care that was adapted from the Uganda Ministry of Health Accreditation Criteria for ART sites. Two focus group discussions of 8-12 participants each, (one for females; another for males) were also held with PLHIV who are still accessing care at each of the 17 health units; until the information generated was generally similar. The purpose was to get the clients’ perspective of the factors affecting retention in ART programs in this setting.

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One Focus Group Discussion was held with ART Clinic Managers from the Lango sub-region; and another with those from the Acholi sub-region in order to gain an insight into the program level factors that could affect retention and adherence to ART in this region. 5.9. Data Collection Techniques The data for this study was collected using the following techniques:

• Structured questionnaire for the ART Clinic Managers • In-depth interview question guide for traced defaulters and / care givers( for the very ill) • Focus Group discussion guide for PLHIV still in care. • Review of the Clinic ART register and Pharmacy logbook.

5.10 Data Collection Procedure In order to determine the retention rates for clients started on antiretroviral therapy in northern Uganda review of the ART clinic registers and pharmacy logbooks was done. To establish the existing strategies for retention and adherence to antiretroviral therapy in Northern Uganda, Focus group discussions and key informant interviews were conducted with the ART Clinic Managers. This also helped to determine the current mechanisms for monitoring retention in antiretroviral programs in Northern Uganda. In order to identify the factors affecting retention and adherence for patients on antiretroviral therapy in Northern Uganda focus group discussions with patients who still access care and treatment from the health facilities; as well as in-depth interviews with those who defaulted on treatment were conducted. All the data collection tools were pilot-tested in a mini-survey at a non-participating health unit (Gulu Regional Referral hospital) to ensure their validity and reliability. The content validity was analyzed by computation of the content validity index (CVI).The instrument was considered suitable if the CVI was 0.70 or higher. Reliability was assessed using Cronbach’s coefficient alpha. The instruments were considered suitable for data collection if the reliability was 0.70 or higher. 5.11 Qualitative methods Key informant interviews and Focus Group Discussions were conducted with the ART Clinic Managers in their offices. Focus Group discussions were held with clients according to gender and age bracket. In-depth interviews were held with the defaulters or their caregivers where necessary. Emerging themes were identified and categorized. 5.12 Quantitative methods Quantitative data was collected using structured questionnaires. Patients’ charts, ART Clinic Registers and Pharmacy Logbooks were reviewed, with the aid of a facility audit checklist administered by trained research assistants, who were working outside the establishment to minimize observer bias. This data was collected over the course of the week, spanning a period of two months (February-March 2009).

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Each sampled medical chart was reviewed once only; and to ensure that there was no double review, the allocated study code numbers were recorded and the list always referred to before conducting further chart reviews. The interviews were conducted in the usual clinic environment; hence the investigators were enabled to report on the daily factors affecting retention of patients in ART programs. The research assistants, under the direct supervision of the principal investigators checked for any omissions and errors in recording responses while they were still at the study site. Data collection went on until the required sample from a particular study site was achieved. Extra interviews were conducted to cater for invalid questionnaires and missing data. The health unit served as the unit of analysis. 5.13 Measurements and Study Variables ‘Retention of patients in ART programs’ was the dependent variable. It is a binary variable with “good” and “poor” as the responses. The Independent variables included the following patient characteristics:

• Age, • Marital status, • Sex,

Residential address (camp dweller, urban, or original village), • Health unit, • CD 4 count at initiation of ART, Distance from the health unit • Nature of health facility ( free or paying)/ ownership • Level of health care (primary, secondary or tertiary/ referral level) • Cumulative Number of patients per health unit • Number of clinic visits missed • Use of a treatment supporter Number of patients who remain in care but stop taking ARVs • Duration of follow-up • Deaths • Barriers to adherence • Patient tracing procedures • Loss to follow-up • Year of ART program initiation

5.14 Execution of the study in the Field Ten Research Assistants, two of whom later served as data entrants, were selected for the study. Three of the Research Assistants were clinical officers, who were deemed technically competent to conduct medical chart reviews; two were graduates of population studies; while the rest were social sciences degree holders who had skills in conducting qualitative research. Their selection aimed at ensuring that they were familiar with the language and geography of the communities around the study sites. However, they were got from outside the particular study settings so that they were independent of the respondents at any of the study sites.

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The research team ensured standardization in data collection by conducting a 3-day centralized training for the research assistants on the study objectives, data collection methods, procedures and processes; WHO Clinical Staging; ART eligibility criteria; review of the data-collection tools; as well as legal and ethical issues in research. They were involved in piloting of all the data collection tools, conducting FGDs and in-depth interviews with clients, and review of ART registers and pharmacy logbooks. Their proficiency in the local languages eased communication during the data collection exercise. At the end of each day, the teams would report their experiences to the Principal Investigators (PI) or their representative. The PIs was responsible for the execution of the study through active participation in data collection and close supervision of the research assistants. They also critically examined all the collected data to ensure its accuracy and completeness. 5.15 Instrument Pre-testing All data collection instruments were pre-tested at Gulu Regional Referral hospital to determine their suitability for collecting the required data. After pre-testing, the instruments were refined and the necessary changes made. This also provided an opportunity for improving the data collection skills of the Research Assistants. After this, the FGD and the In-depth interview question guides were translated into Acholi and Langi to facilitate communication during interviews. 5.16 Data Management When the filled tools arrived at the data management centre; they were cross-checked for consistency and validity. For example all questionnaires had the name of the health facility, district and code of the interviewer. The tools were checked to see if they were fully filled. Where the information was incomplete it was noted and reasons for incompleteness established. This editing process was followed by coding of all the questions on the tools. Established coding formats were applied for ease of comparison. For example coding for reasons for loss of follow-up used previous codes. Coding was followed by the data entry process. Double data entry was done. All data was entered in EPIDATA V3.1. The software is easy to learn and occupies little space. In addition, the consistency and validity checks imbedded in the data entry screens are robust. Data cleaning was done with the aid of Epi-info version 2000, to crosscheck for any errors in data entry. Where there was a difference in the data entered, the questionnaires were selected out and one of the data bases corrected; and was subsequently used as the final data base for analysis. Computer data cleaning; editing and immediate storage with back-up copies was done on a daily basis. A random sample of the original completed questionnaires was compared with the computer print out to assess the accuracy of the entered data. Frequency distributions and cross tabulations of all variables were generated. All the raw data forms were put in coded box files and securely kept to avoid losing them during the course of the study. 5.17 Quantitative Data Analysis Data analysis was carried out using the Statistical Package for STATA Version 9. Outcomes were expressed as ratios and percentages. Means, standard deviations, and simple proportions were

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generated as appropriate to describe the data. Data was then summarized in tables, graphs, pie charts, cohort survival functions estimated at 3 months, 6 months, 12 months, and 24 months; and histograms. Bi-variate analysis was done to determine significant associations between the dependent variable and the independent variables. Odds ratios, p-values, 95% confidence intervals; log ranks as well as Chi-square test statistics were computed. Variables that were significantly associated with retention of patients in ART programs in the bi-variate analysis were entered into a logistic regression model with retention as the dependent variable. The regression model then generated the outcomes of interest, particularly the factors affecting retention of patients in ART programs in a post-conflict setting. Possible predictors of retention, both individual risk factors and program characteristics were assessed in the analysis, and are described in the table below: Cohort survival functions were done to determine the levels of retention at the end of the follow up periods of 3 months, 6, 12 and 24 months. Table II: Key independent variables Variables Source Definition Patient-related factors Age ART clinic register Year of persons birth Gender ART clinic register Male/Female

Distance patient lives from clinic

ART clinic register Codes to be developed for each site

CD4 cell count (pre-treatment, lowest ever and most recent)

ART clinic register Continuous variable

Lymphocyte count (pre-treatment)

ART clinic register Continuous variable

System of care or program related factorsClinic visit/drug refill schedule ART Clinic Manager 1,2, or 3 months Level of care ART Clinic Manager Tertiary, secondary and

primary Type of institution ART Clinic Manager MOH, NGO, FBO Funding source ART Clinic Manager Government supported,

PEPFAR, Global Fund, other

Number of clients ART Clinic Manager ART clients ever enrolled Date ART program started ART Clinic Manager dd/mm/yyyy System for tracing defaulters ART Clinic Manager Yes/no Pharmacy at the treatment center

ART Clinic Manager Yes/no

Urban/rural site ART Clinic Manager Not defined The retention rates at each ART providing site were estimated using survival analysis methods. The Kaplan-Meier survival curves were presented together with 3, 6 months, 12 months, and 24 months retention rates. No finite population corrections were applied when estimating the retention rates.

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Retention in the ART program was defined as a visit to the clinic for at least one of the following services at least once in the past 3 months: clinical visit and/or pharmacy drug refills. For the construction of the Kaplan-Meier curves the following conventions were used:

The “event” of interest was discontinuation from the ART program. Patients retained in the program were censored at their date of last clinic visit, or drug refill,

whichever was the latest (“last visit date”). Patients who were transferred out were censored at the date of transfer. Deaths were considered as discontinued (event) at date of death (or last visit date if death

date was unavailable or if death date > 3 months from the last visit date). Patients who did not come to the clinic during the last 3 months, and were not transferred

out and did not die were considered as discontinued from the ART program (“event”). As discontinuation (“event”) time, the last date of any of the 2 services (clinical visit, or pharmacy visit) was used.

Similar conventions were applied for retention on ART. However, patients who did not receive an ART drug refill during the last 3 months, and were not transferred out, were considered as discontinued from ART. The date of last ART refill, if not within the last 3 months, was considered the date of ART discontinuation. In addition to estimation of the retention rates, we also examined predictors of overall retention in care. Predictors of retention in the program were assessed using proportional hazards model, assuming a Weibull distribution for our duration, adjusted for clustering at the site level. Possible predictors that were considered included individual disease and demographic characteristics, as listed above, and site level characteristics as collected from the ART Clinic Managers. We performed the multivariate modeling as follows: (1) We described the associations between retention and individual and program level characteristics using hazard-ratios and 95% confidence intervals. Graphical methods were used to select the appropriate cut-off value or functional relationship for continuous predictors. We also assessed the significance of each predictor using Log rank Chi square test statistic. We selected all predictors significant at 5% and 10% levels for the construction of the multivariable Proportional hazards model, assuming an appropriate distribution of the dependent variable. (2) Variables that had p-values less than or equal to 0.1 at bi-variate analysis were entered into multi variate analysis. However, variables with p-values greater than 0.1 which have been found to have biological plausibility in other studies were also considered. The final model was then described using adjusted hazard ratios and 95% confidence intervals.

5.18 Qualitative Data Analysis The Principal Investigators cross-checked all data received for completeness, validity, precision and accuracy. Content analysis was used to analyze the qualitative data on the basis of emerging themes and sub-themes in line with the study objectives. Participants’ responses were coded and typed in Microsoft Word 2007, and later proof-read. The data was then transferred to Nvivo Statistical package to aid analysis. The qualitative data was analyzed by formulating tentative themes and sub-themes, which were continuously analyzed before, during and after data collection. Descriptive summaries and quotes were used. Trend

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analyses of the In-depth-interviews and Focus group discussions were useful for identifying the major issues for each of the study themes and sub-themes. This also facilitated comparisons and contrasts of participants’ views within and among the different study sites by gender, location and age. 5.19 Data Quality Control The Principal Investigators and / or their representative directly supervised the data collection, data entry and analysis. The research assistants underwent 3-days’ training in proper data collection techniques before they set out to work. They were instructed on how to administer the in-depth interview questionnaires, focus group discussions, key informant interviews as well as on responsible conduct of research, with emphasis on research ethics. An extensive discussion of the questionnaires was done during training on question-by-question basis. The questionnaires were also pre-tested on 25 individuals at Gulu Regional Referral Hospital HIV Clinic; and accordingly modified to incorporate the changes. At the end of each data collection day, a de-briefing meeting was held between the data collectors and the Principal Investigators or their representative to discuss and resolve any challenges that could have been encountered during the data collection process. In situations where this meeting was not possible because of the vast distances between the study sites, a phone discussion was conducted with the Team Leaders for the respective Sub-regions at the end of each day. 5.20 Study Limitations and Remedial actions

Recall bias could have occurred during the key-informant interviews with the ART Clinic

Managers. This was minimized by use of health unit records.

ART Clinic registers had a lot of missing data; in which case the researchers reviewed more charts to get representative data. Triangulation of data sources also helped minimize this effect. Most medical charts and ART registers as well as Pharmacy logbooks lacked information on pregnancy status, CD4 count record, Nevirapine exposure, total lymphocyte counts and distances from the health units. In some sites the data management system was so poor and disorganized. In many instances the health workers’ WHO Clinical staging was very doubtful; since many recorded the patients initiating ART while in stage I or II, even without a CD4 count result. Where available these data elements were collected. These data sets with missing variables could have introduced a hidden bias; since we could not easily determine whether they had a positive or negative effect on the outcomes of interest. The principal investigators played an important role in working with the study sites and research assistants to ensure the integrity of data throughout the course of the study. More charts were reviewed to eliminate this bias.

A number of defaulters who were tracked were found to have traveled to South Sudan on

business trips, yet this was outside the study area. Others had transferred to Abim district, in the volatile Karamoja region.

It was not possible to track defaulters who were said to have been incarcerated in various prisons on defilement charges because of the bureaucracy involved. Neither was the team able to track and find any soldiers who had defaulted probably because they were transferred without the ART clinic manager’s knowledge and the community guides were very reluctant to take the team to the army barracks.

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5.21 Ethical Considerations The Principal Investigators sought permission from the National Council of Science and Technology (NCST). Approvals were then got from the District Health Officers to proceed with data collection at the 17 health units. Before data collection began, due care was taken to ensure that informed consent was obtained from all respondents. The informed consent included explanations about the purpose and objectives of the study, the benefits and risks that could accrue from the study; the rights of the respondents, reimbursement arrangement and reassurance on confidentiality. An opportunity was availed to each respondent to ask questions and / or seek further clarification. Respondents were free to refuse to participate in the study and this did not affect their right to care or their relationship with their employer. This study had no explicit risks to the study subjects, but its findings could inform processes for improving the retention of patients in ART programs in post-conflict settings. Patients who appeared to be very sick were not interviewed. Surrogate interviewees were used instead. Unique identification numbers instead of names were indicated on the data collection form. Confidentiality and integrity of all respondents was observed throughout the course of the study. Key informants were not directly linked to the comments made during the study so as to give them freedom to express their views frankly and freely. Key informants were interviewed in their offices to ensure privacy and confidentiality. All data records were kept in box files for safety and confidentiality during data collection and analysis.

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Chapter Six

Results from the Study 6.1 Introduction: This study was conducted between February and March 2009. A total of 1032 ART Clinic Chart registers were reviewed; 17 key informant interviews conducted; and 22 Focus Group discussions held with people living with HIV/AIDS accessing ART at 17 sites across northern Uganda. Defaulter tracing was done on 35 patients who had been identified as lost to follow-up. All respondents in this study gave written informed consent to participate in the survey. The findings are as presented here below: Bar Chart 1: Percentage distribution of the Reviewed Medical Charts by District

From the Bar Chart above, it is evident that Gulu, Pader, and Amolatar districts had the lowest percentages of patients accessing ART: at 1%; 2.4%; and 4.4% respectively. It was not clear whether this was due to geographical barriers (particularly for Amolatar); or due to community-related factors such as stigma.

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6.1.1 Health Facility Distribution by level of service delivery

All the health facilities surveyed were government- owned but supported by NUMAT program; and pie chart 1, below shows their distribution by level of service delivery. There were 10 primary health care centers (Health Center IV); 6 district hospitals; and 1 regional referral hospital. Pie Chart 1: Distribution by level of service delivery

5.9%

35.3%

58.8%

Regional Referral Hospital 

District based hospital 

Primary Health centre 

6.1.2 Socio-demographic characteristics of the HIV/ART patients at the 17 health units

The ART Clinic Managers provided a record of the numbers of adult HIV patients ever registered and those currently registered at the time of the study: broken down by gender and age group, where available. Children were defined as patients less than 14 years of age. The average number of adult HIV positive patients ever registered and currently registered were higher for females as compared to males at all levels of service delivery (See Tables 1 and 2 below). Table 1: Number of adult HIV positive patients ever registered at the HIV clinics Type of facility (Number responding)

Mean Number of HIV+ Male adults ever registered (%)

Mean Number of HIV+ Female adults ever registered (%)

Grand total reported (range for patient numbers )

Regional referral hospital (1)

3773 (34.3) 7237 (65.7%) 11010

District based hospital (4)

562.2 817.25 10572 (1125-5054)

Primary health centre (10)

247.7 551 7987 (283-1674)

From the above table, it is notable that the number of patients registered was lower at the primary health care level (Health Center IV) than at the district and regional referral hospitals. This could be attributed to the order in which the ART programs were initiated; but could also be a sign of an ailing health care system at the primary care level. The impact of HIV-related stigma at community-level on the choice of where the patient seeks AIDS care and treatment cannot be ruled out as well.

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Table 2: Adult HIV positive patients currently registered at the HIV clinics Type of facility (Number responding)

Mean Number of HIV+ male adults currently registered

Mean number of HIV+ female adults currently registered

Grand total reported (range for patient numbers )

Regional referral hospital (1)

+

District based hospital (2)

433.5 894.5 2656 (1004-1652)

Primary health centre (10)

130.7 292.5 4232 (17-928)

+ Data were not available The mean number of male children ever registered was higher than that of female children at the district and health center IV levels of service delivery (see Table 3). However, the mean number of female children currently registered at the HIV clinic was higher than that of males at all levels of service delivery (see Table 4).We did not come across any biologically plausible explanation for this discrepancy. Table 3: Number of HIV positive children ever registered by gender Type of facility (Number responding)

Mean Number of HIV+ male children ever registered

Mean number of HIV+ female children ever registered

Grand total reported (range for patient numbers per site)

Regional referral hospital (1)

452 531 983

District based hospital (3)

66.3 58 373 (108-151)

Primary health centre (10)

33.3 28.3 568 (14-143)

Table 4: Number of HIV positive children currently registered by gender Type of facility (Number responding)

Mean Number of HIV+ male children currently registered

Mean number of HIV+ female children currently registered

Grand total reported (range for patient numbers )

Regional referral hospital (1)

+ + +

District based hospital (4)

54 85 556 (33-300)

Primary health centre (9)

80.1 154.5 2112(14-1775)

+ Data missing

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6.1.2.1 Patients on ART by gender The number of females on ART was higher than that of men at all levels of service delivery, Table 5 below. The average number of patients initiated on ART on a typical clinic day was 6 patients; with a range of 3-12 patients. Table 5: Patients on ART by gender by 31st December 2008 at 17 study sites:

Type of facility Number of females

Number of males

Total Percentage (%)

Referral hospital (1) 2107 1087 3194 53.3 District based hospitals (3)

664 376 1040 17.4

Primary Health care (10)

1143 614 1757 29.3

Total 3914 2077 5991 100.0 Table 6: Demographic characteristics of the patients on ART at the 17 health Units Variable Frequency (n=1032) Percentage (%) Age group 8-29 151 14.6 30-39 328 31.8 40-49 230 22.3 50+ 110 10.7 Not recorded 213 20.6 Sex Male 314 30.4 Female 718 69.6 Bar Chart 2: Showing percentage of patients on ART by age-group

14.6

31.8

22.3

10.7

20.6

0

5

10

15

20

25

30

35

Min‐29 30‐39 40‐49 50+ Not recorded

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From the table above, it is notable that the age groups 30- 49 constitute over 50% of the ART beneficiaries at these sites; while females account for close to 70% of the patients on ART in the region(see pie chart 2,below).This implies that these age groups could be the most infected with HIV/AIDS. This correlates well with the findings of the 2005 national Sero-behavioural survey. More females are affected by the HIV/AIDS epidemic; though the small numbers of men accessing ART could be attributed to their poor health seeking behaviour. This requires that interventions that target men are put in place.  Pie Chart 2: Sex distribution of patients on ART  

  According to the findings in Table 7 below, for those charts where the distance of the patients’ homes from the health facility were recorded, only 6.2 % of the patients were found to be residing within 5 km radius of the health unit. This highlights the role of distance as a geographical factor that could have an effect on the long-term retention in ART programs in this region. However, since these distances were just estimated by the patients they may not be accurate. On the other hand, a distance which is 5km and above, for an HIV/AIDS patient is also a great strain to a person who comes to the health facility by foot.         

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   Table  7:  Socio-demographic Characteristics of patients accessing ART at 17- NUMAT supported sites in Northern Uganda. Variable Frequency (n=1032) Percentage (%) Marital status Married 420 40.7 Widow/Widowed 210 20.4 Other (single& separated) 137 13.3 Not recorded 265 25.7 Distance to the Health facility

<=5km 64 6.2 6-10km 182 17.6 11-15km 114 11.1 16+km 100 9.7 Not recorded 572 55.4 Medical Charts distribution by District

Gulu 10 1.0 Lira 448 43.4 Kitgum 183 17.7 Apac 138 13.4 Dokolo 77 7.5 Pader 25 2.4 Amolatar 45 4.4 Amuru 52 5.0 Oyam 54 5.2 6.2 ART Drug Combinations in Use at the 17-Health Units: Table 8 below, shows that where as the majority of patients on ART were initiated on Stavudine-containing combinations, overtime this has been overtaken by Zidovudine-containing combinations, most probably due to the known adverse events associated with the former drug; hence the Ministry of Health policy to shift patients to Zidovudine. The statistics in the table also indicate that fixed-dose triple-drug combination pills were more popular for ART prescription than double combination or single antiretroviral drugs. This can be attributed to efforts to minimize pill burden in order to enhance adherence. ART clinic managers were asked whether drugs were available to accommodate needs of patients who may need to switch to second line regimens and 7 of the 17 answered in affirmative while the rest said no.

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Table 8: ART Drug combination Drug combination 1st ART

prescribed (n=1032)

2nd ART prescribed (n=291)

3rd ART prescribed (n=105)

Triple combination: three drugs combined in one pill

d4T (30), 3TC, NVP 644(62.4) 39(13.4) 65(61.9) d4T(40), 3TC, NVP 11(1.1) 3(1.0) - AZT (ZDV), 3TC, NVP 234(22.7) 192(66.0) 22(21.0) TDF, FTC, EFV 1(0.1) Double combination: two drugs combined in one pill (including boosted PIs)

AZT (ZDV), 3TC 113(11.0) 40(13.8) 7(6.7) TDF, FTC 3(0.3) 1(1.0) LPV, RTV - 1(0.3) 1(1.0) Single antiretroviral drug AZT (Zidovudine/ ZDV) 4(0.4) 10(3.4) 10(9.5) d4T (Stavudine) 24(2.3) 5(1.7) 3TC (Lamivudine) 21(2.0) 6(2.1) 1(1.0) NVP (Nevirapine) 9(0.9) 5(1.7) EFV (Efavirenz) 132(12.8) 49(16.8) 17(16.2) TDF (Tenofovir) 1(0.1) 1(0.3) NFV (Nelfinavir) 1(0.3) FTC (Emtricitabine) 1(0.3) Table 9: Reasons for change of ARV combination Reason Combination

One (%) (n=291)

Combination Two (%) (n=105)

Combination Three (%) (n=26)

Starting TB treatment 7(2.4) Adverse reactions 13(4.5) Treatment failure clinical 1(0.3) 3(2.9) 1(3.9) Pregnancy 1(0.3) Stock out * 157(54.0) 70(66.7) 21(80.8) Other 24(30.2) 5(4.8) 1(3.9) Not recorded 88(30.2) 27(25.7) 3(11.5)       

47

    Bar Chart 3: Change of ART combination  

  From Table 9 above, it is worthwhile to note that the commonest reason for change of ARV drug combinations was Drug Stock-Out, at 54%; 66.7%; and 80.8 % for each round of switching therapy, respectively. This is followed distantly by occurrence of adverse reactions, at 4.5%. This finding reinforces what respondents in the FGDs said about drug availability at most health units:   “MOH- I have a big problem with them, there is always a communication gap between the health unit and National Medical Stores (NMS), they claim they do not receive our returns. And if they do you a favor to bring you drugs, it will be the wrong consignment of drugs for example, d4T instead of AZT and we look stupid before the patients, If possible NUMAT should provide us with all the drugs.”(Female health worker- Lango Sub region). One respondent in the FGD for ART Clinic Managers had this to say: “We have no problem with NUMAT with the time of delivery of anti-malarial drugs, but they are not providing Septrin for some of our units, while for those which are getting Septrin from NUMAT, its irregular. But with NMS, this is a body that seriously misplaces our documents and there is mis-coordination between Entebbe and they have very poor delivery schedules. So I think they should buy more Lorries or they decentralize.”(Male Clinical Officer-Acholi Sub region). Then one nurse interjected, “Me I think NMS will never improve, I think NUMAT should go to Joint Medical Stores (JMS) instead. We fear for our lives because of stock outs.”(Female health worker- Acholi Sub region).

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One PLHIV was even more dramatic in her comment during the FGD: “ARVs are scarce, they are not sold in clinics, so when they are out of stock, I stay without treatment.”(45 year old female PLHIV, Alebtong). One of the nurses said (with a lot of anger and frustration): “We always have constant stock out of essential drugs, including anti malarial drugs (not ARVs); yet these people are too poor. When you send an attendant for I.V fluids, they don’t come back!” “Patients come thinking services are free especially ARVs, but when you identify an OI and the patient has no money, you have no option but to tell them to come with money before the OI can be treated, it’s so painful to us!” said an ART Clinic Manager from a Private-for-profit HIV clinic. 6.3 Clinical factors Table 10: Comparison of weight and CD4 cell count at ART initiation and at last clinic visit  Variable   Initiation of ART(n=1032) At last clinic visit(n=1032)Weight      <=45kg  208(20.2)         98(9.5) 46+kg  650(63.0)        672(65.1)Not recorded  174(16.9)  262(25.4) CD4 cell count    Most recent (n=1032) <=200  373(36.1)  125(12.1) >200  123(11.9) 149(14.4)Not recorded   536(51.9)  758(73.5)  Table 10 above shows that there was an increase in weight as well as CD4 cell counts for patients who  were  initiated  on  ART;  indicating  an  improvement  in  health  after  starting  treatment. However, some of these indicators for clinical improvement were in a few instances misconstrued by  patients  to mean  that  they were  either  cured  from  HIV;  or  they  could  as well  default  on treatment, as the following quote testifies:  

“Many patients have defaulted on treatment after registering great improvement in their health.

Indeed, many HIV positive persons have even resorted to heavy alcohol consumption and this

alcoholism is impacting greatly on their adherence” (Male FGD participant-Padibe Health

Center)

Table 11: Weight and CD4 count averages: Variable At ART Initiation (n=858) Last clinic visit

(n=770) Weight Mean(SD) 52.3(±9.56) 55.8(±9.40) Range 15-98 18-93 CD4 cell count Initiation(n=496) Most recent (n=274) Mean(SD) 158.8(±241.2) 304.7 Range 0-421.7 1-1508

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The average weight at ART initiation was 52.3 kg; while the average CD4 count was 158.8 cells/ml. There was a notable increment in the average body weight of the patients at the last clinic visit to about 60kg; while the average CD4 count at the last clinic visit was almost double the pre-treatment CD4 count. This implies that those who were taking their treatment registered improvement clinically and immunologically. Hence the impact of the NUMAT-supported ART program in northern Uganda is unlikely to be related to questions of drug efficacy, but rather to health system issues and program effectiveness.   Table 12: Showing Functional Status and Prophylaxis state of patients on ART Functional status of patient Freq (%) (n=1032) Working 788(76.4) Ambulatory 91(8.8) Bedridden 14(1.4) Not recorded 139(13.5) Septrin Prophylaxis No 45(4.4) yes 897(86.9) Not recorded 90(8.7) INH prophylaxis for TB, active TB treatment,

On INH prophylaxis for TB 20(1.9) On active TB treatment 51(4.9) Not on treatment at all 781(75.7) Not recorded 180(17.4) Findings in Table 12 above indicate that majority of patients who had started on ART were now working and ambulatory. In addition over 85% of patients on ART were also accessing Septrin for the prevention of opportunistic infections. The remaining 4.4% who were not taking Septrin could probably have been allergic to sulphur-containing medications, or they could have decided not to start on Septrin prophylaxis. However, there was no evidence of utilization of an alternative drug (e.g. Dapsone) for those who may be allergic to Septrin at all the study sites. About 5% of patients were reported as being on active TB treatment as well as ART; while only 2% were said to be on INH Prophylaxis.

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Table 13: HIV/AIDS and Pregnancy Exposure to Nevirapine for PMTCT

Freq (%) (n=718)

No 332(46.2) Yes 38(5.3) Not recorded

348(48.5)

Patient ever pregnant while on ART treatment

No 336(46.8) Yes 33(4.6) Not recorded

349(48.6)

Patient pregnant at last clinic visit No 358(49.9) Yes 14(1.9) Not recorded   

346(48.2) 

Table 13 above shows that about 2% of the women who attended the last ART clinic were pregnant, while about 5% of the women reported being pregnant while on ART. Unfortunately the uptake of PMTCT services was very low, at only 5.3%. This calls for the integration of family planning into HIV Care, ART and PMTCT services as a primary prevention strategy.

Research assistant plays with an HIV positive baby girl at one of the health units.

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According to table 14 below, there were higher incidences of pulmonary tuberculosis, extra pulmonary cryptococcosis, Oesophageal candidiasis and Kaposi’s sarcoma during ART treatment compared to before ART initiation. This could be attributed to immune reconstitution syndrome due to delayed ART initiation; or to poor screening for these conditions before ART initiation by the health workers. There was a significant increase in the number of pulmonary tuberculosis, Cryptococcosis, Oesophageal Candidiasis and Kaposi’s sarcoma cases that were recorded after ART initiation; indicating that most probably patients were initiated on ART at advanced stages of AIDS (WHO Stages III and IV). These spikes in the incidence of severe Opportunistic infections could actually have been due to immune reconstitution syndrome, which usually occurs at CD4 levels less than 100 cells /ml; and is characterized by the emergence of hither-to unrecognized severe opportunistic infections, due to an improving immune system caused by ART. However, the investigators were not able to include WHO Clinical staging in the analysis, since it had been discovered during data collection that majority of the service providers did not have adequate knowledge to do WHO staging.  Table 14: Showing disease conditions of patients on ART at  Initiation, during treatment and at last clinic visit: Stage Defining Condition  Before ART

initiation Number (%)

During ART treatment Number (%)

At last clinic visit Number (%)

Chronic diarrhoea > 1 month 14(1.4) 11(1.1) 3(0.3) Oral candidiasis 31(3.0) 24(2.3) 2(0.2) Oral hairy leukoplakia - 1(0.1) - Pulmonary tuberculosis 40(3.9) 56(5.4) 22(2.1) Severe bacterial infections - 1(0.1) Unexplained prolonged fever > 1 month 1(0.1) 3(0.3) - Weight loss greater of equal to 10% 5(0.5) 5(0.5) 1(0.1) Atypical mycobacteriosis, disseminated or pulmonary

1(0.1) 1(0.1) -

Candidiasis of oesophagus trachea/ bronchi 8(0.8) 10(1.0) 1(0.1) Cryptococcosis, extrapulmonary 1(0.1) 2(0.2) 1(0.1) Crytosporidiosis with diarrhoea > 1 month - - - Cytomegalovirus disease - - - Extrapulmonary tuberculosis 1(0.1) 2(0.2) 1(0.1) Herpes simplex infection, mucocutaneous/ visceral

5(0.5) 1(0.1) -

HIV encephalopathy 2(0.2) - Kaposi’s sarcoma 2(0.2) 8(0.8) 2(0.2) Lymphoma - - - Non-typhoid Salmonella septicaemia - - - Pneumocystis carinii pneumonia - 1(0.1) Progressive, multifocal leukoencephalopathy - - - Toxoplasmosis of the brain - 1(0.1) - Wasting syndrome 7(0.7) 6(0.6) 1(0.1) Disseminated mycosis - 1(0.1) - *Note: Most of the charts did not indicate whether the condition was present or not at a particular stage of treatment  

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6.4 Frequency of refills for ARV drugs The frequency of ARV drug refills during the first month of treatment was largely once a month according to 65% of the respondents (see Pie Chart 3 below);

35.30%

64.70%

Every two weeks 

Once a month

Pie Chart 3: Frequency of ARV refills in the first month of treatment The frequency of ARV refills between the second 2nd and 6th month was largely monthly, according to 14 (82%) of the 17 respondents; while the rest mentioned every two months. When asked how often patients are expected to refill their ARV drugs after completing the first 6 months of ART treatment, 9 (52.9%) key informants mentioned once a month, while 8 (47.1%) mentioned every two weeks. There is need to harmonize the refill intervals across the board for all NUMAT-supported ART sites. Dispensing of ARV drugs and Cotrimoxazole at the 17 Health Units With the exception of one key informant who did not respond, ARV drugs and Cotrimoxazole were reported to be dispensed at the HIV clinic in all the remaining 16 facilities. On average about 2(±1.15) people were reported to be dispensing ARVs in the HIV clinic on a typical clinical day; with a minimum of one and maximum of 3 dispensers.

53

Table 15: ARV s and Cotrimoxazole drug Stock outs at 17 Health Units Class of Drugs Out of Stock Number of Health Units reporting ARV drug stock out

13

Cotrimoxazole

12

Thirteen out of the 17 health units surveyed were reported to have ever run out of antiretroviral drugs. Similarly, 12 out of the 17 health units reported ever having run out of Cotrimoxazole (Septrin) drug stocks (see Table 16 below). This finding highlights the frequency of drug stock-outs in this region. This is definitely not favourable for long-term adherence and retention in ART programs. Table 16: Frequency of Drug Stock-Outs at 17 Health Units in the last 6 Months: Number of Health Units reporting Stock-outs in the last 6 months Class of Drugs Zero times Once

Twice Thrice Four times

ARVs

3 4 3 6 0

Cotrimoxazole

3 3 5 3 1

According to the key informants, 3 of the 17 health units had not experienced ARV drug stock-outs in the 6 months prior to the commencement of the study; while 4 health units experienced ARV drug stock-outs once in the same period. However, 6 of the health units experienced ARV stock outs thrice in a period of only 6 months; while 3 health units suffered ARV stock outs twice in the same period. On average, health facilities that run out of ARV stocks were replenished after 18 days; while others took up to 40 days to get replenishment. Nevertheless, some reported getting the supplies immediately. Similarly, in the 6 months prior to the study, only 3 out of the 17 health units were reported to have been fully stocked with Cotrimoxazole; compared to 3 health units which reported a stock-out once and the 5 health units that experienced Septrin stock-outs twice within the same period. Three of the 17 health units surveyed were reported to have suffered Septrin stock-outs three times within the six months’ period. On average, Cotrimoxazole was reported to be out of stock for a period of about 51.5 days; while in some cases the stock-out could last a maximum of 210 days. Interestingly, all the stock-outs reported were blamed on the National Medical Stores and Ministry of health. All key informants reported that NUMAT delivers drug supplies in time; complete with buffer stocks.

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6.5 Retention Levels in ART Programs At NUMAT-Supported ART Sites From the table 17 below, it is clear that the overall retention in the ART programs in Northern Uganda is low, at only 51.1%. Table 17: Overall Retention rates in the ART programs at 17-NUMAT supported health units in Post-Conflict Northern Uganda. Variable

Number (n=1025) Percentage

Retention Retained 524 51.1 Lost to follow up 501 48.9 Total 1025 100.0 Bar Chart 4: Showing the Overall Retention rates in the ART Programs at 17-NUMAT supported health units in Post-conflict Northern Uganda.

  Bar chart 4 above shows that overall, close to 49% of patients who were initiated on ART at the 17-NUMAT supported sites got lost to follow-up. This includes the defaulters, the dead, relocations and probably the self-referrals; as well as those lost to follow up due to unknown cause. This attrition rate is high and should be a cause for great concern.   

55

Bar Chart 5: Showing Overall retention rates as per Pharmacy Records   

  From Bar Chart 5 above, it is noticeable that the retention rates calculated from the Clinic registers and Pharmacy records do not vary greatly. According to the pharmacy records, on average 48.1% of the patients were lost to follow up in northern Uganda, while 51.9% were retained. Table 18: Retention rates based on pharmacy records alone. Variable Frequency (%)(n=1,030)Retention from Pharmacy records Retained 535(51.9) Lost to follow up 495(48.1) Table 19: Number of patients lost-to-follow-up at given time intervals based on Pharmacy records alone: Period Number lost(n=495) Percentage 3 months 0 0 6 months 262 52.9 12 months 110 22.2 24 months 123 24.8 The above statistics show that by 6 months of ART initiation, 52.9% of the patients had been lost to follow up, implying that loss-to- follow up is highest during the first 6 months of treatment when the patient has not stabilized on treatment. There is only a 20% chance that a patient who has been on ART for at least one year will get lost to follow-up in post-conflict Northern Uganda.  

56

Bar Chart 6: Showing loss-to- follow-up at given time intervals based on pharmacy records

0

52.9%

22.2% 24.8%

0

10

20

30

40

50

60

3 months   6 months   12 months 24 months

According to the bar chart, there was no loss-to follow-up in the first 3-months after ART initiation; but attrition was highest in the first 6 months.

An ART defaulter being interviewed at his home

57

6.6 Predictors of Retention in ART Programs-Bi-variate analysis  In order to assess the equality of survival functions, Log-rank test was used. Proportions, Chi-square and p-values were computed. The results of the log-rank test are shown in table 14 below.

6.6.1 Sex and loss to follow up

Among the male clients, 46% had been lost to follow up as compared to 50.1% among the female clients. Retention on the ART seem not to be associated with the sex of the patient (p value =0.710). 

6.6.2 Age of the patient

Patients aged 14-29 and 30-39 almost had the same proportion of loss to follow up. The lowest was observed among those 40-49 years. However, it did not achieve statistical significance (p value =0.780)

6.6.3 Marital status

The married clients had the highest rates of loss to follow up of 58.2%; while the lowest was among the widowed. Marital status of the clients may be associated with their retention in an ART program at 10% level of significance (p=0.097). This could imply that since the males were noted to have poor health seeking behaviour, they could be influencing their wives to stop ART. This correlates well with a statement which was made by one female FGD participant in Lira: “For couples where one of them is in denial, the person in denial discourages the other from taking treatment or even beats her (if it’s the woman taking ARVs) and tells her to stop going for drugs.”(30 year old female FGD participant, Lira). Another FGD participant had this to say:  “For clients who look healthy, and still have interest in relationships, they give up on treatment so that their spouses don’t get suspicious of their status since this may lead to the end of the relationship.”(34 year old female PLHIV, Pajule).

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Table 20: Bi-variate Analysis for predictors of overall retention Variable #(proportion lost to follow up) Log rank Chi-square

df p-value

Sex Male 144 (46.0) 0.14(1) 0.710 Female 357(50.1) Age group 14-29 76(50.7) 30-39 165(50.8) 1.09(3) 0.780 40-49 91(39.9) 50+ 51(46.8) Marital status Married 202(58.2) Widow/Widowed 121(48.6) 4.68(2) 0.097* Other 72(52.6) Change of ART Not changed 405(55.0) 22.33(1) <0.001*** Changed 96(33.3) Distance to facility <=5km 89(48.9) 6-10km 44(38.9) 4.02(3) 0.259 11-15km 28(44.4) 16+km 51(51.5) Weight of patient at initiation <=45kg 118(56.7) 46+kg 297(45.8) 4.17(1) 0.041** CD4 cell count at initiation <=200 189(51.4) >200 64(52.0) 0.97(1) 0.325

6.6.4 Change of ART

55% of the patients who had not changed ART combination were lost to follow up as compared to 33.3% among those who had changed ART combination. The retention on ART was significantly associated with change of ART combination(p value <0.001).This could mean that probably those whose ART combination was not changed lost hope and stopped treatment, perhaps thinking they were on an inferior combination

6.6.5 Body Weight of the patient at ART initiation

The highest rate of loss to follow up was observed among patients who had weight <=45kg at the initiation of ART. The weight at initiation of ART may be associated with retention on ART; and this showed statistical significance (p value =0.041). The implication may be that those who started on ART when they were wasted faced a lot of stigma; or could have had more severe immune system damage and hence could not recover. Indeed, according to the table above, loss to follow up was higher among those who started on ART at CD4 count less than 200 cells. This shows the need for initiating ART when the immune system is not yet irreparably damaged.

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6.7 Kaplan-Meier Survival curves at different time intervals Retention rates on ART in northern Uganda were also estimated using the Kaplan-Meier survival functions at 3months, 6 months, 12 and 24 months. The results are shown in the Figure 1 below.

0.00

0.25

0.50

0.75

1.00

0 500 1000 1500 2000 2500analysis time

Retention_Pharm_grp = <=3months Retention_Pharm_grp = 6 monthsRetention_Pharm_grp = 12 months Retention_Pharm_grp = 24 months

Kaplan-Meier survival estimates, by Retention_Pharm_grp

The graph above shows that in the first 3 months there were no clients that were lost to follow up. Loss to follow up was instead witnessed at 6 and 12 months and 24 months. This could clearly be explained by the steepness of the two survival curves. This is further elucidated according to the figures in the table below. Table 21: Number of patients lost at given time intervals based on Pharmacy records Period Number lost(n=495) Percentage 3 months   0  0 6 months   262  52.9 12 months  110 22.224 months  123  24.8  

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Graph 2: Single Kaplan –Meier survival functions

0.2

5.5

.75

10

.25

.5.7

51

0 1000 2000 3000 0 1000 2000 3000

<=3months 6 months

12 months 24 months

95% CI Survivor function

surv

ival

pro

bailit

y

time

Graphs by RECODE of Retention_pharm

Kaplan-Meier survival estimates, by Retention_Pharm_grp

6.7 Survival analysis for predictors of overall retention

A proportional hazards model was also fitted assuming a Weibull distribution for the survival time. Findings were as shown in table 16 below:

6.7.1 Interpretation of the proportional hazards model

Sex of the patient The hazard of loss to follow up was reduced by 8% among the females as compared to males. This implies that females were at reduced risk of being lost to follow up as compared to males. This means that men stand a higher risk of loss-to-follow-up as compared to females, although it did not achieve statistical significance (p value =0.399).

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Table 22: Proportional Hazards Modeling

Variable   Hazard  ratio 95% CI p‐value Sex    *Male   1.00     Female   0.92  0.76‐1.12  0.399 Marital status       *Other   1.00 Married   1.32  1.01‐1.73  0.042** Widow/widowed  1.12  0.84‐1.50 0.446 Change of ART       *No   1.00     Yes  1.55  1.24‐1.95 <0.001** Distance        *<=5km  1.00 6‐10km  1.05  0.73‐1.51  0.779 11‐15km  1.65  1.07‐2.53 0.023** 16+km  1.06  0.75‐1.50  0.759 Weight  at  ART initiation  

     

*<=45kg  1.00     46+kg  1.28  1.03‐1.59 0.024** CD4  count  at  ART initiation  

     

*<=200  1.00     >200  1.24  0.93‐1.65 0.140 Age group    *<=29  1.00     30‐39  1.02  0.78‐1.34 0.864 40‐49  0.88  0.65‐1.19  0.415 50+  0.80  0.56‐1.14 0.224 *reference category; **significant at 5%; ***significant at 10% Marital status  Patients who were married had a 1.32-fold increased hazard of being lost to follow up as compared to those who were either single or never married. The implication here is that in this area, being married seems to be associated with an increased risk of lost- to –follow-up ; and this achieved statistical significance (p value =0.042). Similarly, patients who reported as being widowed also had a 1.12-fold increased hazard of being lost to follow up as compared to the other categories of marital status (single and never married). However, these findings did not show any statistical significance (p value =0.446).     

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Change of ART  Patients whose ART combination(s) were changed during the course of antiretroviral therapy had approximately a 1.6-fold increased risk of getting lost to follow up as compared to those who had not changed ART combinations. Change of ART combination in the post conflict areas in northern Uganda therefore seemed to be very strongly associated with increased risk of loss to follow up; and this achieved statistical significance (p value <0.001).  Distance to the HIV clinic  As the distance to the HIV clinic increases, the risk of loss to follow up also increases. In this study patients residing a distance of 11-15km away from the clinic had 1.6-fold increased hazard of being lost to follow up as compared to those who were residing less than 5km away from the clinic; and this was statistically significant (p value =0.023).  Weight at ART initiation  Patients who weighed 46kg or more at the time of ART initiation were found to have a 1.28-fold increased hazard of being lost to follow up as compared to those who were 45kg and less. This could probably mean that former regarded themselves as healthier and hence would not need to stay on long-term treatment. Patients who had not lost a lot of weight were at a higher risk of getting lost to follow up as compared to those who had lost weight massively; and this achieved statistical significance-showing a strong association (p value =0.024). Table 23: Odds ratios for predictors of overall retention in ART programs  Variable   Number   Odds ratio  95%CI  p‐value Sex          *Male   314  1.00     Female   718 1.18 0.90‐1.54 0.223 Marital status   *Other   137  1.00     Married   420  0.85  0.58‐1.25  0.417 Widow/widowed  210  1.26  0.81‐1.94  0.304 Change of ART         *No   741 1.00  Yes  291 0.41 0.31‐0.54 <0.001** Distance    *<=5km  182  1.00     6‐10km  114  0.67  0.41‐1.07  0.095*** 11‐15km  64  0.84  0.47‐1.49  0.542 16+km  100 1.11 0.68‐1.81 0.676 weight at ART initiation   *<=45kg  208 1.00  46+kg  650  1.55  1.13‐2.13  0.006** CD4 count at ART  initiation          *<=200  373  1.00     >200  123 1.03 0.68‐1.55 0.897 Age group    *<=29  151 1.00  30‐39  328  1.00  0.68‐1.47  0.983 40‐49  230  0.65  0.43‐0.98  0.040** 50+  110  0.86  0.52‐1.40  0.538 

*reference category; **significant at 5%;***significant at 10%

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6.8 Health Systems at 17-NUMAT supported ART Sites in Northern Uganda Table 24: ART Clinic Managers A total of 17 ART Clinic Managers served as key informants in this study and provided valuable information regarding the systems in place to provide ART. Their categories by cadre are as shown in Table 18 below:

Staff cadre

Number interviewed

Senior Medical Officer 2 Senior Clinical Officer 2 Clinical Officer 7 Orthopeadic Officer 2 Nursing Officer 4 Total 17

Clinical Officers comprised 53% of the ART Clinic managers; while Medical doctors made up only 11.7% of the ART clinic managers among the 17 NUMAT-supported ART sites. Clinical Officers and Nurses made up 65% of the ART clinic managers; implying that the majority of ART beneficiaries in the region are initiated, monitored and followed-up by non-Physician health workers.

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A Clinical Officer (seated) prescribing ART at Amolatar Health Center IV.

6.8.1 Human Resources for HIV/AIDS Care Provision

According to the key informants, only 4 of the 17 health facilities had a medical doctor available on a typical HIV clinic day to provide direct HIV care and treatment. This implies that only 24% of the health facilities surveyed had technical support from a medical doctor. One of the facilities with this staff cadre was a regional referral hospital and the other a district hospital, In all the 4 instances, only 1 medical officer was reported to be available at each of the facilities. The average number of clinical officers available on a typical HIV clinic day was 2; with a range of 1-4. All the 17 ART clinic managers interviewed reported availability of at least one clinical officer on a typical HIV clinic day. Other cadres of staff mentioned included laboratory technicians. It is important to note that none of the health facilities surveyed had a nutritionist on a typical HIV clinic day. Further details are summarized in Table 19 below. Table 25: Cadre of staff that provides direct HIV care and treatment on a typical HIV clinic day. Staff cadre # Available on a

typical HIV clinic

day

Not available Mean # Range

Medical doctor 4 13 1 -

Clinical officer 17 0 2 1-4

Nurse/midwife (enrolled and

registered)

14 3 2 0-5

Nursing Assistant 10 7 1 0-3

Nutritionist 0 17 0 0

Lay ART support workers 13 4 2 0-6

Social workers 1 16 1 0-1

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From the above data, it is worthwhile to note that only one health facility had a social worker among their staff (Regional referral hospital). The ART Clinic managers were further interviewed on the average number of hours medical doctors spend at the HIV clinic during a typical HIV clinic day. They reported that doctors spend about 3- 8 hours in the clinic during a typical HIV clinic day; with a mean of 5.7 hours, (SD+_2.6 hours). A similar question was posed about the clinical officers; and the reported mean was7.9 hours (SD 2.4 hours); with a range of range 2-10 hours. Information was also collected on the number of staff designated to provide the key care- related services on a typical HIV clinic day. The obtained averages are summarized in Table 20, below (n=17).

Human Resources for HIV care: Nursing Officer at Padibe Health Center (Right)

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Table 26: Staff available to provide key care-related services on a typical HIV Clinic day Care-related Service Mean number of staff available on

a typical HIV clinic day Range

Registration 1 0-3 Triage 1 0-10 Adherence counseling 2 1-5 Clinical services 2 1-4 ART prescription 1 1-2 Phlebotomy 1 0-13 ART dispenser 1 0-2 Follow-up on missed appointments and defaulting

1 0-7

Referral services 2 0-13 Data management 2 0-13 The above table shows evidence of under-staffing for most of the critical components of the ART care pathway, particularly data management and tracking of patients lost- to- follow-up.

6.8.2 Supervision of health workers:

The ART clinic managers reported that supervisors from outside their facilities observe their clinical practices at the HIV clinic 3 times, within a period of 6 months; with a range of 1-5 times. When asked whether the clinicians in the HIV clinic had formal mentors experienced in ART and respond to questions, review clinical cases, provide feedback and support case management, 11 (64.7%) responded in affirmative while 6 (35.3%) said no. Clinic managers were also asked whether patient case conference reviews were done at the HIV clinic and 9 (52.9%) responded in affirmative while 8 (47.1%) said no.

6.8.3 Availability of HIV care and Prevention services

TB prophylaxis, nutritional supplementation and palliative care were the least available types of all HIV-related care services at the surveyed health facilities (see Table 21, below). One of the health units reported inability to conduct TB diagnostic testing.

6.8.4 Provision of adherence-related services

Clinic managers were further asked whether a series of adherence-related services had ever been provided by their respective HIV clinics. All the 17 the managers reported providing ART adherence counseling by the health care staff. The adherence counseling services are said to have been initiated as early as 2004 in some facilities; and in 2008 for the others. ART adherence counseling was available at 13 of the 17 health facilities and the service had been in place for an average of duration of 1.7 years. However, information from the FGD sessions with ART Clinic managers showed that the majority of health workers expressed desire to be trained in counseling skills.

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The delay to initiate adherence counseling at some sites, combined with the lack of adherence at 4 of the 17 sites, could be a factor among the many that have affected the retention rates in this region. Prevention with positives services was also available at 16(94.1%) of the 17 facilities and the service had been in place for an average duration of about 2.5 years. Referral community services were the least available and where available, the services had been in place for an average of 2.5 years (see Table 18). It is important to note that none of the adherence related services were reported to have been stopped after initiation. Table 27: Availability of HIV care and Prevention services Type of Service Available(n=17 Not available

HIV counseling 17 (100) 0

Diagnostic HIV testing 17 (100) 0

Adult ART 17 (100) 0

Paediatric ART 16 (94.1) 1(5.9)

Paediatric HIV care no ART 17 (100) 0

OI prophylaxis 17 (100) 0

Management of OI 17 (100) 0

Cotrimoxazole prophylaxis 17 (100) 0

TB testing 16 (94.1) 1 (5.9)

TB prophylaxis (INH) 1 (5.9) 16 (94.1)

TB treatment 17 (100) 0

Laboratory testing 17 (100) 0

Treatment of STIs 17 (100) 0

PMTCT services 17 (100) 0

Palliative care 10 (58.8) 7 (41.2)

Nutritional supplementation 5 (29.4) 12 (70.6)

Nutritional education/advice 17 (100) 0

Family planning services 17 (100) 0

Prevention with positives 16 (94.1) 1 (5.9)

Post exposure prophylaxis 17 (100) 0

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Table 28: Availability of adherence related services Type of service Available Not

available Year range for service initiation (mean, median # years since initiation)

Cessation of service

ART adherence counseling by health care staff

17 (100) 0 2004- 2008 (1.7, ) Still operational

ART adherence counseling by lay workers

13 (76.5) 4 (23.5) 2004-2008 (1.7, 1) Still operational

Prevention with positives

15 (88.2) 2 (11.7) 2005-2008 (2.5, 3) Still operational

PLHA support groups

13 (76.5) 4 (23.5) +

Outreach Home- Based care

11 (64.7) 6 (35.3) 2005-2008 (2.3, 2.5) Still operational

Referral community services

8 (47.1) 9 (52.9) 2004-2008 (2.5,2.5) Still operational

+ Dates were not available

6.8.5 Frequency of visits, appointments and patient loads

Information elicited in this survey also indicated that the average number of adult patient visits to the HIV clinics in the previous month prior to the survey was 385; with a range of 76-1000 visits. It is however important to note that the mean number of visits was higher for district hospitals (525 visits) as compared to the other levels of service delivery (400 for the referral hospital, and 295 for health center IVs). A similar enquiry was made about paediatric visits made at the HIV clinic during the past month and the mean number of visits reported was 38, with a range of 13-104 visits. It is however important to note that the number of paediatric HIV visits were higher for the referral hospital, at 100 visits per month; followed by 51 visits per month for district hospitals and 22 visits per month for health center IVs). The average number of adult HIV patients that were reported to be seen by each clinic manager on a typical clinic day was 89 patients. The numbers were however higher for district hospitals as compared to other levels of service delivery (100 for the regional referral hospital; 126 patients per clinician per day for district hospitals; and 70 patients per clinician per day for the health center IVs). On the whole, these figures, though self-reported, seem to be rather on the high side: indicating a heavy client load that would definitely lead to long waiting times. Interestingly, 16(94.1%) of the 17 health facilities were not into the practice of limiting the number of patients seen on a typical HIV clinic day; and the average number of clients that may be seen on a typical clinic day was reported to be 94. Only 5 of the 17 ART clinic managers confirmed that they occasionally turn away patients who are seeking care on a typical HIV clinic day, while 12 (70.6%) said they never turn away patients.

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6.8.6 Proportion of visits scheduled by appointment

The proportion of adult visits scheduled by appointment on a typical HIV clinic day was higher for the regional referral hospital as compared to the lower levels of service delivery, Table 29: Proportion of Visits scheduled by Appointment Type of facility Mean proportion of visits scheduled by appointment (%)

Referral hospital 75

District based hospital 70

Primary health center IV 43.4

From Table 19 above, it is evident that the primary health center IV management teams need to be assisted to establish functional and effective appointment systems for ART patients in order to regulate client loads, reduce on waiting times, as well as prevent burn out and stress of the already constrained health workforce at that level. 6.9 Tracking Systems and Losses to follow-up According to the key informants, the commonest reason why patients on ART got lost to follow-up is because they had moved from the camps back to their original homes in the villages (16 out of 17 respondents); followed closely by death (15 out of 17 respondents) and lack of funds for transport to the health units (10 out of 17 respondents). And whereas 4 of the 17 key respondents said that sometimes the reasons why patients get lost to follow-up are unknown; 7 of the respondents thought that the distance to the health facility was a key reason why some patients defaulted on ART treatment (see table 14 above). From table 18 below, it is also evident that only 5 out of the 17 health units had adherence support workers to follow –up patients that may have missed appointments. Similarly, only 5 out of 17 health units had home-care workers that trace ART patients who are lost-to-follow up. Only 2 of the 17 key informants reported that their health units conduct home visits by trained health care workers. All these are signs of a weak community follow-up support structure around the patients accessing ART from the NUMAT-supported health units. However, 11 out of the 17 key informants said their health units had a system for tracking patients who transferred out to other ART service providers.

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Table 30: Tracking Systems for Patients on ART at 17-NUMAT supported health units. Variable Number of health Units

reporting(n=17) Tracking system for making individual HIV client appointment 15 System for identifying ART patients who have missed an appointment

No System 1 Pharmacy reports 4 Appointment diary 10 Other Methods for tracing clients on ART who are lost 9 Methods Telephone call 2 House visit by adherence Support worker 5 House visit by health care workers 2 House visit by home-based care workers 5 Other, specify (CBO) 1 Retention rates 6 Reasons why patients become lost to follow-up Death 15 Move 16 Patient decision 8 Lack of funds 10 Unknown 4 Other, specify (distance) 7 Having a system for tracking patient transfers to another facility for ART care

11

General OPD register with HIV/AIDS and non HIV/AIDS clients 1 Specific register for HIV/AIDS clients 8 Specific register only for ART clients 2 Individual client chart/medical record 1 No record kept 1

6.9.1 Tracking of ART eligible patients not yet started on treatment

The ART Clinic managers were also asked whether their clinics kept track of patients who they found eligible for treatment but had not yet started on ART and 11 (68.7%) of the 16 who responded to this question answered in affirmative ,while 5 said no.

6.9.2 Waiting Time for ART eligibility assessment

ART Clinic managers reported that patients had to wait to determine eligibility for ART; and the reported mean time was approximately 22 days, with a range of 7-56 days.

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6.9.3 Priority reasons for waiting for eligibility assessment

The top three commonly mentioned reasons as to why patients ART eligibility assessment involved components of waiting time were: CD4 count not available -which was endorsed by 13 of the 16 respondents. This was followed by patient having other Opportunistic Infections- which was mentioned by 10 of the 16 respondents interviewed; and patient has TB and patient decision- both of which were mentioned by 7 of the 16 respondents.

6.9.4 Waiting time for starting ARV drugs

On average, patients who were found eligible for ART initiation reportedly had to wait for an average of 20 days before they started on ARV drugs; with a range of 1-30 days. The top three reasons mentioned to justify the waiting time included: 14 of the 16 clinic managers interviewed mentioned ‘patient needs more adherence preparation sessions’; 13 mentioned ‘patients may have other Opportunistic Infections’; 11 mentioned that the ‘patient may have TB’; while 10 mentioned ‘patient decision to wait.’

6.9.5 Patients waiting to start ART at time of the survey

Information on those eligible for ART patients, who were waiting to start ART at the time of this survey was available for 14 facilities; and their average number was reported to be 21 patients, with a range of 3-58 patients. The commonly used criteria for eligibility assessment for ART were CD4 cell count, and WHO clinical stage according to 16 of the 17 ART clinic managers. In addition 9 mentioned that the criteria was based on national guidelines, while 6 mentioned that it was based on WHO guidelines and 1 mentioned other international guidelines.

Patients waiting to be served at Padibe Health Center IV, Kitgum.

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6.10 ARV treatment tools used at clinics On the domain of ARV treatment tools used at the clinics 14 of the 16 clinic managers who responded to the question mentioned SOPS, 15 mentioned wall posters, 13 elicited desk aides and 10 elicited check lists. 6.11 ART Combination Regimens AZT, NVP and EFV based were the commonly mentioned first line regimens at the surveyed health facilities. Table 31 below shows the average number of patients who were on a second line regimen was 1. A total of 8 health facilities were reported to be having patients on second line ART regimens. Table 31: Type of ART regimens available at the facilities

First line regimens

Type of regimen Number of facilities reporting regimen type

AZT based regimens 16

D4T based regimens 15

NVP based regimens 16

EFV based regimens 16

Tenofovir based regimens 6

3TC 1

Second line ART

AZT based regimens 6

D4T based regimens 1

NVP based regimens 1

6.12 Laboratory Services Capacity: From table 32 below, it is notable that none of the 17- NUMAT supported sites in this survey has a CD4 Counting Machine on site. This perhaps explains the glaring delays in initiating patients on ART. It is well known now, that delays in ART initiation have poor prognostic outcomes; particularly due to severely damaged immune systems; as well as immune reconstitution syndrome, which in our setting is difficult to diagnose, let alone manage. Although 15 of the 17 sites were reported to have a specimen referral system in place; findings from the Focus Group discussions with the PLHIV at various sites indicated that accessing CD4 counting services still poses a significant challenge.

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Table 32 also shows that it is only 15 out of the 17 facilities that were in position to carry out hemoglobin tests; while only one site could run liver and renal function tests (the Regional referral hospital). This is indicates the need to further strengthen the laboratory capacities at various kevels for ART monitoring purposes. Table 22: Laboratory Services Capacity at 17-NUMAT supported ART sites . Variable No. of Facilities(n=17) ART laboratory tests performed at facility 15 Laboratory tests for ART performed at the facilities CD4 count 0 Total lymphocyte count 5 Viral load 0 Liver function 1 Renal function tests 1 White blood cell count and differential 8 Hemoglobin/Haematocrit 15 Other tests 5 Places where tests are performed other than facility Regional Referral hospital 7 Other 9 Access to Lab services not offered at facility Patient must go to laboratory 1 Specimen referral system in place 15 pre-treatment ART tests done CD4 cell count 14 Viral load 1 Total Lymphocyte 8Liver function  2Renal function  1WBC differential 10 Haemoglobin/Haematocrit 15 Table 33: Tests done to assess the Clinical progress of patients after ART initiation: Variable Number of Health Units Performing test Laboratory Test Not

performed

Every 3 months

Every 6 months

Every 12 months

Other Tests*

CD4 cell count 2 - 12 1 - Viral load 10 - - - - Total Lymphocyte 7 - 4 - 1 Liver function 10 - - - 2Renal function 11 - - - 1 WBC differential 6 - 3 1 3 Haemoglobin/Haematocrit 2 2 1 - 10 *Other tests include HIV rapid test, pregnancy test, Hb, and TB. From Table 33 above, it is evident that only 12 out of the 17 health units reported conducting CD4 cell counts tests after every 6 months to assess the clinical progress of patients who had started on ART. This may point to a need to strengthen and streamline the laboratory monitoring and follow-up of patients who start on ART.

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6.13 Current sources of support at the 17 health facilities For the 17 facilities surveyed, ART services were initiated between 2004 -2007. All the facilities reported receiving government support. The forms of support offered included Drug supplies, human resource, and infrastructure and associated supplies. External support was the second commonest source of support. Table 34: Current Sources of support for the ART Program Source of support Support received No support

received Top 5 Kind of support commonly mentioned

Government 17 (100) 0 ARVs, OI drugs, laboratory equipment, infrastructure, ART related training, Technical assistance , pharmacy

External support 9 (52.9) 8(47.1) ARVs, OI drugs, Technical assistance, ART training and medical supplies

Global fund 4 (23.5) 13 (76.5) ARVS, ART related training, technical assistance, pharmacy, medical supplies, OI drugs.

Research/University 2 (11.8) 15 (88.2) ARV drugs, OI drugs , infrastructure, laboratory equipment, pharmacy and medical supplies

6.13.1 Sources of support ever received

According to the key informants, the other organizations that have ever provided support to their health facilities included; AIM, NUMAT, BAYLOR, TASO, JRCR, PSI, AVSI and GUTH.

AVSI Support (above): Partnerships can help in strengthening HIV/AIDS Care provision

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6.14 Factors affecting Retention in ART Programs in post-conflict Northern Uganda According to the responses gathered during the focus group discussions and in-depth interviews, the following were the key factors affecting retention of HIV-positive persons in ART programs in post-conflict northern Uganda:

6.14.1 Health systems factors

Drug stock outs at the health units stood out clearly as a key barrier to retention and adherence of many PLHIV in Northern Uganda, particularly in situations where MOH/NMS are responsible for the supply chain. Although the ART Clinic Managers reported that ARV drug stock supplies had improved since NUMAT came onto the scene; but there were still frequent ARV drug stock-outs for supplies from Ministry of Health/National Medical Stores. Also, some health units were reported to be receiving both ARV s and Septrin from NUMAT, while others received only ARVs. There is need for harmonization and standardization. One FGD participant took it a step further,”NUMAT should provide Septrin, fluconazole, I.V fluids and other essentials drugs as well. When we refer AIDS patients to the district hospitals, they find a worse situation.” (Male clinician, Acholi sub-region). Another Key Informant had this to say: “As we handle these clients, we are not only handling the HIV part of it, having ARVs and Septrin is not enough, NUMAT has to expand the support.”(Female Nurse, Lango sub-region).

• The logistics management system was said to be difficult because drugs from different providers have different stock cards. There is need to harmonize these stock cards.

• High patient loads at the health facilities have caused long waiting times. This partly contributes to the high defaulter rates at some facilities. As one health worker put, “The numbers of HIV clinic days are still limited, at my health unit: 2 days per week. Some clients miss these days and may instead come on non ART days and find no staff since we rotate in other departments, such persons miss their drugs.”(Male Clinician- Lango sub-region)

• In addition, it was found that there were a significant number of patients who got lost to follow up before initiating ART because of the long process of ART initiation, coupled with the distance and cost of transport to the health units.

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Lost –to- follow-up before ART initiation; but was on Septrin (pictured above right).

• It was also found that the linkage between the Antenatal clinics/ Maternity for PMTCT, and the ART Clinics was still very weak. This made it difficult to identify which mothers would require Comprehensive HIV/AIDS Care, leading to delays in ART initiation.

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IEC by NUMAT: There is need to strengthen community awareness of PMTCT.

FGD session with Female PLHIV with breastfeeding babies pictured below ( Orum Health Center IV)

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6.14.2 Community-related factors

• Stigma is still a very serious impediment to ART adherence and long term retention;

particularly among school teachers, and the middle-income earners (civil servants and businessmen). Stigma is still high at individual, household and community levels.

Above: A 9 year old HIV positive boy that was forced to abandon school due to stigma and discrimination (Pajule- Pader district)

“Stigma is still very high especially among the well-to-do business men and civil servants. They even do not want the NSAs to read their names out. Some of them send other people to pick their drugs for them due to stigma. Sometimes they prefer being seen over the weekend and privately.”(35 year old male clinician, Lango sub-region.) Another ART Clinic Manager had this to say: “My problem, are teachers! We treat children whom they teach, and the parents whose children they teach, it makes them lose respect in the community.” The same sentiment was re-echoed by a female nurse who said, “Teachers do not want to mix up with other HIV patients. I have many who come to me privately. They want to be attended to quickly. We put their drugs in something and dispense from another room.” Another health worker said, “It’s even worse with health workers who are working at the same health unit. They prefer to go to health facilities far away to access care. Those who are in denial, we leave them; those who accept the advice, we support them in a confidential way when they come with their files”.

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One male clinical officer said, “Men normally tend to send their wives to pick their ARV refills for them; you will never see them at the clinic.” The following quotes from FGD participants at various study sites further illustrate the levels of stigma at community level: “There is a lot of stigma in the community, I am referred to as a ‘living corpse’, people at home do not want to associate with me, even my own mother, this discourages me from taking drugs and I feel like dying.” (38 year old male PLHIV, Padibe). “The community members are always happy whenever the drugs are out of stock, because they wish all of us dead.”(Female PLHIV, Amolatar). “The community members say that those on ARVs do not die fast, they wish they should be given drugs that kill them to prevent infection.”(29 year old female PLHIV, Orum). “People say that those with ‘silimu’ are infectious so we should not share chairs, shake hands and share food with the healthy.”(32 year old female PLHIV, Atiak). This is a clear indication that communities in the region do not yet have even the basics on HIV/AIDS, including modes of transmission. There is urgent need to increase HIV/AIDS awareness among the communities.

• Mass- Media influence: Incidences of radio stations advertising herbalists and traditional healers who have a cure for HIV/AIDS were reported during the FGD sessions. Newspaper opinion pages and radio programs were also cited as responsible for spreading negative and discriminatory attitudes.

• Disclosure: Parents and families have also not been supported to disclose to HIV infected children about their serostatus. Adolescents were reported to be frequently asking why they are on long-term treatment.

An HIV positive adolescent(14 years) accessing ART at Lira Hospital(pictured above): What are the challenges and coping mechanisms?

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6.14.3 Geographical Factors

• Distance from the health facilities and lack of finances to meet transport costs is a significant barrier to retention in ART programs. Most patients complained about the distance to the health units; and the majority was reported to be missing their appointments. When patients are doing well, they avoid coming to the clinic on the appointment days.

Aswa bridge (above left); Population in transit- IDP camp set on fire (above right)

Distance from the health facilities and lack of finances to meet transport costs is a significant barrier to retention in ART programs; particularly for those who are leaving the camps for their villages. One health worker commented thus: ‘Most patients complain about the distance to the health units.

Majority do not keep their appointments.’

This was further re-affirmed by the FGD participants as being critical to ART access, as quoted below: “Distance from home to the clinic is so long, when I am down and with no one to send to collect for me drugs, I miss and only go for it when I get well.”(Male PLHIV, Alebtong). ‘We also have a health center, that is Ober Health Center; the Referral hospital – HIV clinic is always congested and far; so I think they should decentralize ART services or ARVs to Ober health center which is nearer to us. This would also help us (PHAs), in accessing our drugs.’ (Defaulter, Lango sub region).

However, one FGD participant had this to say: ‘With this booming business in Southern Sudan,

many patients travel to Juba and never return’ (Female Nursing Assistant, Acholi sub-region).

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6.14.4 Human Resources Factors

• There is still a very acute shortage of trained health workers in this area, to offer treatment

care and support to PLHIV. The patient provider ratio is still unacceptably high.

• Poor counseling at the initial stage of HIV diagnosis. A number of defaulters who were

traced in their communities said they were not aware that ART was life-long treatment. This

was one of the reasons they gave for getting lost-to follow-up.

• Most health workers working in the HIV/AIDS Clinics reported that they were not trained in

counseling skills; yet patients who presented to them came with more than just medical

needs. Health workers reported experiencing very serious challenges with discordant couple

counseling, yet the numbers of discordant couples were reportedly on the rise.

• Provider attitudes: Many health workers were reported to manifest negative attitudes

towards people living with HIV/AIDS, particularly those who do not work in the HIV

Clinics.

• Health worker motivation and remuneration was reported to be a big challenge by clinic

managers. They were said to be too few, and are transferred frequently.

• The Network Support Agents (NSA) that were trained are too few (2 per Sub County); they

were said to be very useful in peer counseling, and they need to be well motivated.

6.14.5 Socio-economic Factors

Food shortage and food insecurity at household level has been reported to impact greatly on the

adherence and long term retention of PLHIV in ART programs. A significant number of FGD

participants thought this was a critical factor to long term retention. Those who have just transited back to

the villages have not yet grown enough food to prevent hunger and face particularly greater risks.

“I lack enough fluids to drink and food to eat and yet with ‘ARBs’, when the stomach is empty, you feel really weak.”(30 year old female PLHIV, Alebtong).

“Lack of enough food to eat forces some people to give up treatment as drugs make one weak when they don’t eat enough food.”(43-year old male FGD participant, Dokolo).

• Many PLHIV tend to transfer out to other service providers on self-referral basis in order to

benefit from other incentives such as food support; school fees or mosquito nets among

others. This is further confirmed by the following quote:

“Material support from other agencies: For example TASO gives food, school fees and eventually takes over the patient without our knowledge”(Key informant).

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Alcoholism is now a serious social problem.

6.14.6 Drug-related Factors

• Patients who get severe side effects discourage the rest of the community and they drop out

of the ART program.

• Some patients reported that often times the pills to swallow at one go were too many for one

to adhere to on a daily basis and hence some of them took a ‘holiday’; often with

consequences.

• There are incidences of frequent ARVs and essential drugs stock outs from MOH at various

units

6.14.7 Patient-related Factors

• Non-disclosure and lack of home-based support, continues to be a critical barrier to

retention and adherence in ART programs.

• Many patients were found to have defaulted on treatment after registering great

improvement in their health. Indeed, many HIV positive persons were reported to have

resorted to heavy alcohol consumption and this alcoholism is impacting greatly on their

adherence.

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Male PLHIV (above left) who defaulted on ART after improving in health- Lira town.

Sexual and reproductive health choices have also been found to play a role in disclosure and

adherence to ART, as evidenced by this quote:

• “For clients who look healthy, and still have interest in relationships, they give up on

treatment so that their spouses don’t get suspicious of their status since this may lead to the

end of the relationship.”(34 year old female PLHIV, Pajule

• Incarceration: Prisoners were reported to have become so prone to loss-to-follow up, and

these were mainly the defilement cases. These cases were said to be common in this region

because some parents use it as an opportunity to generate income.

• Occupation: According to findings from the FGD sessions, soldiers and police officers

were found to easily get lost to follow-up because they tended to be transferred without

notice to the health units. The same scenario was reported of other civil servants in the

region. According to one FGD participant, ‘Soldiers are lost to follow-up because they

transfer them without notifying anybody. They are among the main culprits among those lost

to follow up in Acholi sub region’-(Male Clinician, Gulu).

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• Gender: Opinions gathered during the focus group discussions indicated that generally,

there is poor health-seeking behavior among men living with HIV/AIDS in northern

Uganda.

Male PLHIV still in care at Orum Health Center: Men have poor health-seeking

behavior.

• Pregnancy rates among women who have improved on ART were reported to be ‘very

high’. These women were said to be defaulting because they fear to go to the health units

and face harassment by health workers. To make matters worse, most HIV positive mothers

in this setting were said to have no infant feeding options apart from breastfeeding; and they

end up infecting their children due to continued breastfeeding.

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2-year old HIV positive girl born to a female PLHIV (above left)

6.14.8 Cultural and Religious Factors

Myths and misconceptions about antiretroviral therapy still abound in this setting, particularly to do with ARV side effects. Indeed this perception could be captured from the following quote: “The side effects of these drugs have made some clients to give up treatment.”(40-year old male FGD participant Dokolo.) “I was told that those drugs have terrible side effects, I had to leave them”, said one defaulter. “Some people say they are healed, after taking drugs for sometime and they see that they are looking healthy.”(36 year old female FGD participant, Alebtong).

There are also strong beliefs about traditional healers providing a cure for HIV/AIDS. There are

incidences of traditional healers who claim they can cure HIV and these have ended up fleecing the

unsuspecting public.

One male FGD participant narrated to the group how he had been advised by one traditional healer:

‘ He told me to catch a lizard (‘Oluguk’), kill it and drink its blood; then boil it and take the soup,

after which I would be healed of HIV. I got the lizard, killed it, and drank its blood; I didn’t eat its

flesh. But when I went back to test I found I was still positive.’

“I have heard of a magic doctor over the radio in Lira town around Atat market that cures HIV/AIDS”- (39 year old male FGD participant, Pajule).

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‘Some man went to Kitgum and claimed that he cures HIV/AIDS using drops of water. People

stopped taking their ARVs. By the time we realized it was too late. It took the DHO’s

intervention.’(40 year old male Clinician).

Religious leaders (Pastors) who preach the gospel of faith-healing also still abound and have been

reported to have convinced many patients to discontinue ART.

6.15.0 Defaulter Tracing • More than 52 % of the defaulters who were tracked were found to have died; however, the local culture does not permit one to ask what the probable cause of death was. • Over 30 % of defaulters could not be traced at all; since they had given either different names or different home addresses: hence they were classified as ‘lost to follow-up, cause unknown’. • Many patients were found to have got lost before ART initiation, but were on Septrin; probably due to the tedious process of ART initiation, heavy client loads, staff shortages and the costs involved in traveling to the health units.

Table 35: Defaulter Tracing in Northern Uganda. S/No. Description of the

Defaulter Reasons given for defaulting Remarks

1. Female, 36 years, Oreny Village; Bata Sub county, Dokolo District. Started ART: 19/11/2005 Last Refill date: 04/ 09/ 2006

Lost to follow-up: cause unknown. Probably re-located

2. Male, 34 years,Alii,Alal, Dog Ayira Functional Status: Very ill; Bedridden Started ART: 17/2/ 2008 Last Refill : 21/ 07/2008 Distance from facility: 10km Alebtong

Very ill; lack of transport; distance from facility, without family support.

Lack of transport to access drugs

3. Female, 37 years; Baro Otolo

Died Died

4. Female, Adult; Pajule Died Died 5. Female, 41; Alebtong Died Died 6. Female; 42years;

Amolatar Distance from the facility very long Lack of transport

7. Oyela, Male Adult, Lost; gave wrong address Unknown cause

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S/No. Description of the Defaulter

Reasons given for defaulting Remarks

Oyam Could not be traced 8. Amolo-Female; 29

years; Lira.

Side effects of the drugs: Got Severe skin rash and discontinued treatment

Drug-related side effects

9. Awany – Anyeke; Adult Male

Now on Herbal medicines and remedies

Herbal Medicine

10. Ayela; 34 year Female; Agidak Parish,

She became pregnant and was changed to Nevirapine but she reacted severely to Nevirapine and decided to abandon the treatment. She is planning to go to JCRC Mengo so that she can be re-initiated on ARVs.

Drug- related side effects

11. Betty, Female; 37 years; Alwala Parish; Bangala landing site; Namasale sub county.

DIED DIED

12. Apio 60/730 Muntu Sub county; Amolatar district township.

The client could not be traced. It seems she gave a wrong address at registration or relocated to another place, Last Refill date: 27/ 06/ 07.

Wrong Direction/ Relocated

13. Jenty ; 50- T30 Bangala-Alwala Parish; Namasale sub county, Amolatar district

Died in 2008; Cause of death could not be established

Died

14. Caesar ,Owiri Parish, Muntu Sub county; Amolatar ;Adult Male Last Refill date: 3/9/2008

Could not be traced in the village that was recorded as his residential area.

Lost to follow-up; cause unknown.

15. Connie 087/T30 Aboke; Iceme Sub county- Omolo Apany ;Lango; Apac district

The client was initiated on Septrin on 2/8/2007; picked her last Septrin refill on 21/09/2008. Now buys the Septrin from the drug shops, because she gets tired of waiting in the queues at the health center. She was never initiated on ART though she was eligible at CD4 count of 162 cells/ml.

Lost to follow-up before ART initiation.

16. Silpurosa ABK:CHCC.1848 Opeta parish; Mat Imed ikiti; Aboke sub-county-Apac district CD4 Count: 151

The client said she had never been initiated on ART

Lost to follow-up before ART initiation. Is on Septrin

17. Luwano-019- T30 Opeta parish; Abako; Aboke sub county Apac district

Died on 29/ 10 /2008 He was reported to have been overdrinking at the time of his death.

Died. Alcoholism problem.

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S/No. Description of the Defaulter

Reasons given for defaulting Remarks

18. Harriet: 018-T30 Atek. Idwati. Aboke Sub county. Apac district.

DIED on 09. 01. 2009 of diarrhea and vomiting

Died; cause unknown.

19. Awe Ayela Aboke

‘Septrin is enough for me’ ? Myths about ART ? Pill burden

20. Khadija LIDC/5270/ OK T30 Ojwina Division. Bar Ogole- Wigweng.

DIED. The neighbors said the client was very sick and taken to the village. They only heard that she had died.

DIED Cause unknown.

21. Felistar LIDC/658/AF T30 Adekokwo sub county- Obata Parish

The Client could not be traced in Obata Parish. Community members said he could have used a different name.

Wrong address given by client.

22. Grace, 25 years; female 023/T30 Ating Parish- Ayiki-Orum sub county –Lira.

She was reported t have re-located to Lira, Amuca; with another man.

Re-located

23. Suzan 029/T30 Olum Parish- Amyelo- Orum sub-county, Lira district.

Died on 2/10/2008 of severe malaria, diarrhea, and cough and vomiting.

Died.

24. Tonny 253/T30 Aliwang-Adwali sub county, Lira district.

He Died; but the cause of death and the date of his demise could not be ascertained: the family members were too emotional.

Died

25. Female PHA, Lira, 46 years.

She got a self-transfer to JCRC (Mengo), and was considered as lost to follow –up. She went because her CD4 count was coming down and there were no drugs for second line regimen.

Self- transfer out.

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6.16.0 Data Management Practices at 17-NUMAT supported sites A total of 1032 charts were reviewed of which only 239 (23.2%) provided complete data for analysis.  Bar Chart 7: Showing Charts with Missing and/ Complete data.

 

 Having a lot of missing data in the charts is a manifestation of poor data management practices, particularly at the point of data collection by the health workers. This could have introduced a hidden bias in the study findings. As can be noticed from the bar chart below, Gulu district did not provide any charts that were fit for analysis because all the charts from Gulu had a lot of missing data. This discovery points to the urgent need to train the health workers in data management; as well as strengthen and streamline information management at health unit and regional levels. The charts with complete data were distributed by district as shown in the bar chart below: Bar Chart 8: Showing distribution of charts with complete data by District

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Extensive Chart Review by the Research team at Amolatar health center IV

Table 36: Demographic characteristics of patients accessing ART at 17 NUMAT supported sites in Northern Uganda (Complete charts only) Variable Frequency(n=239) Percentage Age group 13-29 52 21.8 30-39 97 40.6 40-49 65 27.2 50+ 25 10.5 Sex Male 59 24.7 Female 180 75.3 If only the completed charts were considered men make up only 24.7% of patients accessing ART.

This could mean that there is a generally poor health-seeking behavior among men living with

HIV/AIDS in northern Uganda.

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Bar Chart 9: Showing Distribution of patients by Age group

The 30-39 age group was found to make up the biggest proportion of patients accessing ART; an indicator that HIV/AIDS is affecting mainly the young and productive age groups. Females were found to take up a very big portion of ART beneficiaries, perhaps further showing the vulnerability of women and girls to HIV/AIDS in conflict situations; and their positive health seeking behavior. Table 37: Socio-economic characteristics (Complete charts only). Variable Frequency (n=239) Percentage Marital status Married 133 55.7 Widow/Widowed 75 31.3 Other (single& separated) 31 13.0 Distance to the Health facility <=5km 55 23.0 6-10km 30 12.6 11-15km 121 50.6 16+km 33 13.8 District Lira 149 62.3 Kitgum 17 7.1Apac 46 19.3 Dokolo 6 2.5 Pader 2 0.8Amolatar 3 1.3 Amuru 8 3.4 Oyam 8 3.4

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Table 38: Showing the average Retention rates on ART in Northern Uganda (For complete charts only) Variable Number (n=239) Percentage Retention Retained 99 41.4 Lost to follow up 140 58.6 Bar Chart 10: Showing retention rates in ART programs in post-conflict Northern Uganda.

Bar chart 10 above shows that close to 60% of patients who were started on ART got lost-to-follow-up. The complete charts when considered alone, give much lower retention rates (41.4%). 6.18.0 Existing strategies for retention and adherence to antiretroviral therapy in Northern Uganda.

Information generated from the health workers during the FGDs showed that the following strategies are in place for enhancing adherence and long-term retention in ART programs in Northern Uganda:

Pill counting on every visit Adherence counseling at least three times before initiation “Group counseling and group health talks where clients are given opportunity to share

their experiences on side effects Health education on every clinic day where adherence features as one of the key topics Use of the patients’ cards to give them appointments; so that those with irregular

appointments are referred for more adherence counseling. Keeping patient cards which have the same appointment dates together, so that one can

easily tell who has not turned up. However, the majority confessed that they did not have no follow up or patient tracing

mechanisms in place.

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6.19.0 Current mechanisms for monitoring retention in antiretroviral therapy programs in Northern Uganda.

According to the ART Clinic Managers, the mechanisms for monitoring retention in ART programs were still limited. This was ably mentioned by one respondent as can be noted from the following quote:

“The mechanisms for tracking patients are limited because our services are facility based. We only depend on our records”(Male clinician-Acholi sub-region).

Nevertheless, the following mechanisms were reported to be in use at the time of the survey:

• ART clinic register: can monitor those who miss appointments. • Comprehensive HIV care cards. • Peer counselors know how to trace the clients. • Network support agents (But those are very few per sub county) • Home Based care visitors (Are based in the communities but are not linked to the health unit

structures). Other respondents in the health workers’ FGD sessions made the following comments: “People who work in the ART clinic are normally few because we do not want to paralyze other parts of the health unit. So, we have no time for keeping accurate records. Work load is too much, and sometimes there is lack of commitment by health staff to collect data.” “We need records monthly or quarterly mortality/ Morbidity audit meetings to get to the cause of the loss to follow up due to deaths, transfer outs. NUMAT should facilitate these meetings at each of these health facilities and at district and regional level.” “Parish expert clients can be used to register clients at parish level; they can report on a monthly basis to the health unit.” “PHA should be organized from district to local parish and facilitated to provide regular updates on quality of care, transfer outs, deaths etc. so that nearly accurate information can be got and kept.”

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The following pictures also carry significant information from the retention study:

In-depth interview with a defaulter: Patient tracing mechanisms can work (above).

The above picture shows efforts to improve data management at Anyeke Health Center IV through provision of Computers (courtesy of Baylor-Uganda).

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Pictured above: FGD session with male PLHIV accessing ART at one NUMAT-supported health unit.

FGD with female PLHIV accessing ART at Anyeke health center-Oyam district (see above)

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FGD session with female PLHIV still in care at Ogur health center IV (above). Data collection in Lango sub-region, pictured left.

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Above: Key Informant interview with a Clinical Officer at Aboke Health Center IV

Defaulter tracing in Aduku- Lango sub-region(see picture above)

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Picture above showing defaulter tracing in Amach: Wrong address given by a client.

Picture above shows existing ART records at Amach Health center IV. Few health Units keep accurate records.

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Picture above shows an FGD session with Male PLHIV at Amolatar Health Center IV

Picture above shows an FGD session with female PLHIV at Aduku-Lango sub-region.

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Picture above shows defaulter tracing in Ogur- Lango sub-region.

Defaulter tracing in Oyam district-Northern Uganda (Patient gave wrong address)

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Picture above shows an FGD session with female PLHIV at Aduku-Lango

Picture above shows FGD session with male PLHIV still in care at Aboke.

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Picture above shows a patient’s ART card with missing data (Body weight)

. Research team after data collection at Kitgum hospital (left); and Padibe health center pictured above.

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Key informant interview (above left); and FGD session (above right) at Padibe health center IV.

Above:FGD session with female PLHIV. Note the pregnant mother (in black dress) - PMTCT services?

Female FGD session-Pajule (above). PHA Peer support group office (Pajule)

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An empty IDP camp( Acholibur) Tools for defaulter tracing( Pajule health center)

NUMAT- increasing ART access at Awach HC IV. Research team consults at Pajule (above).

Left: Female PLHIV in an FGD session-Pajule. In-depth interview with a defaulter(Padibe)

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Expanding ART access in Acholi. Defaulter traced to her home in Lango(above).

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Chapter Seven

Discussion 7.1 Introduction: The purpose of this study was to determine the retention of HIV positive persons in ART programs in post-conflict northern Uganda. We set out to precisely determine the level of retention of patients in antiretroviral therapy programs supported by NUMAT in 17 government owned health units. We have also identified the factors that are significantly associated with retention; the predictors of attrition from ART programs at these study sites; as well as the reasons underlying loss-to- follow up in post-conflict situations. The fundamental methodologies applied were based on the principle of ‘participatory approach’ aimed at taking account of the views of a broad cross-section of the population of HIV positive persons in Northern Uganda; and ensuring that the views of all the relevant actors were expressed openly, freely and frankly. The study was based on both primary and secondary data. 7.2 Data Collection and significant Findings The successful collection and analysis of data from this cross-sectional survey was partially compromised by missing data in some of the reviewed medical charts. Of the 1032 charts reviewed, only 239 charts had complete information, indicating a critical gap in data management; particularly at the stage of data collection by the service providers. Whether this was due to heavy workload, negligence, or ignorance of the importance of data collection could not be easily ascertained. At this point, it is impossible to predict whether better outcomes would have been registered if all the reviewed charts had complete data: but common sense points in this direction. Our consolation is that we used triangulation of both qualitative and quantitative methods, thereby minimizing the limitations of each. Missing data is a major limitation of secondary data reviews. It is therefore not very surprising that we found a lot of missing data in the charts we reviewed. Although we minimized the attendant bias by reviewing more charts, we still could not achieve the required 294 medical charts as per the adjusted sample size calculation. Nonetheless, the qualitative data collected helped to provide deeper meaning to what was available from the quantitative data sources. According to Worster and Haines (2004), the advantages of conducting chart reviews include: a relatively inexpensive ability to research the rich readily available existing data; easier access to conditions where there is a long latency between exposure and outcome; and most importantly, the generation of hypotheses that can be tested prospectively. This particular study has drawn on the above benefits of retrospective chart review. However, according to Pan et al, (2005), chart review is also limited by incomplete documentation, missing charts, information that is unrecorded; difficulty interpreting information found in the documents; difficulty establishing the cause and effect and problematic verification of information. In our case we could not use WHO clinical staging in our analysis because there was variance in the quality of information recorded by the service providers.

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We endeavored to improve the quality of the data collected by carefully selecting and training the research assistants with the data collection tools and closely supervising them; as well as piloting of the data collection tools to determine inter-rater reliability. These are best practices recommended by Wu and Ashon (1997). It is however not all sad news. The ability to report on retention in ART programs in post-conflict northern Uganda, even after 20 years of a destructive civil war, is clear testimony that NUMAT has made great in-roads in establishing the basic monitoring and evaluation systems at these facilities. This routine monitoring and data management system could work even better, if it were backed by electronic systems and personnel specifically dedicated to data management and defaulter tracing at health unit level. 7.3 Strategic and Programmatically relevant findings: To the best of our knowledge, this study significantly differs from previous retention studies in terms of the study setting: a post conflict situation, following over 20 years of an armed insurgency that left thousands displaced and many dead. And because of the unique design of the study, direct outcome comparisons with other retention studies may be quite challenging; though extrapolation of the findings to other settings and ART programs is still crucially relevant. It is worthwhile to note that every single patient who is retained in care and on ART is a life saved; and potentially a source of tremendous benefit to families, communities and nations. Consequently, a loss-to- follow-up of 49% of those patients who are initiated on ART in northern Uganda must be a cause for grave concern. There is need for better and robust means of tracking patients who start on ART up to their doorstep at home. Only then would the NUMAT- supported ART programs be able to address the various reasons for attrition. According to Stephen et al (2006), the impact of ART in poor countries is unlikely to be related to questions of drug efficacy, but rather to health systems issues and program effectiveness. Our findings are in harmony with this assertion. When patients default on treatment, chances that they may die; or even develop drug resistant strains, which may be passed on to the general population are very high. With the rise in the number of patients requiring second line therapy, it is clearly evident that the higher cost of second line drugs will impact on total program costs as the NUMAT ART program matures. The most gratifying lesson learnt from this cross-sectional survey is that the NUMAT-supported ART program is covering many hard-to-reach areas despite the post-conflict situation and its attendant challenges. This is an indicator that ART can be delivered to those in need , even with the most basic of facilities and still achieve excellent clinical outcomes; provided there are adequate support systems around the patient. Making ART more accessible in geographical terms is therefore critical in enhancing retention of patients in HIV/AIDS care programs. In addition, this study has found that close to 70% of patients on ART were females. Various studies conducted in the past have always laid testimony to the poor health-seeking behavior among men. It was not a surprise therefore, that men made up the majority of defaulters in this survey. Interventions that target men need to be put in place and strengthened.

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The age groups 30-49 years constituted over 50% of the ART beneficiaries at the study sites. This implies that these age groups are the most affected by the AIDS scourge; and correlates well with the findings of the 2005 Uganda National Sero-behavioral survey. One interesting finding is that the numbers of patients registered at the primary health care level (Health center IV) were lower than at the district –based and regional referral hospital levels. This could be attributed to the sequence in which ART programs started in Northern Uganda, but could also be a symptom of an ailing health care system at the peripheral health units. Evidence from the focus group discussions held during the survey also shows that community residents’ stigma towards PLHIV is still very high; perhaps some prefer to seek care from afar, where they may not be easily identified. Unfortunately, the key informants reported that the hospitals are becoming ‘monster sites’ with huge patient loads; characterized by long waiting times. This ultimately compromises the quality of care and could lead to burn-out among the health workers. According to Dr.Gilles Van Cutsem of Medicins Sans Frontieres (MSF), relying on a few primary care sites could become just as bad as using larger hospitals. This implies that as NUMAT plans for the future, the issue of human resources for health at the supported health units will be even more critical, as more people access ART. Therefore, sustained capacity building of health workers, cascaded task shifting; enhanced supervision and motivation of health care providers should be a key consideration. A robust human resource recruitment, retention and retraining strategy ought to be put in place to overcome the capacity constraints. Sooner than later, some of the ART program resources should be channeled to addressing systemic human resource problems such as low pay, retention and geographical imbalances. Findings from this study showed that only 6.2% of the patients on ART were residing within a 5 km radius of the health facilities. In this particular study, patients who were residing at a distance of 11-15 km away from the health facility had a 1.6 fold increased hazard of being lost-to-follow-up as compared to those who were residing less than 5 km away from the clinic (p-value = 0.023). This highlights the issue of distance as a geographical barrier that could have an effect on the long-term retention of patients on ART. Similar findings were got by Schneider et al (2007), where they argued that the importance of high travel costs and the long time spent travelling to get to the ART sites is a critical factor affecting retention in ART programs in South Africa. The proportional hazards modeling we conducted during the analysis of our data actually showed that as the distance from the health unit increases, the risk of a patient getting lost-to- follow-up also increases. However, since the distance could have been mere estimates by the patients, they may not be accurate. Nevertheless, a distance that is 5km and above, for any AIDS patient would still be a great strain to a person who goes to the health facility by foot; which is a very common occurrence in our setting. Also, one of the major challenges emerging from this survey in northern Uganda is the large number of patients moving between facilities, who, once self-transferred out, are censored in the cohort analysis and counted as either dead or lost-to-follow-up. This raises the need to urgently consider national identification systems with data- bases that are interlinked and can be shared between the various players in the HIV/AIDS field, particularly at regional level. In this study, the defaulter tracing exercise showed that 52% of the patients who were lost-to- follow- up had actually died. Similar findings were indeed obtained by Dr. Ebrahim Variava of

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Klerksdorp Tshepong Hospital complex in South Africa, when he followed up defaulters and found that 42% had died. The statistics in our setting are worse, probably because of the harsh challenges that confound HIV/AIDS in a post-conflict situation. Early death on ART could be due to opportunistic infections or due to immune reconstitution inflammatory syndrome (Variava, E., 2007). Findings recorded in table 14 indicate that higher incidences of tuberculosis, cryptococcal meningitis, Oesophageal candidiasis and Kaposi’s sarcoma were diagnosed by the health workers after ART initiation for the patients in the NUMAT-supported programs. This was most likely due to immune-reconstitution inflammatory syndromes. Indeed, similar findings have been obtained in other studies; and these points to the late initiation of patients onto antiretroviral therapy. Since the data we utilized was retrospective, it was difficult to ascertain whether the patients were actually taking ART at the time of death. What compounded the problem further is the fact that Luo culture abhors probing into the circumstances and possible causes of death.

7.3.1 Drug Stock-outs:

The commonest reason for change of ARV combination was drug stock-outs. This was also a major complaint registered throughout the FGD sessions, and is key to adherence and retention in ART programs. According to Hon. Richard Nduhuura ( Minister of State for health in charge of General duties), the National Medical Stores, who are the chief suppliers of antiretroviral drugs to government health units, is being overhauled and soon drug stock-outs ‘will soon be a thing of the past’(The New Vision, Vol. 24; No. 106, pages 14-15. June 1st 2009). Despite the political promises, we are yet to register an impact on service delivery at health unit level. Clearly, any ART program worth its name ought to urgently address the issue of ARV stock-outs as an emergency; for the consequences are well known to all of us.

7.3.2 CD4 Count rise and Body weight gain

Findings from this study indicate that the majority of patients registered improvement in these two clinical indicators of ART drug efficacy. This implies that the impact of the NUMAT-supported ART programs in northern Uganda will be more assessed on health system issues and program effectiveness, rather than drug efficacy. Therefore NUMAT needs to concentrate on health systems strengthening. Findings also indicated that about 87% of patients on ART were also accessing Co-trimoxazole (Septrin) prophylaxis under the NUMAT supported program. This is way above the national average of 60% as reported by Uganda’s Ministry of health and is an indicator of efforts being made by NUMAT to provide a basic care package to PLHIV in northern Uganda. However, findings from the FGD sessions with the health unit managers indicated that there was no alternative drug, such as Dapsone, provided for those who may be allergic to Cotrimoxazole.

7.3.3. Pregnancy and PMTCT access

From table 13, it is evident that only 5.3 % of pregnant women had ever been given Nevirapine for PMTCT; yet their pregnancy rates are as high as 2-5%. Though PMTCT uptake has generally been reported to be very low in Uganda due to various factors (most especially the lack of male involvement), there is a critical need to qualitatively gain an insight into this area. This being a unique setting, the sexual and reproductive health choices for persons living with HIV/AIDS in

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post-conflict northern Uganda is beyond the scope of our survey. The fertility desires, fertility intentions and reproductive health choices of this population will clearly, require further study. Another notable observation is that failure to implement effective and sustainable PMTCT interventions will increase the need for paediatric ART in the near future, with the attendant costs to the program. Evidence already suggests that paeditric HIV/AIDS care is still lagging behind in the NUMAT-supported ART programs. Clearly, something ought to be done so that children are prioritized.

7.3.4 Retention rates in the NUMAT-supported ART programs:

The overall retention rates in the ART programs at the 17 health units was found to be 51.1%. Though this low by any standards, it is not very surprising. Various retention studies conducted in Uganda in the recent past have given a range of 39 – 81 % for most ART programs. Nevertheless, we cannot congratulate ourselves on this finding. Low retention rates are an indicator of major weaknesses in the support systems around the client; and a sign that valuable, yet scarce resources may be going down the drain. Therefore, all efforts must be made to address the underlying reasons to loss-to-follow-up at technical, strategic and programmatic levels. According to our findings, (table 13), loss-to-follow-up is highest during the first 6 months of ART initiation when the patients have probably not yet stabilized on treatment. Similar findings have been reported in various studies on retention in ART programs in South Africa.

7.3.5 Demographic characteristics and loss-to-follow-up

Among the male clients, 46% were found to have been lost-to-follow-up as compared to 50.1% among the female clients, over the same period. However this did not achieve statistical significance (p value = 0.710); indicating that retention on ART seems not to be associated with the sex of the client. Conversely, the married clients in this study were found to have had the highest rates of loss-to-follow-up of 58.2 % while the lowest was among the widowed. Marital status therefore may be associated with retention in an ART program, at 10% level of significance (p-value = 0.097). But this is a peculiar finding that we could not easily collaborate with findings from other studies elsewhere. Nonetheless, there is evidence from our qualitative data which suggests that there is actually a possible linkage. Another unique finding from the bi-variate analysis of our data was that 55% of the patients whose ART combination was not changed were eventually lost-to-follow up, as compared to 33.5% among those who had changed ART combination; and this had statistical significance (p-value < 0.001). This could mean that probably those whose ART combination was not changed lost hope and stopped treatment, thinking that perhaps they were on an inferior regimen. To the best of our knowledge, no other study has obtained a similar finding. Furthermore, findings from this study also indicate that the highest rate of loss-to-follow-up was observed among patients who had body weights less than 45 kg at the time of initiating treatment. This association was also statistically significant (p-value = 0.041). The implication may be that those who started on ART when they were wasted either faced a lot more stigma; or could have had more severe immune system damage and hence could not recover. This further reinforces findings

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from previous immunological studies that recommended early ART initiation before irreversible immune system damage has occurred.

7.3.6 Health System Factors in ART programs

Study findings are in agreement with other studies which have shown that the majority of ART beneficiaries are initiated, monitored and followed up by non-physician health workers. In this era of acute shortages of health professionals in Africa, practice seems to be ever preceding policy; hence task shifting to less qualified health workers may eventually be the rule rather than the exception(Ashie M.,et al,2007 & Thistle et al,2007).

7.3.7. Reasons for loss-to-follow –up

According to the key informants in this study, the commonest reason why patients were reported as lost-to follow-up, was relocation(16 out of 17 respondents); death (15 out of 17); lack of finances to meet transport costs (10 out of 17); and long distances to the health units( 7 out of 17 respondents). Almost similar findings were obtained in a South African study (Variava, E., 2007). However, our study also found that the community follow-up and support systems around the patients on ART in this region were still very weak; only 2 Network Support Agents (NSA) were available for each sub-county; and their motivation required further enhancement. According to Dr.Worley S.B. et al (2007) ; and Chirwa Z. & Africaner .E.,2007), strong support groups are a well-noted mechanism to really help retain patients in care and to help find missing members. These support groups clearly play a vital role in reducing stigma and discrimination, providing treatment literacy and tracking defaulting clients. They also recommend task shifting and the use of community-based mechanisms. This is the way to go in order to improve adherence and long-term retention in this setting as well.

7.3.8 Stigma and discrimination against people living with HIV/AIDS

All the Focus group discussions we conducted with patients on ART who were still in care were awash with narratives of very painful and extremely stigmatizing experiences these patients go through on a daily basis. Clearly, stigma stands out as the single greatest impediment to ART access, adherence and long-term retention in northern Uganda. According to Denis Nduhuura (2004) - HAJAP Program Manager-A.C.O.R.D., there is no longer any dispute over the fact that challenging stigma and discrimination constitutes a critical part of the equation in the fight against HIV/AIDS. This is even truer in the light of recent developments that have helped to reduce the price of drugs, thereby enhancing the potential for ARVs to be reached by some of the poorest and most needy people living in Sub-Saharan Africa. However, unless stigma and discrimination are challenged, they are unlikely to access these life drugs.

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7. 4 Conclusions Since the inception of large-scale ART access early in this decade, ART programs in Africa have retained about 60% of their patients at the end of 2 years. Overall retention rates in northern Uganda average about 51.1%. The major cause of patient attrition from ART programs in this post-conflict setting is Loss to follow-up due to relocation, death, long distances from the health facility; stigma at individual, community and household levels; ARV related-side effects; incarceration, and self- transfer by patients to other providers who offer other incentives. Instituting better patient tracing procedures, better understanding of loss to follow-up and earlier initiation of ART to reduce mortality are needed if retention is to be improved. The key priority areas for action by NUMAT include:

Increased community engagement and expansion of training and deployment and motivation of community health workers.

The development of human resource capacity for health in their catchment areas. The lack of human resource capacity has been identified as one of the greatest barriers to overall health sector delivery.

Intensifying strategies to fight stigma and discrimination at all levels Strengthening the ARV drug stocks and logistics supply chain management in order to off-

set shortages and stock outs caused by the inefficiencies of the National Medical stores. Improvement of health care infrastructure & equipment; and Provision of electronic systems for data management at health unit level.

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Chapter Eight Recommendations

1. There was strong evidence of missing data, at most health facilities. We recommend that NUMAT takes critical steps to strengthen record keeping and improve M & E practices at the NUMAT-supported ART sites. This could be done through recruitment of data clerks who can double as adherence counselors to collect data, and trace individuals who default on treatment; training of health workers in the importance of data in programmatic management; and establishment of a computerized information management system at various levels. Data collection tools should be user-friendly, given the client loads at the clinics. Establish and put to use standardized systems to quickly detect loss to follow up(i.e. standardized tools, pre-ART and ART registers; Appointment registers; tracking registers to monitor tracking and re-entry to care, community registers and patient mapping). NUMAT could even consider employing dedicated people at village level to track down defaulters.

2. A comprehensive response is required to address the complex causes and multi –dimensional consequences of stigma and discrimination. There should be provision of accurate, unbiased information to dispel the many myths , misconceptions and stereotypes linked to HIV/AIDS ; the greater involvement of people living with HIV/AIDS in the development and implementation of responses at all levels; support for associations of people living with HIV/AIDS to promote solidarity and mutual support; training for community-based counselors to provide technical advice and home-based care to patients and their families; increased access to treatment, testing and other services. NUMAT should endeavor to address stigma at household level, individual, and community levels (schools, churches, villages, markets etc). Stigma reduction strategies could incorporate HIV/AIDS awareness campaigns through public dance & drama performances; radio programs; IEC materials dissemination; training and advocacy for PLHIV and radio programs focusing on stigma and discrimination. This will lead to encouraging PLHIV to adopt and maintain positive living practices; increase the disclosure of HIV status among sexual partners; and improve community involvement in HIV/AIDS services. It would also be wise to incorporate HIV-negative persons into the NSA networks and peer support groups to further minimize stigma and discrimination.

3. Greater focus on the family: Families affected by HIV are critical partners in working successfully with the index clients and communities. Families determine the quality of the client’s first-line support system and also interface the client and the community systems. NUMAT should use index clients as an entry point to reach out, mobilize, sensitize and provide services to the other family members. This systemic approach will improve the welfare of people living with HIV, address stigma and discrimination at household level, and contribute to the general efforts to scale-up HIV/AIDS services.

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4. NUMAT should focus resource allocation towards intensifying AIDS awareness and community sensitization against stigma and discrimination. This should entail efforts aimed at school-going children, teachers, radio presenters, religious leaders, health workers, civil servants the business communities, traditional healers, the uniformed service, and out-of-school youths. NUMAT should utilize the mass media to deliver clear messages for stigma reduction and ART literacy; and increase collaboration and networking among community- based organizations, to develop complementary and integrated strategies for combating HIV/AIDS- related stigma and discrimination. To be successful, these actions will need to be integrated into existing development frameworks, including poverty reduction strategies, national plans of action, sector wide approaches and emergency response plans. NUMAT must, of necessity seek out for every opportunity for increasing partnerships in order to strengthen its HIV/AIDS programs. Particular focus should be laid on those partnerships that will create sustainable livelihoods for PLHIV to address household food insecurity.

5. Children must be prioritized for treatment of HIV/AIDS. There is need to re-build the

confidence of the families to take care of children affected by HIV/AIDS in the region. Further study of the patterns and factors affecting their adherence to ART in post-conflict settings warrants critical study. Of key importance also is a deeper understanding of the challenges and coping mechanisms among adolescents living with HIV/AIDS in post-conflict Northern Uganda.

6. Strong Community follow-up and patient support systems should be a precondition for all ART Programs in this region. It is important to understand that HIV is both a social and health problem. Professional community outreaches should be used to ensure strong linkages between health units and families. NUMAT could consider building the capacity of private health care providers to provide a substantial proportion of HIV care, including ART treatment. NUMAT should also involve communities and PLHIV/As, particularly in the provision of peer psychosocial support, adherence counseling, ART literacy, and in the tracking of ART patients. Expand the NSA networks to at least one per village.

7. Equip more nurses and clinical officers with the required knowledge and skills to manage patients on ART. More responsibility should be delegated to lower level health workers, while ensuring that professional medical oversight is provided to maintain quality control. Empowering nurses is essential for maximizing efficiency at the primary care level. NUMAT could also consider instituting a mobile training and mentoring team so that all ART sites receive regular physician support for overall HIV/AIDS care provision. The terms of reference should encompass training and mentoring of nurses and clinicians in HIV management, treatment of opportunistic infections, Paediatric HIV/AIDS care, PMTCT, STI management, as well as systems improvement and quality assurance. Additionally, some of the ART program resources could be channeled to addressing systemic human resources problems, such as low pay and retention. This team should also design training and mentor-ship strategies for improving patient-provider relations through continuous client sensitization of their rights as patients; as well as training health workers in customer care and public relations; stigma reduction; supported disclosure, etc.

8. Create linkages between HIV prevention, testing, care and treatment for the family with TB contact tracing. This would be a critical intervention for the family’s wellbeing because TB usually spreads within the home. TB clinics serving co-infected populations should

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therefore be equipped to provide these family-based interventions during home-visits. This means training staff, peer educators or community-based DOTS supporters- and providing them with some way of documenting whether the activity was thorough and complete. Available human resources at facilities providing DOTS’ services- which are mostly at primary health care centers that are very close to the people- should be leveraged to provide ARV services for those without access to these services. There is need to staff all peripheral health units with better trained providers who are able to manage and treat both HIV and TB. Place ART clinicians in the TB clinic which would also allow the clinic to initiate ART during the first two months of TB treatment rather than waiting until after the client has a confirmed sputum conversion.

9. Establish regular audit meetings for ART Clinic managers to share challenges, as well as promising practices on a monthly or quarterly basis. This should also serve as a forum for the NUMAT information managers to review health unit data bases and offer the necessary technical support.

10. It would also be useful to introduce outreach services at each of the health facilities; functional home-based care services provided by trained health workers; as well as community drug distribution points for delivering ARV refills nearer to the patients’ homes. Health units should be organized to visit the homes of PLHIV to build relationships with them, provide chronic care, encourage them, and demonstrate that they are important community members. This would reduce on the distances that patients have to travel to the health units; raise community awareness; or even contribute to stigma reduction. Consider also, the integration of people living with HIV/AIDS (PLHIV) and the community into the clinical team using peer educators to do the counseling, prepare the person for ART, and monitor and track defaulters.

11. It is strongly recommended that NUMAT sets the pace for establishing ART clinics in the more peripheral health units at the grassroots( i.e. Health center II and III) in order to reduce on the work load at the existing ART sites. These lower units could be overseen by a visiting clinician on a regular basis.

12. NUMAT should strengthen the laboratory monitoring systems to ensure that CD4 counts are done on a regular basis and accurate records are kept for better monitoring of the patients clinical outcomes. NUMAT should also consider providing laboratory reagents to the health facilities, as well as train laboratory assistants in the diagnosis of opportunistic infections and ART monitoring.

13. In order to further impact on the quality of HIV/AIDS care offered at the NUMAT-supported sites, it is strongly recommended that in addition to the provision of ARVs and Cotrimoxazole supplies, NUMAT should take on the responsibility of providing essential drugs for the management of common opportunistic infections, including intravenous fluids.

14. It is also recommended that NUMAT trains all health workers at these sites in counseling skills: particularly child counseling and discordant couple counseling. This will enhance their ability to offer holistic care to the patients who are entrusted to their care.

15. NUMAT should lead the process of increasing VCT access at community and household levels, using outreach/ mobile VCT clinics .Private health service providers could also be

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accredited and supported to offer VCT services under the overall supervision of the NUMAT program.

16. Specifically target and utilize PLHIV. Train them in positive living, positive prevention; drug adherence; public speaking, disclosure; stigma reduction and OVC child care. PLHIV are often poor, weak and in need of care and support. Funds should be set aside for sustainable livelihoods programming and income-generating activities for PHA groups. Target men because due to their dominant social status within the culture and communities, they fear to disclose their HIV status.

17. There is need to engage a wider range of partners and other strategies to improve patient follow-up for patients on ART: PLHIV support groups; NGOs, CBOs, FBOs, local community structures, prisons’ authorities, school teachers, students clubs etc. When implementing any project activity at the grassroots level, it is critical that NUMAT continues to form good relationships with local leaders and other NGOs active in post-conflict Northern Uganda and regularly organize consultative fora with all stakeholders to share lessons learned, promising practices and chart the way forward for program improvement.

18. Youth are amongst the critical populations needing special attention in HIV prevention programming. This is made more critical by the fact that Uganda has a generally young population with over 50% being people below 15 years. We are about to witness increasing numbers of HIV+ children growing into youths because of antiretroviral therapy. These and other dynamics influencing youths demand programs that address their needs specifically. NUMAT should put in place strategies for youth-specific HIV prevention services that could comprise training youth leaders; promoting school-based HIV prevention services; facilitating formation of adolescent peer support clubs; conducting MDD performances in schools; distributing youth-friendly HIV prevention IEC materials; promoting HIV prevention through sports; organizing other contests for HIV prevention; and creating safe recreational and education space for adolescents at NUMAT –supported sites.

19. A large percentage of the target population does not listen to the radio, hence rendering radio communication ineffective when considering the very poor. Drama presentations are the most effective communication tool in HIV/AIDS sensitization. Drama presentations leave deep impressions on the mind s of the audience, as drama is difficult to forget. Sensitization is not only important in combating ignorance on HIV/AIDS and stigma, but also in providing PHAs with the confidence to openly disclose their status. Also, local officials are integral to community sensitization. Partnering with local leaders builds confidence within the community and allows for the sustainability of the program.

20. People living with HIV/AIDS (PHA) make unique contribution to HIV/AIDS programming through a strength that combines acquired knowledge and skills with personal experience of living with HIV/AIDS. NUMAT should make deliberate efforts to enhance meaningful involvement of PHA at all levels of planning and programming, aimed at channeling their unique contribution to inform and influence service delivery. NUMAT should also carry out advocacy, collaboration, networking and capacity-building aimed at increasing the visibility and influence of PHA on HIV/AIDS programs. Program models to empower PHA should then be documented and shared widely with other implementing partners.

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REFERENCES Allen, Tim."Trial Justice: The International Criminal Court and the Lord's Resistance Army", African Arguments Series, Zed Books, London,2006. ISBN 1-84277-737-8 Allison, J.J., Wall, T. C., Spettell , C. M., Calhoun, J., Fargason , C.A., Kobylinski,R.W., Farmer, R. & Kiefe, C. (2000). The art and science of Chart review. Journal of Quality Improvement, 26(3), 115- 136. Ammassari A, Trotta M, Murri R, et al. Correlates and predictors of Adherence to Highly Active Antiretroviral Therapy: Overview of Published Literature. JAIDS, December 15, 2002; 31(suppl 3): S123- S127.

Angela .H, (2004). Unraveling the Dynamics of HIV/AIDS related Stigma and Discrimination, the role of community- Based Research, Case Studies of Northern Uganda & Burundi. A.C.O.R.D.- Agency for Cooperation and Research Development.

Ashie M et al. Partnering with people living with HIV/AIDS to support HIV/AIDS prevention, care, and treatment services in rural Nigeria. HIV Implementers’ Meeting, Kigali, Rwanda, abstract 309, 2007.

Ashton, C. M., Kuykendell , D.H., Johnson, M.L., Wray, N. P. & Wu, L., (1995). The association between the quality of inpatient care and early Readmission. Annals of Internal Medicine, 122, 415-421. Bangsberg DR, Hecht FM, Charlebois ED, et al. Adherence to protease inhibitors, HIV-1 viral load, and development of drug resistance in an indigent population. AIDS 2000, 14:357-366.

Bangsberg DR, Perry S, Charlebois ED, et al. Non-adherence to highly active antiretroviral therapy predicts progression to AIDS. Aids 2001,15:1181-1183.

Behrend, H. (M. Cohen, trans.) Alice Lakwena and the Holy Spirits: War in Northern Uganda, 1985-97, James Currey, 2000. ISBN 0-8214-1311-2.(Originally published as Behrend , H. 1993. Alice und die Geister: Krieg in Norden Uganda. Trickster, Munich.)

Blower S, Bodine E, Khan J et al. The antiretroviral rollout and drug-resistant HIV in Africa: insights from empirical data and theoretical models.AIDS.19 (1): 1-14, January 3, 2005.

British HIV Association. HIV Treatment Guidelines 2005. British HIV Association 2005.

Caplan , R.A., Posner , K. L. & Cheney, F. W. (1991). Effect of outcome of physician judgments of appropriateness of care. Journal of the American Medical Association, 167, 567-572.

Chirwa, Z and Africaner E. The Buddy Programme, successes and challenges in a resource limited setting in Katima Mulilo, Namibia. Third South African AIDS Conference, Durban, abstract 526, 2007.

118

DeOlalla P, Knobel H, Carmona A, Guelar A, Lopez-Colomes J, Cayla J.Impact of adherence on highly active antiretroviral therapy on survival in HIV-infected patients. JAIDS 2002, 30:105-110.

De Temmerman, E. Aboke Girls: Children Abducted in Northern Uganda, Fountain, 2001. ISBN 9970-02-256-3. (Originally published as De Temmerman, E. De meisjes van Aboke: Kindsoldaten in Noord- Oeganda. De Kern, 2000. ISBN 90-5312-146-3.). Doom, R. and K. Vlassenroot. "Kony's message: a new koine? The Lord's Resistance Army in Northern Uganda," African Affairs 98 (390) 1999: 5 to 36). Dworkin, R.J. (1987). Hidden bias in the use of archival data. Evaluation and the Health Professions, 10(2), 173-185.

Etienne M et al. Effect of varying models of adherence support on lost to follow up rates; findings from 34 treatment facilities in eight resource limited countries. 4th International AIDS Society Conference on HIV Pathogenesis, Treatment and Prevention, abstract WEPEB101, Sydney,2007.

Gingyera-Pincywa, A.G. "Is there a Northern Question?" in K. Rupesinghe , ed. Conflict Resolution in Uganda, International Peace Research Institute, Oslo, 1989. Goldman, R.L. (1992). The reliability of peer assessments of quality of care. Journal of the American Medical Association, 267, 958-960.

Haley, R.W., Hooton, T. M., Schoenfelder, J.R., Crossley , K.B., Quade , D., Stanley, R.C. & Culver, D. H. (1980). Effect of an infection surveillance and control program on the accuracy of retrospective chart review. American Journal of Epidemiology, 111(5), 543-555. Hellings, P. (2004). A rich source of clinical research data: Medical records and Telephone logs. Journal of Paediatric Health care, 18(3), 154-155. Hess, D.R. (2004). Retrospective studies and chart reviews. Respiratory Care, 49(10), 1171-1174. Hogg RS, Heath K, Bangsberg D, Yip B, Press N, O'Shaughnessy MV et al. Intermittent use of triple- combination therapy is predictive of mortality at baseline and after 1 year of follow- up. AIDS 2002; 16(7):1051-1058.

Holmboe, E., Gross, R. & Hawkins, R. (1996). Chart reviews for residents. Academic Medicine, 71(11), 1139. http: // www.aidsmap.com/cms 1191180.asp http://hab.hrsa.gov/publications/chapter 5/Chapter 5. Accessed on 22/03/07. http://www.medinet.lk/aids/aids-watch.htm. Accessed 22/09/07.

http:// www.msf.org.za/docs/lusikisiki_final_report_2006 pdf

119

Jackson, P. "The March of the Lord's Resistance Army: Greed or Grievance in Northern Uganda?" Small Wars and Insurgencies 13, no. 3 (autumn 2002): 29 to 52.

Jansen, A,C.M., van Aalst- Cohen, E. S., Hutten, B. A., Buller, H.R., Kastelein,J.J.P. & Prins, M. H. (2005).

Lippincott Williams & Wilkins (2003). Expanding access to HIV antiretroviral therapy. AIDS 17(17): 2419- 2427, 2003.

Magula, Nombulelo et al. Adherence to HAART in the first year of the rollout programme at King Edward VIII Hospital, KwaZulu-Natal, South Africa. Third South African AIDS Conference, Durban, 696, 2007.

Mallory. O. Johnson, Sydney R*, Matthew P. F., Christopher J. G. (2008).Patient Retention in Antiretroviral therapy programs in Sub-Saharan Africa. A Systematic Review. cf. PLOS Medicine.

Maponyane M et al. 2-year follow-up of patients attending ART clinics in Gauteng and the North West Province: results of a systematic review of 13,097 patients. Third South African AIDS Conference, Durban, Abstract 326, 2007.

Ministry of Health. Republic of Uganda. National Sero-behavioral survey, 2005.

Mlambo, K et al. Down referral project: a way to prevent overloading at initiation sites. Third South African AIDS Conference, Durban, abstract 592, 2007.

Nduhuura. R.(2009). National Health Insurance to improve lives, productivity of Ugandans. The New Vision,Vol.24; No. 106. Pages 14-15. June 1st 2009. Neidich, B. (1990). A method to facilitate student interest in research: Chart Review. Journal of Nursing Education, 29(3), 139- 140. Nieuwkerk P T, Sprangers MAG, Burger DM et al. Limited Patient Adherence to Highly Active Antiretroviral Therapy for HIV-1 infection in an Observational Cohort Study. Arch Intern.Med.2001; 161:1962-68. Ofcansky , T. "Warfare and Instability along the Sudan-Uganda Border: A Look at the Twentieth Century" in Spaulding, J. and S. Beswick , Eds. White Nile, Black Blood: War, Leadership, and Ethnicity from Khartoum to Kampala. Red Sea Press, Lawrenceville, NJ: 195-210, 2000. Pan, L., Fergusson, D., Schweitzer, I. & Herbert, P.C. (2005). Ensuring high accuracy of data abstracted from patient charts: The use of a standardized medical record as a training tool. Journal of Clinical Epidemiology, 58(9), 918- 923.

120

Paterson DL, Swindells S, Mohr J, Brester M, Vergis EN, Squier C et al. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med 2000; 133(1):21-30.

Paterson et al, 6th Conference on Retroviruses and Opportunistic Infections; 1998; Abstract 1-172.

Reuters Alert Net accessed at http://www.IRIN news.org on 18/03/2009.

Schneider H et al. Can the public sector rise to the challenge of ART? Evidence from second generation sites in Gauteng Province. Third South African AIDS Conference, Durban, abstract 474, 2007.

Sydney R., Matthew F.P., Christopher J.G. Patient Retention in Antiretroviral Therapy Programs in Sub-Saharan Africa: A Systematic Review, 2007. Smith, A. J. (1996). Chart reviews made simple. Nursing Management. 27(8): 33-34 Thistle et al. Decentralization of antiretroviral treatment in a rural district in Zimbabwe: experiences and lessons at one year. HIV Implementers’ Meeting, Kigali, Rwanda, abstract 730, 2007.

Variava E. Reasons for loss to follow-up and defaulter tracing after 2 years of ART programme. . Third South African AIDS Conference, Durban, Abstract 590, 2007.

VonKoss Krowchuk, H., Moore, M.L. & Richardson, L. (1995). Using health records as sources of data for research. Journal of Nursing Measurements, 3(1), 3- 12. Ward, K. "'The Armies of the Lord': Christianity, Rebels and the State in Northern Uganda, 1986- 1999", Journal of Religion in Africa 31 (2), 2001. War in Northern Uganda: The Holy Spirit Movements of Alice Lakwena, Severino Lukoya and Joseph Kony (1986-1997)", in Clapham, C. ed. African Guérillas. James Currey, Oxford, 1998. WHO.2003.Scaling up antiretroviral therapy in resource-limited settings: Treatment guidelines for a public health approach. World Health Organization, United Nations Joint Program on HIV/AIDS Report, 2007.

Worley SB et al. Development of a system for identifying and tracking ART Patients to minimize losses to follow-up in Eastern Cape South Africa. Third South African AIDS Conference, Durban, Abstract 672, 2007.

Worster, A. & Haines, T. (2004). Advanced Statistics: Understanding medical record review (MRR) studies. Academic Emergency Medicine, 11(2), 187- 192. Wu, L. & Ashton, C.M. (1997). Chart Review: A need for Reappraisal. Evaluation and Health Professions, 20(2), 145-163.

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APPENDICES RETENTION OF HIV POSITIVE PERSONS IN ART PROGRAMS IN POST-CONFLICT NORTHERN

UGANDA- BASELINE SURVEY Form 1 ART Clinic Register Review

__ __ __ __ __ __ Patient Study Number Section 1 Interview Information NO. QUESTIONS AND FILTERS CODING CATEGORY SKIP TO ANSWER 1. Questionnaire Identification Number Clinical records 01

Laboratory register 02 Pharmacy logbook 03

2. Site Identification Number [Codes to be listed]

3. Interviewer code [Codes to be listed]

4. Data entry staff 1 initial

5. Data entry staff 2 initial

6. Data collection date [__ __ | __ __ | __ __ ] DD MM YY

7. Record patient unique ID number

8. Record patient health facility file number

9. Record study participant ID number. Record patient study number of every page of questionnaire.

10. Start time of data collection __ __ : __ __ [Hour: minute]

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__ __ __ __ __ __ Patient Study Number Section 2 Patient Characteristics NO. QUESTIONS AND FILTERS CODING CATEGORY SKIP TO ANSWER11. Record Sex

Male 01 Female 02

12. Record month and year of respondent’s birth.

[__ __] in completed month Don’t know 777 [__ __ __ __ ] in completed year Don’t know 777

13. Record marital status Single 01 Married 02 Cohabitating 03 Divorced/ Separated 04 Widow/ Widowed 05 Not recorded 555

14. District/ Division/ Ward [Codes to be listed] Not recorded 555

15. Village name of usual place of residence (de jure)

[Codes to be listed] Not recorded 555

16. Village name of current place of residence (de facto)

[Codes to be listed] Not recorded 555

17. Distance to clinic (km) [Codes to be listed] Not recorded 555

18. Did patient transfer into clinic No 00 Yes 01 Not recorded 555

Q21 Q19 Q21

19. Record date of patient transfer into clinic

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

20. Record date that patient initiated ART BEFORE transferring to this clinic

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

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__ __ __ __ __ __ Patient Study Number Section 3: ART Regimen NO. QUESTIONS AND FILTERS CODING CATEGORY SKIP

TO ANSWER

21. Record start date of FIRST ART treatment prescribed at this facility.

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

22. Record FIRST ART prescribed at the facility: First look for fixed dose combinations (FDC). FDC are a combination of drugs in one pill/ tablet/ capsule. - Triple combination means there are

three drugs in one pill, such as “D4T(3), 3TC, NVP”.

- Double combination means there are two drugs in one pill, such as “Combivir” (AZT/3TC).

Find and circle the correct FDC. If a FDC is not available, circle each single ARV drug in regimen. If ARV is not listed in the table, record the name of the drug under x) Others (Specify).

DRUG NAME Triple combination: three drugs combined in one pill a) d4T (30), 3TC, NVP

b) d4T(40), 3TC, NVP

c) AZT (ZDV), 3TC, NVP

d) TDF, FTC, EFV

e) AZT (ZDV), 3TC, ABC Double combination: two drugs combined in one pill (including boosted PIs) f) AZT (ZDV), 3TC

g) TDF, FTC

h) LPV, RTV

Single antiretroviral drug

i) AZT (Zidovudine/ ZDV)

j) ddI (Didanosine)

k) d4T (Stavudine)

l) 3TC (Lamivudine)

m) ABC (Abacavir)

n) NVP (Nevirapine)

o) EFV (Efavirenz)

p) IDV (Indinavir)

q) NFV (Nelfinavir)

r) SQV (Saquinavir)

s) RTV (Ritonavir)

t) FTC (Emtricitabine)

u) TDF (Tenofovir) v) Others? (Specify)

___________________

23. Record stop date of first ART. [__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

__ __ __ __ __ __

124

Patient Study Number Section 3: ART Regimen NO. QUESTIONS AND FILTERS CODING CATEGORY SKIP TO ANSWER24. Has ART regimen changed since first

prescription? No 00 Yes 01

Q26 Q25

25. What was the reason for discontinuation of first ART regimen? N.B. Adverse reactions include: nausea/ vomiting, diarrhea, headache, fever, rash, peripheral neuropathy, hepatitis, jaundice, dementia, anemia, pancreatitis, CNS adverse event, other adverse event

Starting TB treatment 01 Adverse reactions (see list) 02 Treatment failure clinical 03 Treatment failure immunological 04 Poor adherence 05 Patient decision 06 Pregnancy 07 End of PMTCT 08 Stock out 09 Other, specify _____________ 66 Not recorded 555

26. Record start date of SECOND ART treatment prescribed at this facility.

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

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Patient Study Number Section 3: ART Regimen NO. QUESTIONS AND FILTERS CODING CATEGORY SKIP

TO ANSWER

27. Record SECOND ART prescribed at the facility: First look for fixed dose combinations (FDC). FDC are a combination of drugs in one pill/ tablet/ capsule. - Tripe combination means there are

three drugs in one pill, such as “D4T (30), 3TC, NVP”.

- Double combination means there are two drugs in one pill, such as “Combivir” (AZT/3TC).

Find and circle the correct FDC. If a FDC is not available, circle each single ARV drug in regimen. If ARV is not listed in the table, record the name of the drug under x) Others (Specify).

DRUG NAME Triple combination: three drugs combined in one pill a) d4T (30), 3TC,

NVP b) d4T(40), 3TC,

NVP c) AZT (ZDV), 3TC,

NVP d) TDF, FTC, EFV e) AZT (ZDV), 3TC,

ABC Double combination: two drugs combined in one pill (including boosted PIs) f) AZT (ZDV), 3TC

g) TDF, FTC

h) LPV, RTV

Single antiretroviral drug i) AZT (Zidovudine/

ZDV) j) ddI (Didanosine)

k) d4T (Stavudine)

l) 3TC (Lamivudine)

m) ABC (Abacavir)

n) NVP (Nevirapine)

o) EFV (Efavirenz)

p) IDV (Indinavir)

q) NFV (Nelfinavir)

r) SQV (Saquinavir)

s) RTV (Ritonavir) t) FTC

(Emtricitabine) u) TDF (Tenofovir) v) Others? (Specify)

___________________

28. Record stop date of second ART. [__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

29. Has ART regimen changed since second prescription?

No 00 Yes 01

Q31

Q30

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__ __ __ __ __ __ Patient Study Number 3: ART Regimen NO. QUESTIONS AND FILTERS CODING CATEGORY S

KIP TO

ANSWER

30. What was the reason for discontinuation of second ART regimen? N.B. Adverse reactions include: nausea/ vomiting, diarrhea, headache, fever, rash, peripheral neuropathy, hepatitis, jaundice, dementia, anemia, pancreatitis, CNS adverse event, other adverse event

Starting TB treatment 01 Adverse reactions (see list) 02 Treatment failure clinical 03 Treatment failure immunological 04 Poor adherence 05 Patient decision 06 Pregnancy 07 End of PMTCT 08 Stock out 09 Other, specify _____________ 66 Not recorded 555

31. Record start date of THIRD ART treatment prescribed at this facility.

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

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__ __ __ __ __ __ Patient Study Number 3: ART Regimen NO. QUESTIONS AND FILTERS CODING CATEGORY SKIP

TO ANSWER

32. Record THIRD ART prescribed at the facility: First look for fixed dose combinations (FDC). FDC are a combination of drugs in one pill/ tablet/ capsule. - Triple combination means

there are three drugs in one pill, such as “D4T(3), 3TC, NVP”.

- Double combination means there are two drugs in one pill, such as “Combivir” (AZT/3TC).

Find and circle the correct FDC. If a FDC is not available, circle each single ARV drug in regimen. If ARV is not listed in the table, record the name of the drug under x) Others (Specify).

DRUG NAME Triple combination: three drugs combined in one pill a) d4T (30), 3TC, NVP

b) d4T(40), 3TC, NVP

c) AZT (ZDV), 3TC, NVP

d) TDF, FTC, EFV

e) AZT (ZDV), 3TC, ABC

Double combination: two drugs combined in one pill (including boosted PIs) f) AZT (ZDV), 3TC

g) TDF, FTC

h) LPV, RTV

Single antiretroviral drug i) AZT (Zidovudine/

ZDV) j) ddI (Didanosine)

k) d4T (Stavudine)

l) 3TC (Lamivudine)

m) ABC (Abacavir)

n) NVP (Nevirapine)

o) EFV (Efavirenz)

p) IDV (Indinavir)

q) NFV (Nelfinavir)

r) SQV (Saquinavir)

s) RTV (Ritonavir)

t) FTC (Emtricitabine)

u) TDF (Tenofovir) v) Others? (Specify)

____________________

33. Record stop date of third ART. [__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

34. Has ART regimen changed since third prescription?

No 00 Yes 01

Q36 Q35

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__ __ __ __ __ __ Patient Study Number 3: ART Regimen NO. QUESTIONS AND

FILTERS CODING CATEGORY SKIP

TO ANSWER

35. What was the reason for discontinuation of second ART regimen? N.B. Adverse reactions include: nausea/ vomiting, diarrhea, headache, fever, rash, peripheral neuropathy, hepatitis, jaundice, dementia, anemia, pancreatitis, CNS adverse event, other adverse event

Starting TB treatment 01 Adverse reactions (see list) 02 Treatment failure clinical 03 Treatment failure immunological 04 Poor adherence 05 Patient decision 06 Pregnancy 07 End of PMTCT 08 Stock out 09 Other, specify _____________ 66 Not recorded 555

129

Patient Study Number __________________________________ Section 4: Clinical Characteristics NO. QUESTIONS AND FILTERS CODING CATEGORY SKIP

TO ANSWER

36. Record date of last clinic visit [__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

37. Record patient weight at ART treatment initiation.

[__ __ __ ] kg Not recorded 555

38. Record patient weight at last clinic visit.

[__ __ __ ] kg Not recorded 555

39. Record patient’s functional status at last clinic visit.

Working 01 Ambulatory 02 Bedridden 03 Not recorded 555

40. Record patient’s WHO stage at ART treatment initiation.

Stage 1 01 Stage 2 02 Stage 3 03 Stage 4 04 Not recorded 555

41. Record patient’s WHO stage at last clinic visit.

Stage 1 01 Stage 2 02 Stage 3 03 Stage 4 04 Not recorded 555

42. Was patient receiving CTX prophylaxis at the last clinic visit?

No 00 Yes 01 Not recorded 555

43. Was patient on INH prophylaxis for TB, active TB treatment, or no treatment at all at last clinic visit?

On INH prophylaxis for TB 01 On active TB treatment 02 Not on treatment at all 03 Not recorded 555

44. Has patient been exposed to nevirapine for prevention of mother-to-child transmission of HIV?

No 00 Yes 01 Not applicable (if male) 444 Not recorded 555

45. Was patient ever pregnant while on ART treatment?

No 00 Yes 01 Not applicable (if male) 444 Not recorded 555

46. Was patient pregnant at last clinic visit?

No 00 Yes 01 Not applicable (if male) 444 Not recorded 555

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__ __ __ __ __ __ Patient Study Number Section 4: Clinical Characteristics NO. QUESTIONS AND FILTERS CODING CATEGORY

46.

Record whether there was an active disease 1) before ART initiation (date before Q21), during ART treatment, and 3) at the last clinic visit (date Q36). Circle 01 for ‘yes’ and 02 for ‘no’. Circle 555 for ‘not recorded’. Step 1: a) Find ART initiation date (Q21): [__ __| __ __| __ __] DD MM YY b) Find last clinic visit date (Q36): [__ __| __ __| __ __] DD MM YY Step 2: Record active disease before ART initiation (Step 1-a). Step 3: Record active disease during ART treatment. This is any active disease occurring between ART initiation date (Step 1-a) and last clinic visit date (Step 1-b). Step 4: Record active disease at last clinic visit (Step 1-b).

Stage Defining Condition Before ART initiation

During ART treatment

At last clinic visit

Yes No Yes No Yes No a) Chronic diarrhoea > 1 month 01 00 01 00 01 00 b) Oral candidiasis 01 00 01 00 01 00 c) Oral hairy leukoplakia 01 00 01 00 01 00 d) Pulmonary tuberculosis 01 00 01 00 01 00 e) Several bacterial infections 01 00 01 00 01 00 f) Unexplained prolonged fever > 1 month 01 00 01 00 01 00 g) Weight loss greater of equal to 10% 01 00 01 00 01 00 h) Atypical mycobacteriosis, disseminated or

pulmonary 01 00 01 00 01 00

i) Candidiasis of oesophagus trachea/ bronchi 01 00 01 00 01 00 j) Cryptococcosis, extrapulmonary 01 00 01 00 01 00 k) Crytosporidiosis with diarrhoea > 1 month 01 00 01 00 01 00 l) Cytomegalovirus disease 01 00 01 00 01 00 m) Extrapulmonary tuberculosis 01 00 01 00 01 00 n) Herpes simplex infection, mucocutaneous/ visceral 01 00 01 00 01 00 o) HIV encephalopathy 01 00 01 00 01 00 p) Kaposi’s sarcoma 01 00 01 00 01 00 q) Lymphoma 01 00 01 00 01 00 r) Non-typhoid Salmonella septicaemia 01 00 01 00 01 00 s) Pneumocystis carinii pneumonia 01 00 01 00 01 00 t) Progressive, multifocal leukoencephalopathy 01 00 01 00 01 00 u) Toxoplasmosis of the brain 01 00 01 00 01 00 v) Wasting syndrome 01 00 01 00 01 00 w) Disseminated mycosis 01 00 01 00 01 00 x) Not recorded 555 555 555

__ __ __ __ __ __ Patient Study Number 4: Clinical Characteristics NO. QUESTIONS AND

FILTERS CODING CATEGORY

SKIP TO

ANSWER

47. Was patient transferred out?

No 00 Yes 01 Not recorded 555

Q50

Q48

Q50

48. Record transfer out date [__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

49. Where was patient transferred to?

HBC 01 Palliative care 02 PMTCT 03 PLHA support group/ club 04 OVC group 05 TB 06 Medical speciality 07 Nutritional support 08 Legal 09 Another ART clinic 10 Hospital 11 Other, specify ____________ 66 Not recorded 555

50. Did patient die? No 00 Yes 01 Not recorded 555

Q53

Q51

Q53

51. Record date of death [__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

52. Record cause of death Malignancy 01 Tuberculosis 02 Other OI 03 Other, specify ____________ 66 Not recorded 555

132

Patient Study Number _________________________________ Section 4 Test Results NO. QUESTIONS AND

FILTERS CODING CATEGORY SKIP

TO ANSWER

53. Pre-treatment CD4 count. [__ __ __ __ ] Not recorded 555

Q54 Q55

54. Date of pre-treatment CD4 count

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

55. Most recent CD4 count

[__ __ __ __ ] Not recorded 555

Q56 Q57

56. Date of most recent CD4 count

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

57. Lowest ever CD4 count

[__ __ __ __ ] Not recorded 555

Q58 Q59

58. Date of lowest ever CD4 count

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

59. Pre-treatment viral load test (where available)

[__ __ __ __ ] Not recorded 555

Q60 Q61

60. Date of pre-treatment viral load test (where available)

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

61. Most recent viral load test (where available)

[__ __ __ __ ] Not recorded 555

Q62 Q63

62. Date of most recent viral load test (where available)

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

63. Pre-treatment total lymphocyte count

[__ __ __ __ ] Not recorded 555

Q64 Q65

64. Date of pre-treatment total lymphocyte count

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

65. End time of data collection __ __ : __ __ [Hour: minute]

END

133

RETENTION IN ART PROGRAMS IN POST-CONFLICT NORTHERN UGANDA

Form 2 Pharmacy Logbook Patient Study Number Section 1 Interview Information NO. QUESTIONS AND FILTERS CODING CATEGORY SKIP

TO ANSWER

1. Questionnaire Identification Number

Clinical records 01 Laboratory register 02 Pharmacy logbook 03

2. Site Identification Number [Codes to be listed] 3. Interviewer code [Codes to be listed] 4. Data entry staff 1 initial

5. Data entry staff 2 initial

6. Interview date [__ __ | __ __ | __ __ ] DD MM YY

7. Record patient unique ART ID number

8. Record patient health facility file number

9. Record study participant ID number. Record patient study number of every page of questionnaire.

10. Record patient’s sex from Form 1 Section 2 Q11

Male 01 Female 02

11. Record patient’s date of birth from Section 2 Form 1 Q12

[__ __ | __ __ | __ __ ] DD MM YY

12. Start time of data collection __ __ : __ __ [Hour: minute]

Section 2 Verify Respondent NO. QUESTIONS AND FILTERS CODING CATEGORY SKIP TO ANSWER 13. Record Sex

Verify that sex is same as respondent in cross-sectional questionnaire (Q11)

Male 01 Female 02

14. Record month and year of respondent’s birth Verify that month and year of birth are same as respondent in cross-section questionnaire (Q12)

[__ __] in completed month Don’t know 777 [__ __ __ __ ] in completed year Don’t know 777

134

Patient Study Number Section 3: ART Regimen

NO. QUESTIONS AND FILTERS

CODING CATEGORY SKIP TO

ANSWER

15. Record start date of FIRST ART dispensed at this facility.

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

16. Record FIRST ART dispensed at the facility: First look for fixed dose combinations (FDC). FDC are a combination of drugs in one pill/ tablet/ capsule. - Triple

combination means there are three drugs in one pill, such as “D4T (30), 3TC, NVP”.

- Double combination means there are two drugs in one pill, such as “Combivir” (AZT/3TC).

Find and circle the correct FDC. If a FDC is not available, circle each single ARV drug in regimen. If ARV is not listed in the table, record the name of the drug under x) Others (Specify).

DRUG NAME Triple combination: three drugs combined in one pill a) d4T (30), 3TC, NVP b) d4T(40), 3TC, NVP c) AZT (ZDV), 3TC, NVP d) TDF, FTC, EFV e) AZT (ZDV), 3TC, ABC Double combination: two drugs combined in one pill (including boosted PIs) f) AZT (ZDV), 3TC g) TDF, FTC h) LPV, RTV Single antiretroviral drug i) AZT (Zidovudine/

ZDV) j) ddI (Didanosine) k) d4T (Stavudine) l) 3TC (Lamivudine) m) ABC (Abacavir) n) NVP (Nevirapine) o) EFV (Efavirenz) p) IDV (Indinavir) q) NFV (Nelfinavir) r) SQV (Saquinavir) s) RTV (Ritonavir) t) FTC (Emtricitabine) u) TDF (Tenofovir) v) Others? (Specify)

___________________

135

Patient Study Number Section 3: ART Regimen

NO. QUESTIONS AND FILTERS

CODING CATEGORY

SKIP TO

ANSWER

17. Record date of last refill for first ART regimen.

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

18. Has ART regimen changed since first ART dispensed?

No 00 Yes 01

Q18

Q17

19. What was the reason for discontinuation of first ART regimen? N.B. Adverse reactions include: nausea/ vomiting, diarrhea, headache, fever, rash, peripheral neuropathy, hepatitis, jaundice, dementia, anemia, pancreatitis, CNS adverse events, other adverse events

Starting TB treatment 01 Adverse reactions (see list) 02 Treatment failure clinical 03 Treatment failure immunological 04 Poor adherence 05 Patient decision 06 Pregnancy 07 End of PMTCT 08 Stock out 09 Other, specify _____________ 66 Not recorded 555

20. Record start date of SECOND ART dispensed at this facility.

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

136

Patient Study Number Section 3: ART Regimen NO. QUESTIONS AND FILTERS CODING CATEGORY SKIP

TO ANSWER

21. Record SECOND ART dispensed at the facility: First look for fixed dose combinations (FDC). FDC are a combination of drugs in one pill/ tablet/ capsule. - Triple combination means

there are three drugs in one pill, such as “D4T(30), 3TC, NVP”.

- Double combination means there are two drugs in one pill, such as “Combivir” (AZT/3TC).

Find and circle the correct FDC. If a FDC is not available, circle each single ARV drug in regimen. If ARV is not listed in the table, record the name of the drug under x) Others (Specify).

DRUG NAME Triple combination: three drugs combined in one pill a) d4T (30), 3TC, NVP

b) d4T(40), 3TC, NVP c) AZT (ZDV), 3TC,

NVP d) TDF, FTC, EFV e) AZT (ZDV), 3TC,

ABC Double combination: two drugs combined in one pill (including boosted PIs) f) AZT (ZDV), 3TC

g) TDF, FTC

h) LPV, RTV

Single antiretroviral drug i) AZT (Zidovudine/

ZDV) j) ddI (Didanosine)

k) d4T (Stavudine)

l) 3TC (Lamivudine)

m) ABC (Abacavir)

n) NVP (Nevirapine)

o) EFV (Efavirenz)

p) IDV (Indinavir)

q) NFV (Nelfinavir)

r) SQV (Saquinavir)

s) RTV (Ritonavir)

t) FTC (Emtricitabine)

u) TDF (Tenofovir) v) Others? (Specify)

____________________

22. Record date of last refill of second ART.

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

137

Patient Study Number Section 3: ART Regimen NO. QUESTIONS AND

FILTERS CODING CATEGORY SKIP

TO ANSWER

23. Has ART regimen changed since second ART dispensed?

No 00 Yes 01

Q23 Q22

24. What was the reason for discontinuation of second ART regimen? N.B. Adverse reactions include: nausea/ vomiting, diarrhea, headache, fever, rash, peripheral neuropathy, hepatitis, jaundice, dementia, anemia, pancreatitis, CNS adverse event, other adverse event

Starting TB treatment 01 Adverse reactions (see list) 02 Treatment failure clinical 03 Treatment failure immunological 04 Poor adherence 05 Patient decision 06 Pregnancy 07 End of PMTCT 08 Stock out 09 Other, specify _____________ 66 Not recorded 555

25. Record start date of THIRD ART dispensed at this facility.

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

138

__ __ __ __ __ __ Patient Study Number Section 3: ART Regimen NO. QUESTIONS AND

FILTERS CODING CATEGORY SKIP

TO ANSWER

26. Record THIRD ART dispensed at the facility: First look for fixed dose combinations (FDC). FDC are a combination of drugs in one pill/ tablet/ capsule. - Triple combination

means there are three drugs in one pill, such as “D4T (30), 3TC, NVP”.

- Double combination means there are two drugs in one pill, such as “Combivir” (AZT/3TC).

Find and circle the correct FDC. If a FDC is not available, circle each single ARV drug in regimen. If ARV is not listed in the table, record the name of the drug under x) Others (Specify).

DRUG NAME Triple combination: three drugs combined in one pill a) d4T (30), 3TC, NVP

b) d4T(40), 3TC, NVP

c) AZT (ZDV), 3TC, NVP

d) TDF, FTC, EFV

e) AZT (ZDV), 3TC, ABC Double combination: two drugs combined in one pill (including boosted PIs) f) AZT (ZDV), 3TC

g) TDF, FTC

h) LPV, RTV

Single antiretroviral drug

i) AZT (Zidovudine/ ZDV)

j) ddI (Didanosine)

k) d4T (Stavudine)

l) 3TC (Lamivudine)

m) ABC (Abacavir)

n) NVP (Nevirapine)

o) EFV (Efavirenz)

p) IDV (Indinavir)

q) NFV (Nelfinavir)

r) SQV (Saquinavir)

s) RTV (Ritonavir)

t) FTC (Emtricitabine)

u) TDF (Tenofovir) v) Others? (Specify)

____________________

27. Record date of last refill for third ART.

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

139

__ __ __ __ __ __ Patient Study Number Section 3: ART Regimen NO. QUESTIONS AND

FILTERS CODING CATEGORY

SKIP TO

ANSWER

28. Has ART regimen changed since third ART dispensed?

No 00 Yes 01

Q28

Q27

29. What was the reason for discontinuation of second ART regimen? N.B. Adverse reactions include: nausea/ vomiting, diarrhea, headache, fever, rash, peripheral neuropathy, hepatitis, jaundice, dementia, anemia, pancreatitis, CNS adverse event, other adverse event

Starting TB treatment 01 Adverse reactions (see list) 02 Treatment failure clinical 03 Treatment failure immunological 04 Poor adherence 05 Patient decision 06 Pregnancy 07 End of PMTCT 08 Stock out 09 Other, specify _____________ 66 Not recorded 555

140

__ __ __ __ __ __ Patient Study Number Section 4 ARV Refill History NO. QUESTIONS

AND FILTERS CODING CATEGORY SKIP TO ANSWER

30. Record date of last refill for the current ART dispensed.

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

31. Record date of last prescription/ refill (whether or not it is ART)

[__ __ | __ __ | __ __ ] DD MM YY Not recorded 555

Record ARV, dosage, refill visit dates and the number of pills dispensed for each refill from six months ago.

32. Record date: [__ __| __ __ | __ __ ] DD MM YY Not recorded 555

ARV drug name

ARV dosage (mg)

# of pills dispensed

# of pills returned

1 2 3

33. Record date: [__ __| __ __ | __ __ ] DD MM YY Not recorded 555

ARV drug name

ARV dosage (mg)

# of pills dispensed

# of pills returned

1 2 3

34. Record date: [__ __| __ __ | __ __ ] DD MM YY Not recorded 555

ARV drug name

ARV dosage (mg)

# of pills dispensed

# of pills returned

1 2 3

35. Record date: [__ __| __ __ | __ __ ] DD MM YY Not recorded 555

ARV drug name

ARV dosage (mg)

# of pills dispensed

# of pills returned

1 2 3

36. Record date: [__ __| __ __ | __ __ ] DD MM YY Not recorded 555

ARV drug name

ARV dosage (mg)

# of pills dispensed

# of pills returned

1 2 3

37. Record date: [__ __| __ __ | __ __ ] DD MM YY Not recorded 555

ARV drug name

ARV dosage (mg)

# of pills dispensed

# of pills returned

1 2 3

38. End time of data collection

__ __ : __ __ [Hour: minute]

141

RETENTION IN ART PROGRAMS IN POST-CONFLICT NORTHERN UGANDA Form 3 Data Management Form DATA MANAGEMENT – To be completed by the Principal investigator.

NO. QUESTION AND FILTERS CODING CATEGORY SKIP TO

1. Form 1 Clinical Record Result

Completed 01 Partially completed 02 Other (specify) 03

2. Form 2 Pharmacy Logbook Result

Completed 01 Partially completed 02 Other (specify) 03

3. Form 3 Laboratory Register Result

Completed 01 Partially completed 02 Other (specify) 03

4. Checked by Supervisor

Signature_______________________________ [__ __| __ __| __ __] DD MM YY

Ready for

data entry

142

Health Unit InCharge (ART Clinic Manager) Key Informant interview form

Section 1: Interview Information No. Questions and Filters Coding Category Skip To Answer 1. Site Identification Number [codes to be listed] 2. Interviewer Code [codes to be listed] 3. Data entry staff 1 initial 4. Data entry staff 2 initial 5. Date of Interview (DD/MM/YY) [__ __ | __ __ | __ __ ]

DD MM YY

6. Start time of interview __ __ : __ __ [Hour: minute]

Section 2: General Information on Facility No. Questions and Filters Coding Category Skip To Answer 7. Position of persons interviewed

Write exact name of job title for each person who provided information.

8. Name of health facility [codes to be listed] 9. Level of health facility

Regional Referral Hospital 01 District based Hospital 02 Primary Health Centre 03 Private Clinic 04 Other, specify __________ 66

10. Type of health facility

Government 01 Mission facility supported by govt 02 Mission facility NOT supported by the government 03 Private for profit 04 NGO (non-religious) 05 Other, specify __________ 06

Hello, my name is ___________________. I am here as part of a research team conducting a study ART delivery, adherence and retention of patients in ART programs in a post-conflict setting. This research is being conducted by Northern Uganda Malaria, AIDS and Tuberculosis program (NUMAT) and USAID, with permission from Ministry of Health/ DDHS. We want to see if patient retention and adherence are different or the same across different levels and models of ART programs in a post-conflict situation. As the person in charge of the ART services in this facility we would like to ask you questions such as your workload, the activities in the clinic and follow up in the community. All the questions will be about your program. Your contribution is important and will help the country to better understand ART services experiences in retaining patients and supporting adherence in post-conflict settings. Do you have any questions or concerns about the study? May I start the interview? YES _______ (please check) Thank you for agreeing to participate. (Continue below) NO _______ (please put a cross here and stop). Thank you for your time. Is there another person or organization you think we should talk to instead? _______________________________________.

143

Section 3: HIV/AIDS Care No. Questions and Filters Coding Category Skip To Answer 11. What days and hours of

the week does the HIV Clinic operate? Mark all that apply.

Monday [hours]__________ 01 Tuesday [hours]__________ 02 Wednesday [hours] _________ 03 Thursday [hours]_________ 04 Friday [hours]__________ 05 Saturday [hours]_________ 06 Sunday [hours]__________ 07

12. What type of staff provide direct HIV care and treatment on a typical HIV clinic day Read all options and ask how many for each type of staff.

Number

a. Medical doctor/officer

b. Clinical officer c. Nurse/Midwife (enrolled and registered)

d. Nurse attendants e. Nutritionist f. Social workers g. Lay ART support workers (non medically trained, based primarily in the clinic, but not on the formal pay roll)

h. Others, specify

13. How many hours on average do medical doctors/officer spend at the HIV clinic during a typical HIV clinic day?

[___________] hours

14. How many hours on average do clinical officers spend at the HIV clinic during a typical HIV clinic day?

[___________] hours

15. How many staff are designated to provide the following services on a typical HIV clinic day?

Number a. Registration b. Triage c. Adherence counseling (define)

d. Clinical services e. ART prescription f. Phlebotomy g. ART dispenser (dispensing in HIV clinic)

h. Follow-up on missed appointments and defaulting

i. Referral services j. Data management

k. Other (specify) _________________

144

Section 3: HIV/AIDS Care continued No.

Questions and Filters Coding Category Skip To

Answer

16. Please tell me if the following HIV care and prevention services are provided at this facility? (not just at the HIV clinic but at the larger facility) Do not mark service if clients are referred to an external facility. Read all options out loud

YES

NO

HIV counselling and testing 01

Diagnostic HIV testing 02 Adult ART 03 Paediatric ART 04 Paediatric HIV care no ART 05

OI Prophylaxis 06 Management of OI 07 Cotromoxazole prophylaxis 08

TB testing 09

TB prophylaxis (INH) 10 TB treatment 11 Laboratory testing 12 Treatment of STI 13 PMTCT services 14 Palliative care (management of distressing emotional, mental, spiritual, or physical symptoms and end of life care at the clinic or in the home) 15

Nutritional supplementation 16

Nutritional education/advice 17

Family planning services 18 Prevention with positives 19 PEP 20

Please also tell me if the following adherence related services have ever been provided by the HIV clinic. If yes, when did the HIV clinic start providing the service and when was the service stopped if it has stopped?

145

17. Yes/NO Start date End Date ART adherence counselling by health care staff 01

No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

ART adherence counselling by lay workers (e.g., Adherence support workers) 02

No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

Prevention for positives (discussing safe sex, family planning and disclosure) 03

No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

PLHA support groups 04 No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

Out reach Home-based care 05 No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

Referral for community services 06 No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

Other, specify _____________ 66 No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

Section 3: HIV/AIDS Care No. Questions and Filters Coding Category Skip To Answer 18. How often in the past 6

months did a supervisor from outside of the facility (such as MOH officers) observe clinical practices at the HIV clinic?

[____________________]

19. Do the clinicians (doctors) in the HIV clinic have formal mentors who are experienced in ART and respond to questions, reviews clinical cases, provides feedback and assists in case management?

No 00 Yes 01

20. Are patient case conference reviews done at the HIV clinic?

No 00 Yes 01

146

Section 4: HIV/ART Patients No. Questions and

Filters Coding Category Skip To Answer

21. How many registered adult HIV care patients has this HIV clinic ever had? Fill in table. How many are male, how many are female?

ADULT EVER Males Females Total

22. How many current HIV positive adults are registered with the HIV clinic? Fill in table. How many are male, how many are female?

ADULT CURRENT

Males Females Total

23. How many children (age 14 or younger) have EVER been registered at this HIV clinic?

CHILDREN EVER Males Females Total

24. How many current HIV positive children are registered with the HIV clinic?

CHILDREN CURRENT

Males Females Total

25. How many adult patient visits were made at the HIV clinic during the past month?

[ __ __ __ __ __ __ ] clients

26. How many child patient visits were made at the HIV clinic during the past month?

[ __ __ __ __ __ __ ] clients

27. How many adult patients does the HIV clinic see on a typical clinical day?

[ __ __ __ __ __ __ ] clients

147

Section 4: HIV/ART Patients No. Questions and Filters Coding Category Skip

To Answer

28. Does the HIV clinic limit the number of people seen for HIV care during a typical clinic day?

No 00 Yes 01

29. How many clients may the HIV clinic see on a typical day?

[ __ __ __ __ __ __ ] clients

30. How often does the clinic have to turn away HIV patients who are seeking care during clinic hours on a typical HIV clinic day?

Never 00 Occasionally 01 Most of the time 00 Always 01

Section 4: HIV/ART Patients No. Questions and Filters Coding Category Skip To Answer 31. During a typical HIV

clinic day what proportion of adult visits are scheduled visits by appointment

[ __ __ . __ ] proportion of visits that are scheduled

32. Among HIV adult patients enrolled, how many are receiving ARV drugs? Fill in table. How many are male, how many are female?

Males Females Total

33. How many HIV patients are initiated on ARV drugs on a typical clinic day?

[ __ __ __ __ __ __ ] clients

34. How often are patients expected to refill their ARV drugs during the first month of treatment? Record one response only.

Every week 01 Every two weeks 02 Once a month 03 Other, specify ___66

35. How often are patients expected to refill their ARV drugs between the 2nd and 6th month of treatment (not including the first month)? Record one response only.

Every two weeks 01 Monthly 02 Every two months 03 Other, specify 66

36. How often are patients expected to refill their ARV drugs after completing the first six months of treatment? Record one response only.

Every two weeks 01 Monthly 02 Every two months 03 Other, specify 66

148

Section 5: ART Services No. Questions and Filters Coding Category Skip To Answer 37. When did this facility

start providing ART services? Record month and year.

[__ __ | __ __ ] MM YY

38. What is/are the source of support for the ART? Fill in table using coding categories provided below. First record current sources of support more than one possible. Next, record sources of support ever received.

Current:

Source Kinds of support 28a. 28b. 28c. 28d.

Ever:

Source Kinds of support 28e. 28f. 28g. 28h.

Sources of Support Kinds of support 01 Government supported 01 ARV drugs 02 list country specific external organizations

02 OI drugs, including TB

03 Global Fund 03 Infrastructural (buildings, furnishings)

04 Research/ University 04 Laboratory equipment/ reagents

05 Private foundation 05 Pharmacy (security, computers, refrigerators, storage cabinets)

06 Mission 05 Medical supplies (gloves disinfectants, protective equipment)

66 Other, specify ______________

06 ART related training

Categories to be determined (i.e. DFID, other National organizations etc)

07 Technical assistance (specify) _____ (e.g. IEC materials, QA/QI activities) 07 Human resources (salaries, positions)

66 Other, specify __________

149

Section 5: ART Services No.

Questions and Filters Coding Category Skip To

Answer

39. What are the first line ART regimens available in this facility?

AZT based regimens 01 D4T based regimens 02 NVP based regimens 03 EFV based regimens 04 Tenofovir based regiments 05 [site specific options to be added] 06

40. What are the second line ART regimens available in this facility?

[site specific options to be added]

41. How many ART patients are on second line regimen?

[_______________] patients

42. If a patient needed to switch to a second line regimen, are those drugs available?

No 00 Yes 01

43. How is eligibility for ARV treatment defined at this HIV clinic? (Mark all that apply)

CD4 cell count 01 WHO clinical stage 03 Other, specify ___________66

44. Is this eligibility criteria based on one of the following guidelines

National guidelines 01 WHO guidelines 02 Other international guidelines (specify)_______ 66 None of the above 03

45. How long on average do HIV patients have to wait to determine eligibility for ART?

[_______] days

46. What are the top three reasons they wait? (Read options) Patient decision 01 Patient load at clinic 02 CD4 cell count not available 03 Transport issues for patients (not able to come to the clinic) 04 Patient has TB 05 Patient has other OI 06 Other (specify) _______ 66

Reason 1: _________ Reason 2: __________ Reason 3: __________

150

Section 5: ART Services No. Questions and Filters Coding Category Skip

To Answer

47. How long on average do eligible patients wait to start ARV drugs?

[_______] days

48. What are the top three reasons they wait? (Read options) Patient decision 01 ARV drugs not available 02 Patient needs more adherence preparation sessions 03 Transport issues for patients (not able to come to the clinic) 04 Patients have TB 05 Patients have other OI 06 Other (specify) ____________ 66

Reason 1: _________ Reason 2: __________ Reason 3: __________

49. Do clinics keep track of patients who are eligible but have not yet started ART?

No 00 Yes 01

50. How many eligible patients are currently waiting to start ART?

[_______________] patients

51. Are any of the following ARV treatment tools used at the clinic?

YES NO

SOPS 01

Wall Posters 02

Desk aides 03

Checklists 04 Other specify_66

151

Section 6: ART Service Costs No. Questions and

Filters Coding Category Skip To Answer

52. Do patients pay for any HIV-related services in this facility?

No 00 Yes 01

53. What is the average cost of these services provided at this facility or through a referral to another facility? Fill in table. Record average cost in standard currency.

Services Cost of services provided at facility

Cost of referral facility services

a. Registration b. Consultation fees c. HIV test d. ARV drugs e. Cotrimoxazole prophylaxis f. Other O.I. drugs g. X-ray film______________ h. Other services/ supplies,

specify ________

i. Viral load test j. CD4 t-cell count test k. Other laboratory tests,

specify

Section 7: ART Lab and Pharmacy Services No. Questions and

Filters Coding Category Skip

To Answer

54. Does this facility perform laboratory tests related to ART?

No 00 Yes 01

Q54

Q53

55. What laboratory tests for ART does this facility perform (on site)? Mark all that apply.

YES NO CD4 count 01

Total lymphocyte count 02

Viral load 03 Liver function 04 Renal function tests 05 White blood cell count and differential 06

Haemoglobin/Haematocrit 07

Other (specify_______)66

56. For tests not performed on site, where are the tests performed?

Provincial hospital 01 Other (specify) _____________ 66

57. How do patients access lab services that are not performed on site?

Patient must go to lab 01 Specimen referral system in place 02 Other (specify) __________________ 66

152

Section 7: ART Lab and Pharmacy Services No.

Questions and Filters

Coding Category Skip To Answer

58. Which of the following tests are done pre-treatment or after ART initiation to assess the clinical progress of ART clients and how often? Read list. Ask whether test is performed for pre-treatment and after ART initiation.

Pre-treatment After ART initiation a. CD4 No 00

Yes 01

Not performed 01 Every 3 months 02 Every 6 months 03 Every 12 months 04 Other_____05

b. Viral load No 00 Yes 01

Not performed 01 Every 3 months 02 Every 6 months 03 Every 12 months 04 Other_____05

c. Total Lymphocyte No 00 Yes 01

Not performed 01 Every 3 months 02 Every 6 months 03 Every 12 months 04 Other_____05

d. Liver function No 00 Yes 01

Not performed 01 Every 3 months 02 Every 6 months 03 Every 12 months 04 Other_____05

e. Renal function No 00 Yes 01

Not performed 01 Every 3 months 02 Every 6 months 03 Every 12 months 04 Other_____05

f. WBC differential No 00 Yes 01

Not performed 01 Every 3 months 02 Every 6 months 03 Every 12 months 04 Other_____05

g. Haemoglobin/ Haematocrit

No 00 Yes 01

Not performed 01 Every 3 months 02 Every 6 months 03 Every 12 months 04 Other_____05

59. Are ARV drugs dispensed at this facility?

No 00 Yes 01

Q67 Q58

60. Where are the ARV drugs dispensed? (mark all that apply)

Facility pharmacy 00 HIV clinic 01 Other (specify) _________________66

Q59 Q60

61. How many people in the pharmacy on a typical day are available for dispensing ARV drugs?

[_______________] number of dispensing agents

153

Section 7: ART Lab and Pharmacy Services No.

Questions and Filters

Coding Category Skip To

Answer

62. Has there ever been a stock-out of ARV drugs?

No 00 Yes 01

Q63

Q61

63. In the past six months how often have ARV drugs been out of stock?

Zero times 01 One time 02 Two times 03 Three times 04 Four times 05 Other, specify __________ 66

64. What is the longest number of days during the past six months that any ARV drug has been out of stock?

[ ______________ ] days

65. Does the pharmacy dispense Cotrimoxazole?

No 00 Yes 01

Q67

Q64

66. Have you ever had a stock-out of Cotrimoxazole?

No 00 Yes 01

Q67

Q65

67. In the past six months how often have Cotrimoxazole been out of stock?

Zero times 01 One time 02 Two times 03 Three times 04 Four times 05 Other, specify __________ 66

68. What is the longest number of days in the last six past months that Cotrimoxazole was out of stock?

[______________] days

154

Section 8: Adherence No. Questions

and Filters Coding Category Skip

To Answer

Now I will ask you some questions about how this program addresses adherence issues:

69. Are there any adherence guidelines or formal documents (e.g. SOP) that you follow in this health facility?

No 00 Yes 01

Q69

Q68

70. What guidelines or formal documents do you follow? Record name of guideline. If there is a guideline, circle either yes, observed or yes, reported but not seen.

Record name of guideline/formal documents: ____________________________________1. Yes, observed 01 Yes, reported not seen 02 ___________________________________ 2 Yes, observed 01 Yes, reported not seen 02 __________________________________ 3. Yes, observed 01 Yes, reported not seen 02

155

Section 8: Adherence No. Questions and

Filters Coding Category Answer

71. Who counsels patients about adherence to ART here? If yes, are they trained on ART counselling? Mark all that apply.

Provide ART counselling

Trained on ART counselling

a. Medical doctor/officer

b. Clinical officer c. Nurse/Midwife (enrolled and registered)

d. Treatment Nurse/ adherence counsellors

e. Nurse attendants f. Lab staff g. Pharmacy staff h. Nutritionist i. Social workers j. Lay ART support workers (non medically trained, based primarily in the clinic e.g. PLHA, HBC volunteer, not on formal pay roll)

k. Others, specify

72. Are any of the following ARV adherence tools used at the clinic?

YES NO SOPS 01

Wall Posters 02 Desk aides 03 Checklists 04 Other (specify____)66

73. Do you offer the following? Record whether the counselling is always, sometimes, or never offered.

Always Sometimes Never a. Pre-ARV medication counselling

b. Follow-up counselling to discuss adherence to ARV medicines

74. In general, how many counselling sessions do clients undergo prior to starting ART?

[__ __ ] times 777 Don’t know

75. How is counselling offered? Mark all that apply.

Individually 01 With a buddy or treatment supporter 02 As part of a group (ART patients only) 03 Other (specify) _______________________________ 66

156

Section 8: Adherence No. Questions and Filters Coding Category Answer 76. How often is adherence assessed during the following visits and how is it assessed?

How often How adherence is assessed (mark all that apply)

Where adherence data is recorded (mark all that apply)

a. Preparedness visits for taking ARV drugs

Always 01 Sometimes 02 Never 03

Patient self-report barriers 01 Health care provider judgment 02 Standardized checklist 03 Other or past prescription behaviour 04 Other, specify ______66

General OPD register with HIV/AIDS and non HIV/AIDS clients 01 Patient card Specific register for HIV/AIDS clients 02 Specific register only for ART clients 03 Individual client chart/medical record 04 No record kept 05 Other, specify ______66

b. Months 1-6 of ARV drugs

Always 01 Sometimes 02 Never 03

Patient self-report 01 Pharmacy Pill count 02 Clinic-based pill count 03 Health care provider judgment 04 Electronic pill cap count 05 Standardized checklist 06 Other, specify ______66

General OPD register with HIV/AIDS and non HIV/AIDS clients 01 Patient card Specific register for HIV/AIDS clients 02 Specific register only for ART clients 03 Individual client chart/medical record 04 No record kept 05 Other, specify ______66

c. After 6 months of ARV drug treatment

Always 01 Sometimes 02 Never 03

Patient self-report 01 Pharmacy Pill count 02 Clinic-based pill count 03 Health care provider judgment 04 Electronic pill cap count 05 Standardized checklist 06 Other, specify ______66

General OPD register with HIV/AIDS and non HIV/AIDS clients 01 Patient card Specific register for HIV/AIDS clients 02 Specific register only for ART clients 03 Individual client chart/medical record 04 No record kept 05 Other, specify ______66

d. When patient has missed an appointment?

Always 01 Sometimes 02 Never 03

Patient self-report 01 Pharmacy Pill count 02 Clinic-based pill count 03 Health care provider judgment 04 Electronic pill cap count 05 Standardized checklist 06 Other, specify ______66

General OPD register with HIV/AIDS and non HIV/AIDS clients 01 Patient card Specific register for HIV/AIDS clients 02 Specific register only for ART clients 03 Individual client chart/medical record 04 No record kept 05 Other, specify ______66

e. When patient has an opportunistic infection

Always 01 Sometimes 02 Never 03

Patient self-report 01 Pharmacy Pill count 02 Clinic-based pill count 03 Health care provider judgment 04 Electronic pill cap count 05 Standardized checklist 06 Other, specify ______66

General OPD register with HIV/AIDS and non HIV/AIDS clients 01 Patient card Specific register for HIV/AIDS clients 02 Specific register only for ART clients 03 Individual client chart/medical record 04 No record kept 05 Other, specify ______66

157

Section 8: Adherence No.

Questions and Filters

Coding Category Skip To

Answer

77. Is adherence assessed for each ART client at every refill visit by the pharmacist/ dispenser?

No 00 Yes 01

Q77

Q76

78. How is adherence assessed by drug dispenser? Mark all that apply.

Patient self-report 01 Pill count 02 Pharmacists’ judgment 03 Electronic pill cap count 04 Verifying refill dates 05 Other, specify ________________66

79. Does the drug dispenser (pharmacist) provide adherence counselling?

No 00 Yes 01

80. What HIV clinic data can be accessed through computer

Individual client chart/medical record 01 Registers 02 Pharmacy records 03 Laboratory records 04

81. Does the HIV clinic know the adherence rate for ART patients?

No 00 Yes 01

82. If yes, what is the adherence rate among how many patients (and the associated date?)?

[_______________] Adherence % [_______________] out of number of patients [__ __ | __ __ | __ __ ] DD MM YY

158

Section 8: Adherence 83. Has the HIV clinic ever offered the following adherence support to all ART patients? (not

referrals but services through clinic); if yes, when did the service start and stop Mark all that apply.

Yes/NO Start date End Date PLHA support groups 01

No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

Adherence support workers 02

No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

Home based care workers 03

No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

Treatment buddies/supporters 04

No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

Other, specify _____________ 66 No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

84. Is having a treatment buddy/supporter a requirement to start ARV drugs at this HIV clinic?

No 00 Yes 01

85. Does this facility have links with community based health workers or volunteers (including faith-based)

No 00 Yes 01

Q87 Q81

86. What types of services do the community based workers provide related to ART adherence? Circle all that apply

Distribute ARV drugs 01 Refer for medical care 02 Provide home-based care 03 Provide adherence support 04 Provide emotional/ social support 05 Missed appointments/Defaulter follow-up 06 Other, specify _______ 66

87. Is there a formal system for making the referrals to community services, such as a referral slip or other means?

No 00 Yes 01

Q85 Q83

159

Section 8: Adherence No. Questions and Filters Coding Category Skip

To Answer

88. If yes, what method is used for referrals? Mark all that apply

Referral slip (observed) 01 Referral slip (not observed) 02 Write on prescription form/letterhead 04 Write note/letter (unstructured) 06 Verbal referral request 05 Other 07

89. Are referrals recorded? Yes, in patient file 01 Yes, in the register 02 Yes, Other (specify ________) 03 No, information does not come back to provider 04

90. How does information about the patients from the community health worker get back to provider?

Written reports 01 Verbal reports 02 Meetings 03 Feedback slip 04 No method used 05

91. Is it required that community health worker/volunteers undergo training in adherence support?

Yes No Don’t know

160

Section 9: Tracing ART clients lost to follow up No. Questions and Filters Coding Category Skip

To Answer

92. Do you have a system for making individual HIV client appointments?

No 00 Yes 01

93. How do you identify ART patients who have missed an appointment?

No System 01 By Pharmacy reports 02 Appointment diary 03 Other, specify ___________ 66

94. Is there a process in this facility for tracing clients on ART who are lost to follow-up?

No 00 Yes 01

Q91

Q90

95. What process is used to trace clients for follow-up? When did the HIV clinic start this process and when did it stop (if it has stopped)

Yes/No Start Date Stop date Telephone call 01

No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

House visit by adherence Support worker 02

No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

House visit by health care workers 04

No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

House visit by home-based care workers 05

No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

Other, specify ___________ 66

No 00 Yes 01

[__ __ | __ __ ] MM YY

[__ __ | __ __ ] MM YY NA 66

161

Section 9: Tracing ART clients lost to follow up No. Questions and

Filters Coding Category Skip

To Answer

96. Does the HIV clinic know the retention rate for ART patients?

No 00 Yes 01

97. If yes, what is the retention rate among how many patients (and the associated date?)

[_______________] retention % [_______________] out of number of patients [__ __ | __ __ | __ __ ] DD MM YY

98. What are the top three reasons why patients become lost to follow-up? Death 01 Move 02 Patient decision 03 Lack of funds 04 Unknown 05 Other, specify _____________ 66

Reason 1: _________ Reason 2: __________ Reason 3: __________

99. Do you have a system for tracking patient transfers to another facility for ART care?

No 00 Yes 01

100. Where is the transfer information recorded?

General OPD register with HIV/AIDS and non HIV/AIDS clients 01 Specific register for HIV/AIDS clients 02 Specific register only for ART clients 03 Individual client chart/medical record 04 No record kept 06 Other, specify ___________________ 66

101. End time of interview

__ __ : __ __ [Hour: minute]

END

Thank the respondent for their time and participation.

162

RETENTION IN ART PROGRAMS IN POST-CONFLICT NORTHERN UGANDA.

PATIENT’S IN-DEPTH INTERVIEW QUESTION GUIDE

Date…………………………………………………………………………………… Health Unit.......……………………………………………………………………….. Venue of Interview……………………………………………………………,……... Interviewer Code………………………………………………………………,,,,,….. Language(s) to be used………………………………………………………………. Starting time………………………………………………………………………….. Closing time………………………………………………………………………….. Demographic Characteristics of the patient Patient ID Number..................................................................................................... Age.......................................... Sex Female Male ( Tick one) Physical Address in the Village.................................................................................. Physical Address where he/she came from today...................................................... Level of Education: Primary Level O- Level A- Level Other (specify) Religion: ........................................................... Introduction Good morning/afternoon Sir/ madam. My name is ………………………………… Our team is from NUMAT Program-Gulu Office. We are here to assess the factors that influence the continuation of HIV positive persons on antiretroviral therapy once they have started treatment, so as to identify strategies to improve retention in ART programs in northern Uganda. The purpose of this interview is to gather your opinions on and experiences with the antiretroviral therapy program at this health unit in order to recommend appropriate interventions that could further improve the quality of care for people living with HIV/ AIDS. This interview is voluntary, private and confidential. Please fill free to discuss any issues and give your frank and honest opinions.

163

I have with me an audio-tape recorder that will help me remember the proceedings of this interview to ensure that I do not miss out any important point. May I use it? (Interviewer asks for consent).I will also be writing down your opinions for record purposes. The record will be kept confidential. May I continue? Question Guides

1. What have been your experiences with taking antiretroviral therapy since you started getting antiretroviral treatment from this health unit?

2. What are the challenges and constraints you have encountered during this period of antiretroviral therapy?

3. How has life in the IDP camps affected your continuation on antiretroviral therapy?

4. What direct costs do you incur in order to access antiretroviral therapy at this health unit?

5. What are the most probable reasons why some patients who start on antiretroviral therapy decide to discontinue the treatment later on?

6. What are the main barriers to adherence in your community? 7. Have you experienced any form of stigma and or discrimination in the community

or at this health unit as a result of your HIV status? 8. To what extent has the community you live in supported you to continue

accessing antiretroviral therapy from this health unit? 9. What do you think should be done at the health unit in order to ensure that

persons who start on antiretroviral therapy at this health unit do not discontinue treatment in the long-run?

10. What do you think should be done at community level in order to ensure that persons who start on antiretroviral therapy at this health unit do not discontinue treatment in the long-run?

11. In your opinion, are there any cultural or religious beliefs that hinder patients from continuing with use of antiretroviral therapy? If yes, describe those cultural / religious beliefs.

We have come to the end of this interview. I would like to thank you for the free and frank discussion. The information you have provided to us will be very valuable for this survey. Have a good day.