Download - Hmis publication, june 2012
page 1
Ministry of Public Health
GD of Policy and Planning
Introduction
This newsletter is designed to provide a basic synopsis of routine HMIS and is structured by first discussing briefly HMIS performance indicators, some health status indicators by MoPH priority health areas and then by discussing some service performance indicators. The primary data source is that of the HMIS, however some indicators are triangulated with those of the household survey and the Afghan Mortality Survey.
There are over 120 MoPH-HMIS indicators which can be used by health professionals to monitor program progress. This newsletter selects some of those indicators by MoPH priority areas including indicators for Maternal and Child Health, Tuberculosis, Malaria, Mental Health and the Hospital Sector.
Some of the proxy MoPH indicators contained within this report include:
% 1 yr olds immunized with DPT3
% 1-yr olds w/ measles vaccine
% institutional deliveries
% of pregnant women received
1 ANC visit
Couple Month Protection
# delivered women receiving 1 PNC/total # delivered women
# of new TB SP+ cases found/est. prev TB
# TB cases cured (SP-)/ total # TB cases under Rx 8 months
# reported mental health cases
% HF with stock-out of 1 essential drug
% of HF with at least one FHW
# of acute malnutrition cases
% of acute malnutrition cases
Trend of Acute W. diarrhea in U5
HIS PUBLICATION No. 1
Month-06
page 2
Trend of Pneumonia in U5
This newsletter is designed to stimulate discussion amongst health professionals with regard to the direction of the health sector. It aims to build the capacity and confidence of people to begin to analyze information so that they may ask questions, check their program data internal consistency checks and begin to monitor their own program progress.
Monitoring is the responsibility of everyone. Data Quality is the responsibility of everyone. Data Use is the responsibility of everyone. The availability of timely and accurate information ensures that decision-makers have no excuse for not taking information into consideration while making decisions. Accountability within governance structure starts with examining vertical and horizontal program information. The information within this newsletter could be used at central level by program or department managers during their regular discussions with stakeholders, at provincial level during the PHCC meetings and also shared with health facility staff.
Description of the HMIS system
Health system strengthening is related to the production and use of quality health information at all levels of the health system. Routine Health Information Systems (RHIS) are receiving increasing attention as a sustainable strategy towards integrated, country-owned national systems.
The HMIS is a system based on qualitative and quantitative indicators on which data is routinely collected, processed, analyzed, interpreted, disseminated, and used to improve the provision of health services according to the MOPH‟s priorities and ultimately to improve the health of the population. The following data is captured using the HMIS.
BPHS
FSR (Facility Status Report)
General Facility Status
Human Resource Status
Equipment Status
Status of Services provided
MIAR (Monthly Integrated Activity Report)
OPD Services
Nutrition Services
Maternal and Neonatal Care
Stock Status
Immunization Services
Laboratory Services
TB Services
Community Supervision
MAAR (Monthly Aggregated Activity Report)/ Health Post Services
Family Planning
Obstetric Referral
Nutrition Screen
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Under Five Morbidity
Stock Information
Community Health Meeting
Immunization Referrals
CAAC (Catchments Area Annual Census) with key target groups
Family Planning Coverage
Pregnancies
Immunization Coverage
Maternal and Neonatal death
EPHS
HSR (Hospital Status Report)
General Status of the Hospital
Human Resources Status
Equipment Status
Status of Services Provided
Supervision
HMIR (Hospital Monthly Inpatient Report)
Inpatient Services
Nutrition Services for under fives
Imaging services Status
Stock Status
Cases and deaths Status
What HMIS can and cannot do
I. The HMIS is limited to the collection of routine management information and as such is not able to capture all the information needs for all program areas. It provides trends to examine health sector performance. The HMIS is limited to priority indicators selected for monitoring progress in the implementation of the BPHS/EPHS. The HMIS does not capture information on notifiable diseases.
II. There are limitations to the use of HMIS data. The population denominator is reduced by 25% because it was assumed that 75% of the population only has access to health services. This means that the HMIS does not capture information on 25% of the population, which may or may not have a higher morbidity and mortality thus could lead to over or under reporting of the services statistics or morbidity and mortality.
III. The HMIS data quality, completeness, timeliness and accuracy, is validated by a third party which demonstrates accuracy of over 90% , which is almost double that found in Pakistan and Uganda, and similar to China and Mexico. National mortality survey (APHI et al 2010) data validated the trends in service coverage, infant and maternal mortality in HMIS data after accounting for underreporting.
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Information flow
Below is a diagram demonstrating the flow of HMIS information across the health sector. The diagram identifies what forms are to be completed and the feedback and results which should be discussed within each tier of the health sector. At the last health retreat in 2012 it was identified that there needed to be strengthening of information sharing for planning and monitoring at Provincial Level. It will be the role of the HMIS Officers to ensure the appropriate dissemination of health information to both the community and at the Quarterly Provincial Health Coordination Committee meetings. The HMIS Officers will also need to coach and mentor health facility staff to use information to improve the health outcomes of the population.
MoPH
HMIS
UNITMaintains
1. Facility Codes and Database
2. Staff Codes and Database
3. Service Statistics Database
4. Grants Management Database
5. Training Database
PHO
NGOHospitals
SC/BHC/
CHC/DH
1. Monthly reports
2. Quarterly Facility reports
3. Reports from Health Posts
4. Community Survey reports
1. Monthly reports by Facility
2. Quarterly reports by Facility
3. Staff changes in province
4. Training in province
5. Grants management reports
6. Ad-hoc reports
1. Feedback reports (Quarterly)
2. Reports/information on request
3. Meetings (PHCC Quarterly)
4. Supervision visits
1. Feedback reports (Quarterly)
2. Reports/information on request
3. Meetings (Semi-Annual)
4. Supervision visits
MoPH
Executive
Directorates
Departments
Analysis for
Action
Health PostCommunity
Health Post
activity reportsAnnual Census
1. Facility Database
2. Staff Database
3. Service Statistics Database
4. Grants Mgt. Database
5. Training Database
Maintains
National Indicator Analysis
Annual Progress Reports
Semi-Annual HMIS Report and
Conference
Analysis for
Action/ provincial planning
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Number and type of health facilities
Health Facilities by projects:
Program BHC CHC DH PH RH SH SHC mobile Other TOT
PGC (EC) 178 83 13 5 1 82 13 6 381
HSS/GAVI 76 15 2 93
MoPH 60 24 3 11 3 13 11 3 33 161
Other 111 19 7 2 2 10 63 46 65 325
PCH(USAID) 267 169 27 5 1 70 11 550
SHARP(WB) 196 84 19 5 0 0 170 5 1 480 BHC: Basic Health Centre, CHC: Comperhensive Health Centre, DH : District Hosptial, SHC: Sub Health
Centre, PH: Provincial Hospital, RH: Regional Hospital, SH: Special Hospital
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Number of health facilities by Province-1390:
Province BHC CHC DH MC PH RH SH SHC Other Total
Badakhshan 33 13 2 21 1 35 5 110
Badghis 24 3 1 1 1 14 44
Baghlan 26 15 2 1 1 17 3 65
Balkh 44 14 5 1 1 1 1 33 6 106
Bamyan 23 10 3 3 1 29 6 75
Dykundi 14 8 2 4 1 13 1 43
Farah 5 11 1 1 17 2 37
Faryab 21 16 2 3 1 14 3 60
Ghazni 37 26 3 1 8 5 80
Ghor 21 8 2 1 1 20 2 55
Helmand 30 14 4 1 11 3 63
Hirat 38 25 4 4 1 25 3 100
Jawzjan 16 7 2 1 1 1 7 2 37
Kabul 74 38 8 10 22 3 26 181
Kandahar 19 20 1 3 1 2 6 52
Kapisa 15 8 1 1 1 15 1 42
Khost 10 12 1 9 5 37
Kunar 21 10 1 1 10 2 45
Kunduz 32 12 1 3 1 17 9 75
Laghman 17 8 2 1 13 1 42
Logar 20 7 2 7 1 6 4 47
Nangarhar 73 19 3 3 1 2 19 6 126
Nimroz 5 2 1 1 7 2 18
Nooristan 11 1 2 10 24
Paktika 18 4 2 1 7 1 33
Paktya 17 8 2 1 11 2 41
Panjsher 9 2 2 1 7 6 27
Parwan 32 10 1 2 1 22 1 69
Samangan 13 5 2 1 1 11 33
Sar-e-Pul 16 8 2 1 1 21 49
Takhar 37 13 3 3 1 15 4 76
Urozgan 7 6 2 1 1 17
Wardak 26 9 3 1 1 18 1 59
Zabul 8 7 1 1 5 22
Grand Total 812 379 69 82 28 6 24 472 118 1990 BHC: Basic Health Centre, CHC: Comperhensive Health Centre, DH : District Hosptial, SHC: Sub Health
Centre, PH: Provincial Hospital, RH: Regional Hospital, SH: Special Hospital
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Number of health facilities by service implementers-1390:
Implementer BHC CHC mobile SHC DH PH RH SH Other TOL
SCA 66 30 5 58 6 2 2 169
MoPH 61 24 3 11 3 11 3 13 33 161
SM (MoPH) 53 20 3 44 3 2 1 126
HN-TPO 69 37 1 34 5 2 1 2 151
CHA 39 25 4 60 6 1 2 137
BDN 42 31 3 24 5 1 2 108
AADA 37 24 4 21 3 2 91
CAF 53 20 1 9 4 1 88
BRAC 42 19 2 15 5 1 0 84
ACTD 33 14 1 25 3 1 77
SAF 34 23 1 12 4 3 77
AMI 29 17 3 21 2 2 1 75
Other 28 5 4 5 2 1 2 7 14 68
Merlin 27 11 12 11 1 2 64
AHDS 22 27 4 4 1 1 0 59
Kinder Berg 3 1 17 29 4 54
AKDN 18 8 1 23 1 1 1 53
ARCS 43 8 1 1 53
IMC 35 5 5 4 1 1 1 52
MRCA 18 7 2 5 2 1 1 36
Move 21 2 8 1 0 32
Ibn Sina 6 8 1 11 1 3 30
SDO 12 11 3 2 1 29
Emergency 2 1 20 23
DAC 8 2 8 1 1 20
CWS 7 2 7 0 16
STEP 1 1 7 0 9
MSI 3 6 9
HADAAF 7 0 7
Wadan 1 6 7
SHUHADA 1 4 1 0 6
LEPCO 5 5
AKHS 3 1 1 0 5
IAM 2 2 4
AIL 3 1 0 4
ToT 812 379 82 472 69 28 6 24 118 1990
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HMIS Report submission:
94% of health facilities in Afghanistan submit their MIAR.
12447 health posts submitted their HMIS reports
Submission 1390 HMIS
Submission
MIAR 94%
FSR 89%
HMIR 81%
HSR 81%
Number of health facilities submitting MAAR 1049
Number of health posts submitted MAR 12447
Submission rate for Monthly Integrated Activity Report (MIAR):
The BPHS including SHC, BHC, CHC, DH had the highest MIAR submission in 1390. The lowest rate belonged to special hospitals (SH).
Among HMIS forms MIAR had the highest submission rate.
Mobile health facilities had the lowest FSR submission.
District hospitals had the highest rate of HSR submission in 1390.
BHC: Basic Health Centre, CHC: Comperhensive Health Centre, DH : District Hosptial, SHC: Sub Health Centre, PH: Provincial Hospital, RH: Regional Hospital, SH: Special Hospital
91%
98% 94% 93%
89% 90%
81%
31%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
BHC CHC DH SHC mobile PH RH SH
HMIS Report Submission By Type of Health Facility
MIAR
FSR
HMIR
HSR
page 9
HMIS Reports Submission by Province in 1390:
Noorstan , Dykundi, Logar, Samangon, Paktya and Kunar had the highest HMIS reports submission.
Monthly Aggregated Activity Report (MAAR) Submission Rate:
Excluding Kabul province, Kapisa health facilities have the lowest health post and MAAR submission.
Provinces %MIAR % FSR % HSR %HMIR % MAAR # MAR
Badakhshan 100% 87% 100% 100% 100% 417
Badghis 84% 81% 100% 100% 78% 310
Baghlan 94% 92% 100% 100% 92% 607
Balkh 93% 89% 63% 100% 84% 799
Bamyan 100% 83% 75% 98% 100% 406
Dykundi 94% 97% 100% 100% 100% 321
Farah 87% 100% 100% 100% 94% 369
Faryab 100% 89% 100% 100% 93% 513
Ghazni 92% 89% 75% 100% 88% 750
Ghor 98% 98% 100% 100% 77% 409
Helmand 93% 95% 60% 57% 77% 429
Hirat 98% 85% 100% 100% 78% 1010
Jawzjan 99% 97% 75% 100% 92% 333
Kabul 72% 43% 33% 44% 30% 420
Kandahar 100% 89% 100% 100% 74% 476
Kapisa 97% 92% 100% 100% 60% 169
Khost 99% 97% 100% 75% 97% 304
Kunar 97% 90% 100% 100% 100% 251
Kunduz 95% 92% 100% 100% 93% 318
Laghman 100% 98% 100% 75% 99% 277
Logar 94% 98% 100% 100% 100% 153
Nangarhar 88% 84% 83% 99% 84% 839
Nimroz 100% 100% 100% 100% 86% 105
Nooristan 92% 100% 100% 100% 100% 140
Paktika 95% 79% 100% 100% 83% 188
Paktya 97% 94% 100% 100% 96% 305
Panjsher 100% 89% 50% 67% 85% 115
Parwan 100% 100% 100% 100% 70% 336
Samangan 96% 93% 100% 100% 100% 140
Sar-e-Pul 98% 96% 100% 100% 93% 264
Takhar 99% 94% 100% 100% 94% 480
Urozgan 94% 100% 100% 100% 77% 185
Wardak 93% 94% 75% 94% 83% 156
Zabul 91% 90% 50% 100% 89% 154
0%
20%
40%
60%
80%
100%
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% of Health Facilities Submit MAAR _ 1390
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Linkages with other systems
Currently the MoPH HIS databases are at the level that allows departments to easily search and extract data from their own databases or to do other queries using a common link.
The MoPH HMIS database is the “common” database through which other departmental databases interact with the core system. The MoPH HMIS Department is to take the technical lead in facilitating database development. The diagram below briefly demonstrates the link between a number of the databases and the HMIS common database.
Some of the databases being used in the MoPH include the M&E database, HMIS, DEWS, EPI database, HR database, Procurement database, Expenditure Management Information System and Payroll system. These need to be integrated, wherever feasible technically and required operationally, and brought under one data centre control via a database warehouse. Improving connectivity to the database at provincial level will also be a priority of the MoPH.
page 11
MoPH Priority Health Problems and Indicators: Health service policy for the national level is set at the central level by a mandatory minimum package of health services, the Basic Package of Health Services (BPHS) and the Essential Package of Hospital Services (EPHS). In 2010, the MoPH identified key health indicators which could be used to measure progress against the key priority areas. This section reviews progress against some of those indicators. Below are the results of the most recent LQAS Household Survey conducted in USAID and EC provinces.
Figure 2: Summary of PGC Household Survey 2011
page 12
1. Reproductive Health
This section covers important indicators for reproductive health include the provision and use of contraceptives, the provision of TT2, institutional deliveries and caesarian section rates.
Percentage of service delivery points providing FP counseling and/or FP products: Less than 80% of health facilities in the following provinces are providing FP services: Farah, Helmand , Kabul, Kapisa , Panjsher and Zabul.
Women Receiving TT2
A woman receiving two or more injection of tetanus toxoid (TT2 or more) during pregnancy is an important indicator of ANC service and preventing neonatal tetanus. Percentage of pregnant women receiving two or more TT injections under HMIS data was close to that of the AMS findings as evidenced in the table below. In addition, the regional distributions of TT2 or more were also similar in HMIS and AMS, indicating that AMS findings validate HMIS data.
Percentage distribution of TT2 or more coverage, contraceptive use by regions in AMS 2010, HMIS 2010 and NRVA 2007-08
Domains TT2 or more coverage % Contraceptive use
%
CYP 2010 is comparable to following % of women using contraceptive for a year
AMS HMIS NRVA AMS NRVA HMIS- CYP
North 60 74 13 255948 19
Central 44 42 31 420282 22
0%
20%
40%
60%
80%
100%
120%
Bad
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Availability of Modern Contraceptive at Health Facilities (1390)
page 13
South 47 53 15 338386 23
Total 50 55 33 20 15 1014617 22
Number of Functional Emergency Obstetric Care (EmOC) Units:
Emergency obstetric signal functions are defined as:
Administration of parenteral antibiotics;
Administration of parenteral oxytocic drugs;
Administration of parenteral anticonvulsants for pregnancy-induced hypertension;
Performance of manual removal of placenta;
Performance of removal of retained products (e.g. vacuum aspiration);
Performance of assisted vaginal delivery (e.g. ventouse, forceps);
Performance of surgery (e.g. Cesarean section); and
Performance of blood transfusion. Facilities are divided into those that provide „basic‟ emergency obstetric care (EmOC) and „comprehensive‟ EmOC. If a facility has performed each of the first 6 functions, it qualifies as providing basic EmOC. If it has provided all 8 of the functions, it qualifies as a „comprehensive‟ EmOC facility.
Provinces Comp. EmOC
Basic EmOC
Provinces Comp. EmOC
Basic EmOC
Badakhshan 2 56 Kunar 1 23
Badghis 2 19 Kunduz 1 53
Baghlan 3 50 Laghman 1 15
Balkh 5 74 Logar 3 20
Bamyan 3 34 Nangarhar 4 62
Dykundi 1 23 Nimroz 1 6
Farah 3 22 Nooristan 1 9
Faryab 6 33 Paktika 4 9
Ghazni 3 45 Paktya 3 21
Ghor 3 14 Panjsher 1 12
Helmand 3 24 Parwan 1 40
Hirat 6 37 Samangan 3 20
Jawzjan 2 27 Sar-e-Pul 3 33
Kabul 6 38 Takhar 4 54
Kandahar 2 28 Urozgan 1 9
Kapisa 1 8 Wardak 2 27
Khost 1 16 Zabul 1 9
page 14
Proportion of Institutional Deliveries
The proportion of births delivered in facilities with basic or comprehensive EmOC.
Caesarian Section Rate: The Caesarian section rate is the proportion of pregnant women who have a cesarean section in a specific geographical area and time period. This indicator demonstrates the extent to which a particular life-saving obstetric service is being performed in EmOC facilities. It reflects the availability, accessibility and utilization of services as well as the functioning of the health service system. The appropriate use of a cesarean section leads to a decrease in maternal mortality and morbidity, as well as decreasing perinatal morbidity and mortality. While cesarean sections may be performed solely for the health of the fetus or newborn, UNICEF/WHO/UNFPA recommend a C-section rate between 5 and 15 per cent of all births, based on estimates from a variety of sources. Rates less than 5 per cent may indicate inadequate availability and/or access to EmOC.
Helmand, Kapisa, Faryab, Badghis, and Laghman had the lowest caesarian section rate in 1390. Kabul , Hirat, and Balkh had the highest caesarian section rate.
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0.8%1.2%
3.7%
0.9%0.6%
1.1%
0.1%
4.4%
2.3%
4.9%
1.4%
0.1%
1.5%0.8%
0.4%1.0%
2.2% 2.2%
0.9% 1.2%0.7%
2.0%
0.7% 0.5%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%B
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Caesarian Section Rate(1390/2011)
Postnatal Care (PNC):
The first hours, days and weeks after childbirth are a dangerous time for both mother and newborn infant. Among women who die each year due to complications of pregnancy and childbirth, most deaths occur during or immediately after childbirth. Care in the period following birth is critical not only for survival but also to the future of mothers and newborn babies. Major changes occur during this period that determine their well-being and potential for a healthy future. Postpartum care for the mother has focused on routine observation and examination of vaginal blood loss, uterine involution, blood pressure and body temperature. Similarly, postnatal care for the baby has focussed on cord care, hygiene and weight monitoring and feeding and/or immunizations. Over-reporting is seen in Logar, Nangarhar, Khost and Kapisa provinces.
0%20%40%60%80%
100%120%140%160%
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% PNC_1390
page 16
2. Child Health
This section covers important indicators for child health including diarrhea and pneumonia cases, trends immunization and malnutrition.
Diarrhea and Pneumonia Cases
Acute respiratory infections, diarrheal diseases, malnutrition, neonatal tetanus and measles are the main
causes of death among children aged 0-59 months in Afghanistan. A review of data reveals diarrhea is widespread throughout the year with an increase in the number of cases started from May, reaching the highest levels in the months of June, July and August and gradually decreasing again from the month of September onwards
Kunar, Laghman, Nangarhar, and Nimroz had the highest rate of diarrhea and pneumonia cases per under 5 population in 1390.
Nangarhar, Kabul, Badakhshan and Kandahar had highest numbers of pneumonia and diarrhea cases in 1390.
More than 240000 cases and 160000 cases are seen in Nangarhar and Kabul health facilities.
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# of Diarrhea and Pneumonia Cases in Children Less than 5 Y per 1000 population (U 5Y)
Diarrhea Pneumonia
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# of Pneumonia and Diarrhea Cases (1390/2011)
Diarrhea cases Pneumonia cases
page 17
Acute Respiratory Infection (ARI) and Diarrhoea Disease (DD) contribute to 40% of all OPD consultation.
29 % of consultations are due to ARI and 11% due to diarrhoea diseases
Immunization Coverage:
The following graphs indicate that trends in immunization have not substantially increased despite increases in deliveries at health facilities. This could represent a missed opportunity to encourage vaccination amongst mothers of newborns.
Diarrhea Diseases
11%
ARI 29%
Other Cases 60%
Proportion of All DD and ARI among all OPD cases in 1390
06/24/2012HMIS Department, MoPH 10
page 18
Measles:
Nangarhar, Kabul, Khost, Kandahar, Ganzni, Kunar , Helmand and Paktya had the highest cases of measles in 1390.
Low Birth Weight:
Malnutrition: In Afghan preschool children 6-59 months, 54% (39.9-60%) are suffering from stunting and 7 % from wasting (Acute Malnutrition). This level of stunting or chronic malnutrition is the highest level in the world . The WHO classifies Afghanistan as country with “very high” prevalence of chronic malnutrition.
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# of measles cases-1390 (2011)
page 19
In terms of percentage, Panjsher, Sar e Pul, Kunar , Zabul, Bamyan and Paktya provinces show a high % of acute malnutrition.
In terms of absolute numbers Badakhshan, Baghlan, Faryab, Hirat, Kabul, Kunar, Kundoz,
Nangarhar , Paktya and Sur e pul have the highest acute malnutrition cases in 1390.
3. Tuberculosis
TB is a major public health and development challenge in Afghanistan. The country is one of 22 TB high-burden countries in the world. The World Health Organization estimates that every year in Afghanistan, more than 53 000 new cases of TB occur and more than 10,500 people die because of this curable disease. Women, already a vulnerable group in Afghanistan, account for 66% of cases.
0%
5%
10%
15%
20%
25%
30%
Bad
akh
shan
Bad
ghis
Bag
hla
n
Bal
kh
Bam
yan
Dyk
un
di
Fara
h
Fary
abG
haz
ni
Gh
or
Hel
man
d
Hir
at
Jaw
zjan
Kab
ul
Kan
dah
ar
Kap
isa
Kh
ost
Ku
nar
Ku
nd
uz
Lagh
man
Loga
r
Nan
garh
ar
Nim
roz
No
ori
stan
Pak
tika
Pak
tya
Pan
jsh
er
Par
wan
Sam
anga
n
Sar-
e-P
ul
Takh
ar
Uro
zgan
War
dak
Zab
ul
% of Acute Malnutrition (# of Cases/U 5Y population) 1390
0
5000
10000
15000
20000
25000
Bad
akh
shan
Bad
ghis
Bag
hla
nB
alkh
Bam
yan
Dyk
un
di
Fara
hFa
ryab
Gh
azn
iG
ho
rH
elm
and
Hir
atJa
wzj
anK
abu
lK
and
ahar
Kap
isa
Kh
ost
Ku
nar
Ku
nd
uz
Lagh
man
Loga
rN
anga
rhar
Nim
roz
No
ori
stan
Pak
tika
Pak
tya
Pan
jsh
er
Par
wan
Sam
anga
nSa
r-e-
Pu
lTa
khar
Uro
zgan
War
dak
Zab
ul
# of Acute Malnutrition by Province1390
page 20
TB detection rate (from HMIS):
4. Service Workload
Average New Out Patient Department per Month by Type of Health Facility
Among BPHS health facilities district hospitals (DH) had the highest average OPD per month in 1390.
OPD per Capita by province: Consultation rates varied markedly by province, ranging from 2.6 in Logar to 0.8 in Kandahar.
0
0.2
0.4
0.6
0.8
1
Bad
akh
shan
Bad
ghis
Bag
hla
n
Bal
kh
Bam
yan
Dyk
un
di
Fara
h
Fary
ab
Gh
azn
i
Gh
or
Hel
man
d
Hir
at
Jaw
zjan
Kab
ul
Kan
dah
ar
Kap
isa
Kh
ost
Ku
nar
Ku
nd
uz
Lagh
man
Loga
r
Nan
garh
ar
Nim
roz
No
ori
stan
Pak
tika
Pak
tya
Pan
jsh
er
Par
wan
Sam
anga
n
Sar-
e-P
ul
Takh
ar
Uro
zgan
War
dak
Zab
ul
TB Detection 1390
1369
814 1291
2341
5276
0
1000
2000
3000
4000
5000
6000
Mobile Sub Center BCH CHC DH
New OPD Per Month by Type of HF 1390
page 21
Trend of Patients/Clients per Month per Health Facility in last 8 Years: There has been a 95% increase in average number of Patients/Clients per month per health facility:
Number of admissions by type of hospital
Provincial hospital had the highest admission in 1390 but bed turn over shows Regional Hospital and after District Hospital had higher bed turn over.
Overall 1378388 patients were admitted in Afghanistan hospitals during 1390.
960 1138
1275 1404
1735 1779 1773 1878
0
200
400
600
800
1000
1200
1400
1600
1800
2000
Y 83 Y 84 Y 85 Y 86 Y 87 Y 88 Y 89 Y 90
Nu
mb
er
of
visi
ted
cas
es
Last 8 past years
Average Number of Patients/Clients per month per Health Facility
page 22
Bed Turnover Rate: Bed turnover rate is a measure of the extent of hospital utilization. It is the number of times there is a change of occupant for a bed during a given time period. It is given by the formula:
Hospital bed turnover rate = Number of discharges (including deaths) in a given time period / Number of beds in the hospital during that time period
DH, 331089, 24%
PH, 408517, 30%
RH, 392424, 28%
SH, 246358, 18%
# Of Admissions by Type of Hospital (1390/2011)
7.5 6.9
9.8
0.0
2.0
4.0
6.0
8.0
10.0
12.0
DH PH RH
Bed Turnover Per Month
page 23
Bed occupancy rate in hospitals: The occupancy rate is a calculation used to show the actual utilization of an inpatient health facility for a given time period. Bed occupancy rates have been proposed to reflect the ability of a hospital to provide safe efficient patient care. A good hospital works well when bed occupancy rates are between 60 and 80%. This creates the flexibility that is good for patients. By type of hospital: Regional hospitals are over-occupied.
By province: Badakhshan, Baghlan, Jawzjan, Kandahar and Kunar hospitals are over-occupied
60% 62%
102%
79%
0%
20%
40%
60%
80%
100%
120%
DH PH RH all Tyep
Bed Occupancy Rate by Type of Hospital 1390
0%20%40%60%80%
100%120%140%160%180%
Bad
akh
shan
Bad
ghis
Bag
hla
nB
alkh
Bam
yan
Dyk
un
di
Fara
hFa
ryab
Gh
azn
iG
ho
rH
elm
and
Hir
atJa
wzj
anK
abu
lK
and
ahar
Kap
isa
Kh
ost
Ku
nar
Ku
nd
uz
Lagh
man
Loga
rN
anga
rhar
Nim
roz
No
ori
stan
Pak
tika
Pak
tya
Pan
jsh
er
Par
wan
Sam
anga
nSa
r-e-
Pu
lTa
khar
Uro
zgan
War
dak
Zab
ul
Bed Occupancy Rate 1390
page 24
Consultation per Health Post per Month Zabul, Laghman , Nooristan and Kunar had the lowest figure for this indicator in 1390. Badghis, Faryab,
Jawzjan and Farah had the highest figure for this indicator in 1390.
5. Mental Health Services
The following map shows utilization of mental health services by province. Mental health services are less utilized in north, northeast and central region.
74
121
59
95
67
41
111 122
91
70
90 92
117
86
68
100 87
18
77
13
30 33 43
14
46
75
53 60
37 31
92
45
26 11
0
20
40
60
80
100
120
140
Bad
akh
shan
Bad
ghis
Bag
hla
n
Bal
kh
Bam
yan
Dyk
un
di
Fara
h
Fary
ab
Gh
azn
i
Gh
or
Hel
man
d
Hir
at
Jaw
zjan
Kab
ul
Kan
dah
ar
Kap
isa
Kh
ost
Ku
nar
Ku
nd
uz
Lagh
man
Loga
r
Nan
garh
ar
Nim
roz
No
ori
stan
Pak
tika
Pak
tya
Pan
jsh
er
Par
wan
Sam
anga
n
Sar-
e-P
ul
Takh
ar
Uro
zgan
War
dak
Zab
ul
Average Patient seen by HP Per Month -1390
page 25
6. Staffing (by facility type)
Proportion of health facilities with at least one female health worker:
Province population per clinical health worker:
Province Name
BPHS facility per 10000population
Province Name
BPHS facility per 10000population
Badakhshan 1,18 Kunar 0,95
Badghis 0,93 Kunduz 0,66
Baghlan 0,70 Laghman 0,98
Balkh 0,81 Logar 1,12
Bamyan 1,67 Nangarhar 0,82
Daykuni 0,95 Nimroz 1,08
Farah 0,62 Nuristan 1,88
Faryab 0,72 Paktika 0,79
Ghazni 0,69 Paktya 0,76
Ghor 0,85 Panjshir 1,60
Hilmand 0,67 Parwan 1,16
Hirat 0,55 Samangan 0,94
Jawzjan 0,66 Sar-i- Pul 0,94
Kabul 0,32 Takhar 0,77
Kandahar 0,44 Urozgan 0,40
Kapisa 0,99 Wardak 1,02
Khost 0,58 Zabul 0,77
0%
20%
40%
60%
80%
100%
Proportion of HF with At Lest One Female Health Worker_1390
page 26
Registered health workers (from HR database):
Physicians per 10,000 population
Midwives per 10,000 population
page 27
Availability of recommended staffing according to BPHS and EPHS: Although there were almost 2, 000 graduated community midwives from various training programs (CMEs and IHSs) there remain concerns with the employment and retention of those newly graduated within the health sector. Trainees are selected by provincial teams. There may need to be a stronger selection process of candidates.
7. Infrastructure, Utilities and Transport
27% of BHC, 14% of CHC and 8% of DH are in temporary buildings.
24% of BHC , 5% of CHC and 2% of DH didn‟t have electricity at all in 1390
50% of BHC, 57% CHC and 72% of DH had appropriate waste disposal system.
13% of DH had no ambulance transportation in 1390.
0 2000 4000 6000 8000
Suppor Staff
Doctor
Nurse
Administration
Midwife
Vaccinator
Lab Technician
Other
Pharmacy Technician
Pharmacist
Dental Technician
Radiography Technician
Anesthesia Nurse
Dentist
Human Resource in Health Sector (1390/2011)
Male
Female
page 28
Functioning laboratory: Blood transfusion capacity existed only in a minimum number of health facilities in Parwan , Bamyan, Zabul, Wardak and Panjsher provinces.
Province
% with functional
Lab
% of HF with Blood
Transfusion capacity
Province
% with functional
Lab
% of HF with Blood
Transfusion capacity
Badakhshan 44% 28% Kunar 50% 42%
Badghis 44% 7% Kunduz 49% 20%
Baghlan 46% 19% Laghman 48% 22%
27%
73% 71%
76%
14%
54% 50%
4% 14%
20%
64% 57% 58%
8%
28%
72%
87%
0%10%20%30%40%50%60%70%80%90%
100%
Infrastructure, Utilities and Transport-1390 for BPHS Facillities (BHC, CHC, DH)
BHC
CHC
DH
31%
4% 11%
22% 13%
27%
13%
29% 23% 26%
55%
11% 14%
31%
18% 18% 10%
17% 10% 9% 8%
27%
14%
42% 45%
0% 0%
38% 47%
30% 32%
8% 0%
62%
0%10%20%30%40%50%60%70%
Bad
akh
shan
Bad
ghis
Bag
hla
n
Bal
kh
Bam
yan
Dyk
un
di
Fara
h
Fary
ab
Gh
azn
i
Gh
or
He
lman
d
Hir
at
Jaw
zjan
Kab
ul
Kan
dah
ar
Kap
isa
Kh
ost
Ku
nar
Ku
nd
uz
Lagh
ma
n
Loga
r
Nan
garh
ar
Nim
roz
No
ori
stan
Pak
tika
Pak
tya
Pan
jsh
er
Par
wan
Sam
anga
n
Sar-
e-P
ul
Takh
ar
Uro
zga
n
War
dak
Zab
ul
% BPHS Facilities (BHC, CHC , DH) with Temporary Building - 1390
page 29
Province
% with functional
Lab
% of HF with Blood
Transfusion capacity Province
% with functional
Lab
% of HF with Blood
Transfusion capacity
Balkh 21% 7% Logar 33% 33%
Bamyan 39% 4% Nangarhar 67% 18%
Dykundi 22% 12% Nimroz 31% 6%
Farah 33% 20% Nooristan 63% 42%
Faryab 41% 14% Paktika 48% 16%
Ghazni 39% 33% Paktya 43% 13%
Ghor 19% 8% Panjsher 28% 5%
Helmand 35% 15% Parwan 25% 1%
Hirat 38% 16% Samangan 26% 21%
Jawzjan 48% 17% Sar-e-Pul 28% 10%
Kabul 65% 10% Takhar 32% 25%
Kandahar 62% 7% Urozgan 65% 41%
Kapisa 35% 10% Wardak 31% 5%
Khost 42% 25% Zabul 32% 5%
0%
20%
40%
60%
80%
Bad
akh
shan
Bad
ghis
Bag
hla
nB
alkh
Bam
yan
Dyk
un
di
Fara
hFa
ryab
Gh
azn
iG
ho
rH
elm
and
Hir
atJa
wzj
anK
abu
lK
and
ahar
Kap
isa
Kh
ost
Ku
nar
Ku
nd
uz
Lagh
man
Loga
rN
anga
rhar
Nim
roz
No
ori
stan
Pak
tika
Pak
tya
Pan
jsh
er
Par
wan
Sam
anga
nSa
r-e-
Pu
lTa
khar
Uro
zgan
War
dak
Zab
ul
Availability of Functional Lab and Transfusion Capacity in Health Facility-1390
% with functional Lab % of HF with Blood Transfusion capacity
page 30
Blood Transfusion Reaction Rate: Samangan , Wardak , Paktika and Jawzjan experience a high rate of transfusion reaction.
Stock Out of Essential Drugs:
Based on HMIS data essential drug stock out had a steady decrease from 1383 to 1390.
0.00%
0.50%
1.00%
1.50%
2.00%
2.50%
3.00%
3.50%
4.00%
Blood Transfusion Reaction Rate (average per month in 1390)
80
73 76
62 63 59
55 60
Y 1383 Y 1384 Y 1385 Y 1386 Y 1387 Y 1388 Y 1389 Y 1390
% of BPHS HFs with at least One Essential Drug Stock Out
page 31
8. Conclussion:
Information to be of use needs to be discussed and shared. Some recommendations could be to review referral practices between primary and tertiary care settings, to review in more detail the shifts in the burden of disease within and between communicable and non communicable diseases, determine how better to strengthen pharmaceutical supply and examine why new female graduates are not being retained or employed n the health sector.