operational research to increase the efficiency of art initiation in africa

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Operational Research to Increase the Efficiency of Antiretroviral Therapy Initiation in Africa Sydney Rosen Department of Global Health Boston University School of Public Health Health Economics and Epidemiology Research Office, University of the Witwatersrand February 1, 2017

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Page 1: Operational research to increase the efficiency of ART initiation in Africa

Operational Research to Increase the Efficiency of Antiretroviral Therapy Initiation in Africa

Sydney RosenDepartment of Global Health

Boston University School of Public Health

Health Economics and Epidemiology Research Office, University of the Witwatersrand

February 1, 2017

Page 2: Operational research to increase the efficiency of ART initiation in Africa

Today’s talk:

• The problem: Inefficient ART initiation

• A solution: RapIT

• The problem with the solution: Cost and cost-effectiveness

• A new solution: SLATE

Page 3: Operational research to increase the efficiency of ART initiation in Africa

The Problem: Inefficient ART Initiation

Page 4: Operational research to increase the efficiency of ART initiation in Africa

A “Treat All” World• In mid-2015, the World Health Organization recommended

offering ART to all HIV-positive persons, with no eligibility threshold: “Treat All”

• By the end of 2016, nearly all African countries had adopted treat all into national policy• Currently (2015): 12 million people on ART in Africa (UNAIDS Fact

Sheet November 2016)

• UNAIDS elimination target for 2030: 24 million people on ART

• “90-90-90” target for 2020: 15-16 million people on ART (WHO Global Health Observatory 2017)

• Upshot is that we have to start a lot more patients on ART in the next decade

1 National Department of Health 2013; 2Plazy et al 2014; 3Clouse et al 2013; 4Rosen and Fox 2011; 5Larson et al 2010

Page 5: Operational research to increase the efficiency of ART initiation in Africa

What if the patients won’t start?• Even after being found eligible for ART, patients don’t start treatment

when they should:- 57% of treatment-eligible patients didn’t start treatment ≤ 6 months in

KwaZulu Natal Province in South Africa in 2011-2012

- The probability of starting ART < 6 months was lowest in those with highest CD4 counts (Bor et al 2017, under review)

• Instead, patients wait until their CD4 counts fall and they are sick- In South Africa, >50% started with CD4 count <270 in 2015 (Boulle et al

2015)

• In a “treat all” world, everyone with HIV is eligible for ART and many will be diagnosed with high CD4 counts

• Our best strategy for expanding early treatment uptake could be to expand testing and initiate ART immediately after a positive HIV test, before the patient leaves the testing site (true “test and treat”)

1 National Department of Health 2013; 2Plazy et al 2014; 3Clouse et al 2013; 4Rosen and Fox 2011; 5Larson et al 2010

Page 6: Operational research to increase the efficiency of ART initiation in Africa

Why don’t people start ART?

• HIV test; result positive• Give blood sample for CD4 count• Complete TB symptom screen• Provide sputum sample if symptomatic

Visit 1

• Provide CD4 count results; treatment eligible• Provide TB test results and initiate TB treatment if

required

Visit 2

• Individual counseling session (education/adherence)Visit 3

• Group counseling session (education/adherence)Visit 4• Provide results of other blood tests• Treatment buddy sessionVisit 5

• Conduct physical examination• Dispense ARVsVisit 6

I am exhausted

Many reasons, but one is that starting treatment is not easy. The process has traditionally been slow, resource-intensive, and grueling for patients. For example, in South Africa…

Page 7: Operational research to increase the efficiency of ART initiation in Africa

A Solution:

Page 8: Operational research to increase the efficiency of ART initiation in Africa

RapIT: Rapid Initiation of Treatment Individually randomized, controlled trial of single-visit (“same

day”) ART initiation compared to standard of care initiation in Johannesburg, South Africa

Randomized (1:1) 377 adult, non-pregnant patients after positive HIV test or first CD4 count to rapid or standard initiation arms

Intervention: Compressed and accelerated initiation procedures to allow all

steps to be completed in one clinic visit Used rapid, point-of care laboratory tests at point of care for

immediate determination of treatment eligibility and regimen choice Outcomes: ART initiation by 90 days; initiated by 90 days and

retained and suppressed by 10 months Follow up by chart review until July 2015

• Take blood sample for CD4 count and perform rapid CD4 count;

• Perform TB symptom screen; take sputum sample if symptomatic and perform rapid TB test; initiate TB treatment if required (ART initiation delayed if TB treatment initiated;

• Perform other blood tests (rapid);• Conduct physical exam (ART initiation delayed if

referred off site for specific conditions);• Conduct education/adherence session;• Conduct individual counseling session;• Dispense ARVs

Visit 1

Page 9: Operational research to increase the efficiency of ART initiation in Africa

Results: Initiated ART ≤ 90 Days; Initiated ≤ 90 Days and Retained and Virally Suppressed ≤ 10 Months

377 ART eligible patients enrolled

136 initiated ≤ 90 days (72%) 182 initiated ≤ 90 days (97%)

Risk difference 25% (95% CI 19 to 33%)Crude relative risk 1.36 (95% CI 1.24 to 1.49)  

54 did not initiate ≤ 90 days 5 did not initiate ≤ 90 days

96 initiated ≤ 90 days and retained and suppressed by

10 months (51%)

119 initiated ≤ 90 days and retained and suppressed by

10 months (64%)

Risk difference 13% (95% CI 3 to 23%)Crude relative risk 1.26 (95% CI 1.05 to 1.5)  

40 initiated but not retained and suppressed

63 initiated but not retained and suppressed

190 STANDARD arm patients 187 RAPID arm patients

Page 10: Operational research to increase the efficiency of ART initiation in Africa

What Did We Learn?• Single-visit initiation as implemented by RapIT started

nearly all patients on ART and improved health outcomes• But it relied on relatively expensive point-of-care

instruments and changed other resource allocation (e.g. staff time)

• Is it cost-effective? Affordable? • We conducted a cost-effectiveness analysis to compare

rapid to standard initiation

1 National Department of Health 2013; 2Plazy et al 2014; 3Clouse et al 2013; 4Rosen and Fox 2011; 5Larson et al 2010

Page 11: Operational research to increase the efficiency of ART initiation in Africa

The Problem with the Solution:

Cost and Cost-Effectiveness

Page 12: Operational research to increase the efficiency of ART initiation in Africa

Methods Estimated cost per patient achieving primary outcome (initiated < 90 days and

retained and suppressed at 10 months) in each arm (“successful patient”) Multiplied resources used per patient (from CRFs and clinic charts) by actual

unit costs for resources, to get an average cost per patient- Clinic visits- ARVs and non-ARV medications- Laboratory tests (point of care and regular)- Fixed costs of clinic infrastructure and staff

Three main results for each study arm:- Cost per patient enrolled = total costs / total number of patients- Cost per patient achieving primary outcome = costs for successful patients/

number of successful patients- “Production cost” = all costs / number of successful patients

Scenario analyses to consider less expensive variations on the study algorithm Report undiscounted provider costs in 2015 USD; excludes savings to patients

Page 13: Operational research to increase the efficiency of ART initiation in Africa

Per patient enrolled Per patient suppressed Production cost$0

$100

$200

$300

$400

$500

$600

$700

$800

$319

$487

$738

$451

$505

$707

Standard arm, for comparison

Rapid arm baseline scenario

No POC TB tests (exclude patients with TB symptoms)

Increase patient volume (implement for all patients at clinic, not solely study sample)

Shift task (some steps shifted from primary health nurse to enrolled nurse)

Minimum cost scenario: exclude TB patients + high patient volume + enrolled nurseCo

st p

er p

atien

t ove

r 10-

mon

th p

erio

d fo

llow

ing

stud

y en

rollm

ent

Results: Cost Per Outcome

$132$18

-$31

Page 14: Operational research to increase the efficiency of ART initiation in Africa

What Did We Learn?• Single-visit initiation as implemented by RapIT was both

more effective and more expensive than standard initiation• Feasible variations on the RapIT strategy should reduce

costs, but they could also affect outcomes• Is it cost-effective? It depends, but the POC instruments

are a deterrent• Logical next step: Try the same strategy without the

technology

1 National Department of Health 2013; 2Plazy et al 2014; 3Clouse et al 2013; 4Rosen and Fox 2011; 5Larson et al 2010

Page 15: Operational research to increase the efficiency of ART initiation in Africa

A New Solution:

Page 16: Operational research to increase the efficiency of ART initiation in Africa

SLATE: SimpLified Algorithm for Treatment Eligibility

• Evaluate a simple, fast procedure for determining eligibility for immediate (same-visit) ART initiation without further steps

• Will enroll 960 adult patients presenting at clinics and not yet on ART in South Africa and Kenya

• Randomize (1:1) to SLATE initiation v standard of care initiation

• Intervention: SLATE algorithm

- For those who “screen in,” immediate dispensing of ARVs at patient’s first HIV-related clinic visit

- For those who “screen out,” refer for additional investigation, care, counseling or support before dispensing ARVs

• Outcomes: ART initiation within 28 days; retention in care at 6 and 12 months

Page 17: Operational research to increase the efficiency of ART initiation in Africa

The SLATE Algorithm

Medical history

Brief physical exam

Screen out criteria = Cough, fever, night sweats, weight loss, persistent headache, or serious self-reported symptoms suggesting further investigation

Screen out criteria = Observed conditions suggesting further investigation

Screen out criteria = Prior ART, TB treatment initiation <14 days, substance abuse, or concurrent medications or conditions suggesting further care

Screen out criteria = Responses suggesting further counseling or support

Symptom report

Readiness assessment

Continue

Continue

DISPENSE ARVS

Continue

REFER FOR FURTHER CARE BEFORE DISPENSING

Page 18: Operational research to increase the efficiency of ART initiation in Africa

SLATE (continued)

• After initiating ART under SLATE:

- Blood draw for required lab tests

- Schedule next routine visit

- Participate in clinic’s adherence support activities at this or future visit

• Study enrollment expected to start in February 2017 (South Africa) and March 2017 (Kenya)

• Follow-up after enrollment visit is by chart review for up to 16 months

• Implemented by BU partners HE2RO in South Africa and KEMRI in Kenya

• Funded by Bill & Melinda Gates Foundation

Page 19: Operational research to increase the efficiency of ART initiation in Africa

What Do We Hope to Learn?• Does SLATE increase overall prompt uptake of ART, by

reducing loss to follow up between HIV testing and ART initiation?

• Do patients initiated under SLATE have the same early outcomes on ART as those initiated under standard care?

• What causes patients to “screen out” under SLATE?

• How much does ART initiation cost providers and patients under SLATE compared to standard care?

• What are patients’ preferences for speed of initiation?

If successful, SLATE could help to standardize a fast, effective, low-cost model of ART initiation, and strengthen the cascade between testing and treatment.

1 National Department of Health 2013; 2Plazy et al 2014; 3Clouse et al 2013; 4Rosen and Fox 2011; 5Larson et al 2010

Page 20: Operational research to increase the efficiency of ART initiation in Africa

Thanks and AcknowledgementsParticipants• Study patients and study clinic operations managers and staff• City of Johannesburg, Gauteng Department of Health, and Kenya Ministry of

HealthCollaborators• HE2RO, Right to Care, KEMRI, Walter Reed Projects, Henry Jackson Foundation• Co-investigators: At BU—Alana Brennan, Matt Fox, Bruce Larson; In South Africa

—Lawrence Long, Mhairi Maskew, Ian Sanne, Francois Venter, and team; In Kenya—Isaac Tsikhutsu, Margaret Bii, and team

Funders• NIH’s National Institute of Allergy and Infectious Diseases• PEPFAR• Bill & Melinda Gates Foundation