Talk given to BU/Brown CFAR social and behavioral core, Feb 1, 2017

1. 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

2. Today’s talk:
• The problem: Inefficient ART initiation
• A solution: RapIT
• The problem with the solution: Cost and cost-effectiveness
• A new solution: SLATE

3. The Problem: Inefficient ART Initiation

4. 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

5. 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

6. 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 session
Visit 5
• Conduct physical examination
• Dispense ARVs
Visit 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…

7. A Solution:

8. 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

9. 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

10. 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

11. The Problem with the Solution:
Cost and Cost-Effectiveness

12. 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

13. $319
$487
$738
$451
$505
$707
$0
$100
$200
$300
$400
$500
$600
$700
$800
Per patient enrolled Per patient suppressed Production cost
Costperpatientover10-monthperiodfollowingstudyenrollment
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 nurse
Results: Cost Per Outcome
$132
$18
-$31

14. 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

15. A New Solution:
SLATE

16. 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

17. 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

18. 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

19. 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

20. Thanks and Acknowledgements
Participants
• Study patients and study clinic operations managers and staff
• City of Johannesburg, Gauteng Department of Health, and Kenya Ministry of
Health
Collaborators
• 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