Effectiveness of Different Adherence Support Program Models in Helping Clients Adhere to HAART

1. Effectiveness of Different Adherence Support Program Models in Helping Clients Adhere to HAART Ruth Finkelstein, ScD and HRSA SPNS Adherence Support Evaluation Collaboration The New York Academy of Medicine New York, New York Funding for this study provided by: Health Resources and Services Administration Grant # 1H97HA 00128 – 01

2. HRSA SPNS ADHERENCE SUPPORT EVALUATION COLLABORATION CO-AUTHORS Ruth Finkelstein, ScD, The New York Academy of Medicine Lois Eldred, DrPH, HIV/AIDS Bureau, HRSA Ricardo Alvarez, MD, Mission Neighborhood Health Center G. Stephen Bowen, MD, North Broward Hospital District Adan Cajina, MS, HRSA Daniel D. Ciccarone, MD, Urban Health Study, University of California, San Fransisco John Dougherty, PhD, Multnomah County Health Department Barbara Hanna, MD, AIDS Services Center Lisa R. Hirschhorn, MD, MPH, Dimock Community Health Center Mary K. Irvine, MPH, Mailman School of Public Health, Columbia University Sharon B. Mannheimer, MD, Harlem Hospital Center Joanne E. Mantell, PhD, MSPH, The New York Academy of Medicine Richard Moore, MD, Johns Hopkins University School of Medicine Rajat Mukherjee, MS, The New York Academy of Medicine Linda M. Mundy, MD, Washington University School of Medicine Emily Richie, MD, Chase Brexton Health Services, Inc. Mark Waters, RN, MPH, New York State Department of Health AIDS Institute Tracey E. Wilson, PhD, SUNY Downstate Medical Center

3. BACKGROUND • Adherence to HAART is critical for successful HIV outcomes defined as HIV suppression, immune restoration and survival. • HIV practice sites across the United States have struggled to implement adherence programs that meet the multifaceted needs of the clients they serve. • Some successful strategies to promote and support adherence have been described, including directly observed therapy (DOT), pharmacist interventions, psycho-educational interventions and electronic reminders. • However, most studies of the effectiveness of adherence support have had small sample sizes, short follow-up, often in specific sub-populations.

4. OBJECTIVE To assess the effectiveness of different adherence support programs using 12 months of longitudinal data from participants in 11 adherence support evaluation programs funded by the DHHS - Health Resources Services Administration (HRSA) Special Projects of National Significance (SPNS) program.

5. METHODSStudy Design: Cross-Site Evaluation • Mixed methods approach incorporating longitudinal assessment; uniform measures of client characteristics and outcomes; intervention characteristics; and process documentation of services used. • Recruitment and enrollment conducted locally at each SPNS site from July 2000 through April 2002. • Prospective enrollment of clients to the adherence support program, but not necessarily to other services at the site or to HAART.

6. METHODSStudy Design: This Analysis • Longitudinal analysis of adherence and viral load for cross-site evaluation participants with baseline assessments, and at least 3 of 4 possible quarterly assessments through 12 months. • Adherence support model identified by structured qualitative site assessment coded into discrete “program variables” to describe the intervention frameworks, services, settings, and staffing.

7. METHODSSample Clients with baseline assessments and at least 3 quarterly follow-ups. N = 670 Sites: Health Services Center, Inc., Hobson City, AL Chase Brexton Health Services, Inc., Baltimore, MD Dimock Community Health Center, Roxbury, MA Harlem Hospital Center, New York, NY Helena Hatch Special Care Center, Washington University, St. Louis, MO Johns Hopkins University School of Medicine, Baltimore, MD Mission Neighborhood Health Center, San Francisco, CA Multnomah County Health Department, Portland, OR SUNY Downstate Medical Center, Brooklyn, NY North Broward Hospital District, Ft. Lauderdale, FL Urban Health Study, San Francisco, CA

8. METHODSData Collection Quarterly Client Assessment • A common interviewer-administered questionnaire developed by CASE and program investigators to collect participant self-report data at baseline, 3,6,9 and 12 months of follow-up. • Data included demographics: behavioral variables including substance use, self efficacy, HIV disclosure and support, and HAART adherence; clinical data including recent hospitalizations, mental health diagnosis, depression assessment, and health status. • Interviewers at each site were trained by CASE to ensure standardization

9. METHODSData Collection (continued) Quarterly Chart Abstraction • Chart abstractions conducted at sites within 30 days of each interview to collect laboratory data(CD4 count, HIV RNA level) and prescribed ART medication data Encounter Data • Recorded services, provider characteristics, and visit length Qualitative Site Interview • Used by CASE evaluation staff to conduct on-site interviews to collect individual program variable data to be used for classification of adherence support programs by type of services provided

10. METHODS Adherence Support Program Models Coded from site self-assessment and interview • Peer Support: a main program component is one on one peer support from trained HIV-infected peer workers • Readiness Training: a main program component is focused on preparing participants before starting a new regimen • Medication Pickup: a main component is on-site pick up of medications (usually including pill box packing, counseling, review) Note: other program models include case management and DOT. However, neither can be included in this analysis due to lack of variability in the sample.

11. Adherence Missed dose in last 3 days (self report) >1 missed dose in last 3 days is non-adherence % adherence calculated by number of doses taken divided by number prescribed (self-report) Viral Load HIV RNA copies/ml from medical record within 30 days of interview HIV RNA <400 copies/ml defined as undetectable METHODSMeasures

12. METHODSData Analysis • Generalized Estimating equation (GEE) methodology was used to model the logit of missed doses and undetectable viral load for different program models. • Odds ratios ( with 95% confidence intervals) were estimated to compare different client groups in different program models. • In each case, all clients in a particular program model were compared to all clients not in that program model. • All statistical analyses were carried out on SAS V.8, using PROC GENMOD for fitting GEE models. • Association with missing data patterns were tested in the GEE models.

13. RESULTSSample Description

14. Different Trajectories for Log Viral Load Based On HAART Experience at Baseline Salvage

15. Odds Ratio Estimates Group Odds Confidence P Value Ratios Limits Naive vs. Experienced 1.2 ( 1.2047, 1.2378 ) 0.3542 Salvage vs. Experienced 0.5 ( 0.4941, 0.5062 ) 0.0003 Naive vs. Salvage 2.4 ( 2.4018, 2.4821 ) 0.0007 Odds Ratio of Achieving Undetectable Viral Load Over Time for Three Groups

16. Odds Ratio Estimates Time Odds Confidence P Value Ratios Limits 3 Month vs. Base 1.6 ( 1.5698, 1.5979 ) 0.0012 6 Month vs. Base 1.7 ( 1.6591, 1.6875 ) 0.0001 9 Month vs. Base 1.7 ( 1.6402, 1.6694 ) 0.0003 12 Month vs. Base 1.8 ( 1.8150, 1.8493 ) <0.0001 Odds Ratio of Achieving Undetectable Viral Load Over Time

17. Odds Ratio Estimates Adherence Odds Confidence P Value Group Ratios Limits Not Missed vs. 1.5 ( 1.4961, 1.5185 ) 0.0005 Missed Odds Ratio of Achieving Undetectable Viral Load Over Time

18. Mean Adherence by HAART Experience at Baseline Salvage

19. Adherence Support Models Number of Sites* Total Clients Peer 4 215 Readiness 6 382 Core Med Pickup 7 322 Adherence Support Program Models * Models are not mutually exclusive, so neither number of sites nor number of clients is additive.

20. Evidence Regarding Effectiveness of Peer Program: Log VL

21. Odds Ratio Estimates Program Odds Confidence P Value Model Ratios Limits Peer vs. Not Overall 2.3 ( 1.5044, 3.4473 ) < 0.0001 Baseline 1.6 ( 1.5867, 1.6491 ) 0.1184 3 Months 3.9 ( 3.8556, 3.9855 ) < 0.0001 6 Months 2.4 ( 2.4073, 2.4876 ) 0.0006 9 Months 2.3 ( 2.2355, 2.3155 ) 0.0033 12 Months 1.7 ( 1.7062, 1.7642 ) 0.0385 Odds Ratio of Achieving Undetectable Viral Load Over Time: Peer Program

22. Mean Adherence Change Over Time: Peer Program

23. Odds Ratio Estimates Program Odds Confidence P Value Model Ratios Limits Peer vs. Not Overall 1.0 ( 0.6570, 1.6493 ) 0.8643 3 Months 1.6 ( 1.5332, 1.5929 ) 0.1428 6 Months 0.9 ( 0.9132, 0.9509 ) 0.8625 9 Months 0.9 ( 0.9214, 0.9576 ) 0.8383 12 Months 0.9 ( 0.8424, 0.8745 ) 0.6082 Odds Ratio of Missed Dose: Peer Program

24. Evidence Regarding Effectiveness of Readiness Program: Log VL

25. Odds Ratio Estimates Group Odds Confidence P Value Ratios Limits Readiness vs. Not Overall 1.0 ( 0.6696, 1.4780 ) 0.9676 Baseline 0.5 ( 0.5186, 0.5383 ) 0.0318 3 Months 1.5 ( 1.4434, 1.4893 ) 0.1252 6 Months 1.2 ( 1.1897, 1.2277 ) 0.4501 9 Months 1.1 ( 1.0978, 1.1342 ) 0.6735 12 Months 0.9 ( 0.9040, 0.9332 ) 0.7379 Odds Ratio of Achieving Undetectable Viral Load Over Time: Readiness Program

26. Mean Adherence Change Over Time: Readiness Program

27. Odds Ratio Estimates Program Odds Confidence P Value Model Ratios Limits Readiness vs. 1.1 ( 0.6787, 1.7033 ) 0.7574 Not Readiness Odds Ratio of Missed Dose: Readiness Program

28. Evidence Regarding Effectiveness of Core Medication Pickup: Log VL

29. Odds Ratio Estimates Group Odds Confidence P Value Ratios Limits Core Medication Pickup vs. Not Overall 1.5 ( 0.9824, 2.2441 ) 0.0607 Baseline 3.0 ( 2.9766, 3.0972 ) 0.0005 3 Months 1.0 ( 0.9867, 1.0200 ) 0.9903 6 Months 1.5 ( 1.4698, 1.5176 ) 0.1155 9 Months 1.5 ( 1.4524, 1.5014 ) 0.1403 12 Months 1.1 ( 1.0565, 1.0922 ) 0.7872 Odds Ratio of Achieving Undetectable Viral Load Over Time: Medication Pickup

30. Mean Adherence Change Over Time: Medication Pickup

31. Odds Ratio Estimates Program Odds Confidence P Value Model Ratios Limits Core Medication Pickup vs. Not Overall 0.7 ( 0.4592, 1.0843 ) 0.1117 3 Months 0.4 ( 0.2111, 0.7097 ) 0.0022 6 Months 0.8 ( 0.4596, 1.3996 ) 0.4374 9 Months 0.9 ( 0.4753, 1.5224 ) 0.5859 12 Months 0.9 ( 0.5673, 1.5539 ) 0.8061 Odds Ratio of Missed Dose: Medication Pickup

32. LIMITATIONS • This analysis is based on program models as designed, not as delivered. • Future analyses will incorporate services received. • Program models are not mutually exclusive, so true comparisons between models are not possible in this analysis. • High rates of loss to follow up and sporadic participation (baseline enrollment is 1700; 12 month completion with 4 of 5 observations is 670). • Lack of randomization or control group (comparisons are between interventions).

33. CONCLUSIONS • This disadvantaged study population overall achieved some improvement in adherence and virologic suppression over the study period. • Some specific models appear to promote such improvement more quickly: peer support, medication pick up, and readiness training. • HAART experience and baseline adherence remain important predictors of adherence and viral suppression across all models of adherence support.

34. IMPLICATIONS • Next steps for data analysis include integration of services received. • Cross site evaluation allows us to assess the effectiveness of multiple interventions simultaneously. • It is helpful to begin adherence support in advance of medication prescription. • While adherence support is labor intensive, effective models are delivered by relatively inexpensive staff (peers, counselors, nurses).