Is HIV/AIDS funding strengthening the health care system: a quasi-experimental study in Rwanda

1. Is HIV/AIDS funding strengtheningthe health care system: aquasi-experimental study in Rwanda Donald S. Shepard (Brandeis University) Peter Amico (Brandeis University) Wu Zeng (Brandeis University) Angelique K. Rwiyereka (Brandeis University) Carlos Avila (UNAIDS) Presented at AIDS2010, July 19, 2010 shepard@brandeis.edu Schneider Institutes for Health Policy, Heller School Brandeis University, Waltham, MA 02454-9110 USA Supported by UNAIDS 1

2. Background 1:crowd out or enhancement • HIV/AIDS services receive $10 billion annually in low- and middle-income countries • Despite need for AIDS resources, opposing effects on health system hypothesized • Crowd out: AIDS funding may displace some non-AIDS services through personnel transfers or effort reallocations • Enhancement: AIDS funding could improve non-AIDS services through better management, improved drug supply and logistics, more resources • Results may depend on country policies and timing

3. Background 2:international research Jeremy Shiffman (2006) – editorial hypothesized crowd out [Bulletin of WHO 84:923] Bongaarts & Over (2010) – non-AIDS services more cost-effective but integration not considered [Science 328:1359] 3

4. Background 3:Rwanda research Laurent Musango (2007) – descriptive study of entire health sector showed growth in many resources [Kigali: Rwanda School of Public Health] Jessica Price et al (2009) – no evidence of crowd out but examined only HIV/AIDS health centers [AIDS Care 21:608] No known empirical studies distinguish AIDS funding from general trends 4

5. Methods 1:matched design AIDS health centers (HCs): Randomly sampled 27 AIDS rural HCs with comprehensive HIV services, including anti-retroviral (ARV) therapy Control HCs: HCs with no HIV/AIDS services, selected from remainder of Rwanda’s 425 HCs Matched on aggregate score with type of ownership (public or non-governmental organization), location, rate of poverty in the district, type of incentive program (e.g., performance based financing) 5

6. Methods 2:non-AIDS indicators Inputs Number of HIV personnel Number of non-HIV personnel Outputs Vaccine doses: BCG, DPT, polio, measles, diphtheria Curative visits: children aged 0-5, children 6-14, people > 14 Hospitalization and child growth monitoring Indexes (preventive, curative) 6

7. Methods 4:analysis Descriptive analyses of indicators and indexes over time Regression (using started log) of individual and combined indicators with clustering with difference-in-differences Regression also evaluates other factors (e.g. enrollment in health insurance) 7

8. Methods 3: data 3 interviewers collected data from each HC and Ministry offices by year (2002 thru 2007) Data include both inputs and outputs for AIDS and non-AIDS services 26 HC pairs with complete data analyzed 8

9. Results 1: non-HIV personnel(average by type of HC) 9

10. Results 2: curative care visits (average by type of HC) 10

11. Results 3: Regression interactions 11

12. Results 4: summary • AIDS HCs had 2.7 (p<0.05) fewer staff working on non-HIV/AIDS services after ART services started • Nevertheless, most non-HIV services (9 out of 11) improved more in AIDS HCs than the control group • One of these improvements (BCG vaccination) was statistically significant • No non-HIV service experienced a significant reduction in output after HIV/AIDS programs started 12

13. Conclusions No support for dire predictions: Non-AIDS services grew at both AIDS and non-AIDS HCs Overall, no evidence of crowd out at HC level and mild support for enhancement Important health system benefit of Global Fund ATM funding: helped support community health insurance Limitations: Neither national level nor long run impacts assessed Strengths: Matched design with regression controls for general trends in health centers 13

14. Thank you Shepard@brandeis.edu 14