Assessing technical efficiency of HIV prevention interventions in three sub-Saharan countries S Bautista-Arredondo, SG Sosa-Rubí, D Contreras-Loya, M Opuni, A Kwan, C Chaumont, J Condo, N Martinson, J Coetzee, F Masiye, S Nsanzimana, J Wang'ombe, K Dzekedzeke, O Galarraga, and R Wamai on behalf of the ORPHEA study team July · 2014
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Assessing technical efficiency of HIV prevention interventions in three sub-Saharan countries
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Assessing technical efficiency of HIV prevention interventions in three sub-Saharan
countries
S Bautista-Arredondo, SG Sosa-Rubí, D Contreras-Loya, M Opuni, A Kwan, C Chaumont, J Condo, N Martinson, J Coetzee, F Masiye, S Nsanzimana, J Wang'ombe,
K Dzekedzeke, O Galarraga, and R Wamai on behalf of the ORPHEA study team
July · 2014
Motivation
- Need for implementing HIV programs with higher efficiency- Maximizing value for money
- Lack of data on updated performance in the region- Previously published evidence suggested enormous
heterogeneity in HIV prevention costs and potential waste (PANCEA, 2002)
- Need to understand:- Current levels of efficiency- Determinants of more efficient performance
Information needs for optimizing HIV programs
- Allocation among interventions- Effectiveness data
- Allocation among populations/groups- Epidemiological and behavioral data
- Allocation among health inputs- Performance data (M&E)- Determinants of efficiency- Interventions to improve efficiency
- Which incentives work better and are more cost-effective?- How can M&E systems and changing in management practices can facilitate
more efficient results
THE ORPHEAPROJECT
Aims
• Research question– Which characteristics predict the most efficient performance in
the delivery of HIV services?
• Objectives– Measure and explain efficiency:
- To estimate the total costs and the average cost per output, at the facility level
- To estimate levels and determinants of efficiency
– Provide recommendations
HTCHIV testing and counseling
PMTCTPrevention of Mother-to-child
Transmission
Key hypotheses
- Heterogeneity of unit costs- High variability on average cost per service across facilities
- Possible to identify the role of determinants and constraints- Modifiable characteristics that predict higher efficiency - Environment in which facilities operate and make decisions - Not possible to
modify through interventions
- Overlap between economics and management - Looking at performance at the facility level: potential for improving efficiency
METHODS
Measuring Efficiency
• Four HIV prevention interventions: HTC, PMTC, MC, FSW
• Four African Countries: Kenya, Zambia, South Africa, Rwanda
• Outputs: all services produced in the previous fiscal year
• Inputs: staff, essential recurrent inputs and services, capital, training and
supervision
• Managerial and environmental characteristics: describing the environment
and constraints in which production decisions are made
- Identify constraints and determinants
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Constraints from the firm’s perspective in the short term
- Country/Location- Urban vs. rural setting- Funding sources- Facility type / Ownership - HIV/AIDS prevalence - Size of demand- Supply of services (utilities)
Determinants, can be adjusted at the facility-level
- Structure and governance- Training and staff composition- Management - Accountability- Incentives- Sanctions
Determinants of efficiency and constraints to more efficient performance
Microeconomic approach
- Micro-costing- One-year retrospective data collection - Effort to measure staff’s time allocation (Time-motion)- Measurement of quality using exit interviews, clinical vignettes
and the cascade approach- Data collection at different levels:Facility-level information
- Staff roster- Drugs and supplies- Utilities- Equipment and buildings
District-level information
- Training - Supervision
National-level information
- Salaries- Prices of supplies (HIV test
kits, ART)
Measuring quality
- Process quality using clinical vignettes and exit interviews
- Try to capture quality of the program through the outcome measures using a
“cascade” approach
- Reflect definition of “comprehensive” prevention packages
- Reflect hierarchy or sense of “effective” coverage
- Assumption: higher quality of services can be captured by higher success of programs in
achieving effective coverage
- Example: PMTCTPregnant women
tested for HIV
Pregnant women tested and positive for
HIV
Pregnant, HIV-positive women linked to ART
Estimating efficiency
- Estimation of total annual input costs – at the facility level
- Estimation of unit average cost per services along the HIV prevention
services cascade
- Correlation of unit average cost vs. scale of production, controlling for
quality
- Estimation of cost functions using a translog specification
- Include determinants and constraints of efficiency in a joint equations system
- Technical efficiency analysis using DEA or other methodology
RESULTS
Kenya, Rwanda and Zambia
Unit cost breakdown
HTC PMTCT
HTC Staff Composition PMTCT Staff Composition
Cost per client across the service cascadeHTC PMTCT
Average cost vs scale for two stages in the cascade
ORPHEA: Policy Implications
- Assessing the determinants of efficiency- Weak evidence of economies of scale in the first stage, much stronger in
the second stage- Supervision seems to have an important role increasing efficiency- Incentives and complex governing structures increase costs- Our results suggest that quality of services is not the most important
predictor of efficiency
- Three promising approaches- Measuring performance at the clinical level and revealing disparities- Fairly simple management training and interventions- Looking into the production function of services: staff compositions
Acknowledgements
- The ORPHEA study is supported by the Bill and Melinda Gates Foundation.
- We gratefully acknowledge the collaboration of our academic partners in Kenya, Rwanda, South Africa, Zambia and the United States.