Presentation on theme: "Measuring to Manage Progress toward Universal Health Coverage Ben Bellows On behalf of the Social Franchise Metrics Working Group NHIS 10 th Anniversary."— Presentation transcript:
Measuring to Manage Progress toward Universal Health Coverage Ben Bellows On behalf of the Social Franchise Metrics Working Group NHIS 10 th Anniversary International Conference on UHC Accra
UHC is multidimensional & aspirational Access: Expand coverage to wider population Scope: Improve quality & quantity of health services offered Financial protection: Improve size of subsidies or reduce informal charges
Access is far from universal in 54 LMIC Of 12 MNH interventions in a review of public data across 54 countries, family planning was the third most inequitable *Barros, A. J. D., Ronsmans, C., et al. (2012). “Equity in maternal, newborn, and child health interventions in Countdown to 2015: a retrospective review of survey data from 54 countries”. Lancet, 379(9822), 1225- 33.
Limited financial protection is common in 51 LMIC* 13–32% of household expenditures over 4 weeks went to healthcare 25% poor households incurred potentially catastrophic healthcare expenses >40% of households used savings, borrowed money, or sold assets to pay for care 41-56% of households spent 100% of health care expenditures on medicines *Wagner, Graves, Reiss, LeCates, Zhang, Ross-Degnan. 2011. “Access to care and medicines, burden of health care expenditures, and risk protection: Results from the World Health Survey” Health Policy. 100(2-3):151-158
Selected constructs and metrics for UHC measurement Quality of care: Donabedian framework (structure, process, outcomes) Investment in facility infrastructure Financial protection: Out-of-pocket spending on health paid for by the patient at the point of service Proportion of household consumption that is spent on healthcare Equitable access: Geographic proximity Above or below a poverty line Member of a wealth quintile
Preferred characteristics in a UHC equity measure Program Managers Quick, inexpensive to collect Easy to interpret by managers and field staff Agency Headquarters Standardized & comparable nationally Easy to explain to policy makers Other Stakeholders Comparable internationally Clients Transparent, trustworthy, quick application process Time-delimited membership Recognition of solidarity Recourse for appeal
Pilot study: Find a good routine, monitoring equity indicator MPI dismissed: not feasible to collect PPI and Wealth Index piloted in 5 countries in 2012 as part of franchise client exit interviews Results compared against selection criteria Progress out of Poverty Index (PPI) Wealth Index (WI) Multi- dimensional Poverty Index (MPI)
QuintileIndiaMadagBeninDRCMali n=797n=853n=535n=242n=293 1 (Poorest)220.127.116.110 2 (Poorer)18.104.22.1680 3 (Middle)21.725.44.300.3 4 (Richer)15.338.622.214.171.124 5 (Richest)12.724.676.890.985.7 Results & indicator attributes Wealth Index Relative measure Uses DHS data to compare client sample to national wealth quintiles Low-cost because DHS data is publicly available PPI Absolute measure A sset list gives likelihood that a client is under $1.25/day poverty threshold Expensive: unique asset weights developed for each country Only 6% of Benin franchise clients are from the bottom 40% of the population Threshold ClientsBeninPakistanPhilippinesVietnam $1.25/da y Franchise19%17% 8% National47%21%18%17% $2.50/da y Franchise61%72%51% National75%60%42%43% 19% of Benin franchise clients living under the $1.25/day threshold vs. 47% of the national population BOTH METRICS GIVE SIMILAR RESULTS
Selection criteria CriteriaPPIWealth Index Easy to Collect and Interpret Easy to collect Easy to calculate Easy to interpret poverty threshold Easy to collect Difficult to calculate Quintiles widely used/understood Low Cost $20,000-$25,000 per country Requires some upkeep costs Inexpensive Based on publicly-available DHS Comparable to National Context Percent of clients under poverty line easily comparable to national poverty rate Difficult/impossible subgroup analysis e.g.: just urban, or just FP clients Wealth quintiles accurate and validated comparison to national distribution Easy subgroup analysis Comparable Across Countries Percentage of clients under $1.25/day standard across countries Can discuss percentage of clients that fall within bottom 40%, but measure is relative to a country
Using Wealth Index routinely Randomly select NHIS facilities or enrollment centers Conduct exit surveys among clients 20 questions about household characteristics Adds approximately 10 minutes to each interview Centralized data analysis in M&E unit – takes about 8 hours Build capacity through a tool kit and standard syntax files Conduct surveys on quarterly or semi-annual basis
Uganda & Kenya: Equity targeting for program enrollment Uganda & Kenya voucher programs Every client identified in the community using a short targeting tool Voucher expires after a year and can only be used for one service package.
Respondents who had ever used the HealthyBaby voucher in Uganda (2010- 2011)
Conclusions: Active equity targeting is key component of UHC Tools exist that can cost-effectively identify the poor for enrollment who, in the absence of the active identification, would not have become NHI members Monitor samples of clients for reporting against performance targets Use for beneficiary identification and enrollment Consider: Are other exemptions as effective to achieve the same objective?
Thank you Social Franchising Metrics Working Group Bill & Melinda Gates Foundation DKT International Planned Parenthood Federation Johns Hopkins Marie Stopes International Population Services International Rockefeller Foundation Population Council University of California San Francisco USAID World Health Partners