Applying the disability-adjusted life year to track health impact of social franchise programs in low- and middle-income countries

BACKGROUND Developing effective methods for measuring the health impact of social franchising programs is vital for demonstrating the value of this innovative service delivery model, particularly given its rapid expansion worldwide. Currently, these programs define success through patient volume and number of outlets, widely acknowledged as poor reflections of true program impact. An existing metric, the disability-adjusted life years averted (DALYs averted), offers promise as a measure of projected impact. Country-specific and service-specific, DALYs averted enables impact comparisons between programs operating in different contexts. This study explores the use of DALYs averted as a social franchise performance metric. METHODS Using data collected by the Social Franchising Compendia in 2010 and 2011, we compared franchise performance, analyzing by region and program area. Coefficients produced by Population Services International converted each franchise's service delivery data into DALYs averted. For the 32 networks with two years of data corresponding to these metrics, a paired t-test compared all metrics. Finally, to test data reporting quality, we compared services provided to patient volume. RESULTS Social franchising programs grew considerably from 2010 to 2011, measured by services provided (215%), patient volume (31%), and impact (couple-years of protection (CYPs): 86% and DALYs averted: 519%), but not by the total number of outlets. Non-family planning services increased by 857%, with diversification centered in Asia and Africa. However, paired t-test comparisons showed no significant increase within the networks, whether categorized as family planning or non-family planning. The ratio of services provided to patient visits yielded considerable range, with one network reporting a ratio of 16,000:1. CONCLUSION In theory, the DALYs averted metric is a more robust and comprehensive metric for social franchising than current program measures. As social franchising spreads beyond family planning, having a metric that captures the impact of a range of diverse services and allows comparisons will be increasingly important. However, standardizing reporting will be essential to make such comparisons useful. While not widespread, errors in self-reported data appear to have included social marketing distribution data in social franchising reporting, requiring clearer data collection and reporting guidelines. Differences noted above must be interpreted cautiously as a result.