Private providers outnumber public providers in nearly all low- and middle-income countries (LMICs), delivering more than 50% of all healthcare services in Africa and Asia and more than 70% of all healthcare in the most populous countries in these regions: Nigeria, India, Pakistan, Bangladesh, and Indonesia [1]. Given private health facilities' large share of national health markets, LMIC national health systems are increasingly challenged to ensure these private providers sufficiently advance public health goals and adhere to national standards of care.
Social franchising is an innovative way of leveraging existing private sector infrastructure in LMICs to serve these national public health goals. To do so, social franchising promotes and improves clinical services among existing private providers through technical assistance and the application of social marketing techniques, a health intervention that has proven successful in fostering widespread access to and use of public health commodities in LMIC countries [2, 3]. As the fastest growing mechanism for engaging private practitioners in national public health initiatives, this social franchising approach is supported by a highly collaborative community of practice and a growing body of evidence that demonstrates social franchising's ability to improve service quality, increase access to essential services, and serve the poor [4, 5].
Social franchises engage existing for-profit, private clinics in a contractual exchange. The franchise program, nearly always run by a non-governmental organization (NGO), builds providers' capacity in new clinical methods, clinic management, business skills, and marketing and advertising techniques. Doing so builds demand for the health services offered. The program also organizes ongoing education and technical support as well as access to subsidized commodities and medicines which are often unavailable. Service quality is further supported through franchise-mediated linkages to private and national referral systems. In exchange, providers who enroll as franchisees commit to providing the health services that the implementing organization prioritizes, often low-margin services such as family planning or antenatal care, or socially unattractive services such as treatment for tuberculosis (TB) or HIV/AIDS. Franchise providers also are required to adhere to clearly defined clinical, reporting, and pricing practices. Increased client load, the resulting increase in profits, training opportunities, and reputation enhancement are the most frequently cited motivations for providers to join a social franchise [6, 7].
Begun in the early 1990s in Pakistan and Nepal, social franchising programs have steadily expanded throughout the developing world; as of June 2012, more than 50 programs operate in 35 countries [8] (see map, Figure 1). Initially, participating clinics and providers offered only family planning services, but many franchise service portfolios have expanded in recent years to include pediatric and maternal care as well as infectious disease testing and treatment, among others. More than half of the world's social franchise programs now offer a range of non-family planning services, and the number of program areas addressed by each franchise is growing each year [8]. While social franchises are often linked to large-scale social marketing programs which promote and distribute non-clinical health commodities (e.g., condoms or mosquito bednets) through retail outlets, the franchises themselves are, by definition, focused on clinical service delivery. Currently, two large international NGOs, Population Services International (PSI) and Marie Stopes International (MSI), operate or support the majority of global social franchise programs, 25 and 10 programs respectively [9, 10].
The growth in the number of programs has led to the development of a global community of practice among social franchisors. Coordinated by the University of California, San Francisco (UCSF)'s Global Health Group, this network of social franchising implementors facilitates information exchanges and supports almost all of the known social franchising programs, compiling data annually about its members in a Compendium of Clinical Social Franchising Programs [8, 11]. The Social Franchising Compendia are comprised of both large and small franchise programs. Large programs are defined as reporting an operating budget of more than $500,000 per year and including more than 50 member clinics. From 2010-2011, the Compendia gathered data on 58 social franchise networks, spanning Asia, Africa, and Latin America.
Increased confidence in this service delivery model on the part of donor agencies and NGOs accounts, in part, for the rapid expansion of social franchising. These stakeholders believe that franchises increase access to important clinical services by extending the geographic reach of the government healthcare system. Related clinical service models, such as NGO delivery or one-time training programs, face challenges in providing widely distributed services. It can be difficult for these models to meet high quality standards at outlets while offering only a low volume of services to a small catchment area and patient base. In contrast, by leveraging existing infrastructure and in situ skilled providers, social franchise networks are theoretically able to assure quality at comparatively low cost, even in low volume settings [2].
As with any health intervention, understanding the health impact of social franchising programs is essential, to inform decision making and to demonstrate the viability and value of this innovative approach. Currently, programs track a number of service delivery measures: the number of patient visits, not tracked by individual patients, for any cause or service (called "patient volume" hereafter); the number of clinics operating (called "number of outlets" hereafter); and (rarely) the number of prevention or treatment interventions received by patients (called "services provided" hereafter). Family planning-focused programs frequently track and report CYPs, a measure of projected impact that can be applied to all family planning methods based on weights to approximate the number of years a method safeguards against pregnancy and the number of products or services provided. For example, 120 condoms are considered to protect the couple from pregnancy for one year, and are thus, equal to one CYP, as are 13 cycles of monthly contraceptive pills, or .26 of a 5-year implant. (Note that the average implant is estimated to provide only 3.8 CYPs, not five, because some 5-year implants are removed early; hence .26 implants leads to one CYP.) [12].
These process measures are widely acknowledged as crude and poorly correlated with the true health impact that these programs likely achieve [13]. Patient volume and number of outlets have inherent problems: the former includes no information on severity of disease, while the latter does not reflect information on the patients served or the types of illnesses and health conditions treated [14]. Although the CYP metric is a good aggregate measure of family planning program projected impact, it is a metric of protection, not health impact, and it is limited to one program area only. As social franchises increasingly expand their portfolio of services beyond family planning, CYPs will capture only a small portion of all care offered.
Program managers and donors currently seek more robust measures of program impact, both to benchmark program performance against appropriate comparators, and to track year-to-year improvement [15–18]. A standardized metric for projected health impact would enable these program comparisons and allow for more accurate assessments of social franchising program variations, after accounting for changes in population health and service delivery. Such a method would also provide a basis for more accurate analysis of the cost-effectiveness of complex delivery systems and programs.
An existing metric, DALYs averted, offers promise as an impact measure of social franchising programs. This metric is based on the DALY, the standard unit representing disease burden in a population, originally developed for the World Bank in 1990 and adopted by the World Health Organization (WHO) in 2000 as part of the Global Burden of Disease Study [19, 20]. Disease burden can be expressed as the number of DALYs lost due to a health condition, either from premature death (mortality) or disability (morbidity), as compared to an ideal life expectancy [20]. The DALYs averted measure, then, denotes the disability-adjusted life years that are not lost - or, are averted - as a result of a health intervention. The attraction of using a metric based on the DALY is that the DALY incorporates both mortality and morbidity, it is widely used by global development agencies, it enables comparison across countries on an standardized scale, and it can be aggregated or disaggregated by disease [21, 22].
The DALYs averted metric is intended conceptually to be the inverse of DALYs in burden and thus benefits from a growing understanding of what a DALY, as a unit, is. Such attributes allow decision makers to use DALYs for comparing the overall burden of disease due to TB, malaria, diabetes, or other illnesses. Conversely, decision makers can also compare projected DALYs averted for understanding the potential to reduce burden with specific interventions, and to allocate resources based on these data.
Despite its established importance in global burden of disease assessment, the DALY has only recently been adapted into a measure of the impact of healthcare interventions by service providers. Beginning in 2007, PSI initiated the use of an impact metric based on the DALY. In each of the 58 countries where PSI operated, researchers calculated a country- and disease-specific DALY coefficient for each prevention or treatment intervention [23]. These models project the impact of specific products and services across a wide range of program areas, such as male circumcision, malaria rapid diagnostic test kits, intrauterine device (IUD) insertions, and pneumonia treatment [24]. Note that PSI bases the DALYs averted metric on models of health impact which are necessarily different from the WHO and World Bank burden models of DALYs. PSI has also never used age weighting in DALY calculations.
PSI DALYs averted models are tailored to different diseases and interventions. As a generalized description, DALYs averted are calculated based on reduced risk in a population and the corresponding years of healthy life preserved. Using country-specific population and health data, the reduced risk of death is calculated by applying the demonstrated effectiveness of prevention or treatment to baseline disease burden. To calculate impact in DALYs averted, the reduction in mortality is multiplied by the number of years between average age at death for the targeted disease and ideal life expectancy. The ratio of years lost from death to years lost from disability is used to calculate the additional years that would be lost to disability for the same disease. The result of this calculation is a DALYs averted coefficient, the impact of a single product or service in years of healthy life preserved. Other publications describe the PSI methodology in more detail [24].
Each of PSI's DALYs averted models projects health impact from the use of one service or product delivered (e.g., a safe child delivery or the sale of a packet of oral rehydration salts (ORS) for pediatric diarrhea), producing a coefficient for this unit. Besides being product- or service-specific, this coefficient is also country-specific, as the number of DALYs averted by any treatment or service varies according to the national burden of disease. For example, in a country with a low malaria burden, the sale of a long-lasting, insecticide-treated net (LLIN) will have a small coefficient whereas this coefficient will be much larger in a country with higher incidence and widespread malaria. Therefore, the DALYs averted coefficient for an LLIN in Nicaragua will differ sharply from that used for an LLIN in Benin. To generate estimates of the number of DALYs averted by a specific service or product intervention, the coefficient is then applied to the total number of services or products distributed within the country during the past year. For example, the LLIN coefficient for Benin is multiplied by the number of LLINs distributed, resulting in the total number of DALYs averted by the LLIN intervention in Benin.
The final model outputs for each intervention, DALYs averted, can serve as a program management tool as these outputs allow comparisons of impact between countries and between different interventions offered within each country program. Organizations can use the DALYs averted metric to benchmark program impact and determine program emphasis and design, as described elsewhere [25]. Thus far, both PSI and MSI have adopted DALYs averted for internal program management use; other organizations are considering doing the same.
For managing social franchising programs, the DALYs averted metric would be useful for projecting program impact, by applying the coefficients to reported service delivery data, on a monthly, quarterly, or annual basis. DALYs averted can be considered for specific interventions within a health program area (e.g., HIV or family planning) for a social franchise network, country, or region. To understand the overall health impact of a social franchise program, the DALYs averted across all individual products or services can be summed. The resulting aggregate will show an estimate of the health impact of family planning services as well as the social franchising program's impact on malaria, diarrhea, and other targeted health conditions. With this aggregate, comparisons of overall effect between social franchising programs managed by different implementing organizations and operating in different national contexts are possible because DALYs averted adjusts for the burden of disease in each country.
Study goals
This study seeks to demonstrate the application of a single, comprehensive health impact measure to social franchising programs. Our principal goal is to present the use of DALYs averted alongside currently used program output and impact measures - patient volume, number of outlets, number of services provided, and CYPs - to track progress across a global set of social franchising networks. We describe changes in social franchising impact over two years, 2010 to 2011, and highlight differences by region and program area. We also review the strengths and limitations of each of the individual metrics currently used by social franchising programs. In doing so, we discuss opportunities to incorporate DALYs averted as a social franchising metric, reviewing the programmatic decisions that could be informed by this metric. We hope this study will provide insight into the benefits and challenges of establishing a standardized impact measurement system for service delivery programs run by multiple implementing organizations.