Reaching the Poor in Kenya through the Private Sector: Assessment of a network model for expanding access to reproductive health services Dominic Montagu, MPH, MBA, DrPH – UC San Francisco Martha Campbell, PhD – School of Public Health, UC Berkeley Julia Walsh, MD, MSc – School of Public Health, UC Berkeley Solomon Orero, MD – K-MET, Nairobi and Kisumu, Kenya

Intervention being assessed Network of 225 health service providers – –60 private practice –150 government –15 NGO and mission Organized by the nonprofit organization K-MET (originally the Kisumu Medical and Education Trust) Goal: Reduce maternal mortality by expanding access to family planning, post-abortion care, and safe early abortion services.

Rationale for K-MET network Kenya’s rural population (80% of total) has limited access to government health services. Private, for-profit health services already exist, already self-sufficient. In rural areas, these providers are primarily mid-level practitioners. Doctors tolerate the mid-level providers in rural areas.

Rationale… “…the main difference between the more and less poor in health is not in the likelihood of being ill but in the access to adequate treatment once ill.” D. Gwatkin, The Lancet commentary, Feb., For maternal mortality: Some critical RH services not available in public services – rural or urban WHO-World Bank meeting in Addis Ababa, February 2002, on human resources challenges for health systems – “The health system is more than the Government’s health services”

The research question Is it possible to expand access to reproductive health services through a network of private sector, for-profit providers without exacerbating inequity?

Methodology Survey data from 102 members of K-MET network and 50 non-member health providers Exit interviews with female clients of both groups of providers 212 household interviews to provide baseline information about the local community Assess the relationship between wealth and the use of member or non-member providers

Weighted asset ownership scores as a proxy measure of wealth Data were collected on water, sanitation, fuel sources, home building materials, and appliances. These variables are compiled to calculate a weighted asset ownership score for each participant as a proxy measure of household wealth. Comparison of wealth distribution and other socioeconomic factors between clients of K-MET members, clients of non-members, and the general community.

Summary Asset Scores – urban/rural

Regression of asset ownership among clients and households

Wealth score graphs, urban and rural Non-member clients Member clients Households

Wealth score graphs - rural only Non-member clients Member clients Households

Limitations of the study Small sample size Definitions of “rural” vary considerably, local definitions – vs. peri-urban Low reported reproductive health (RH) volume led to survey of all patients, not just RH.

Conclusions The experience of this network is that those served are middle-income clients of the communities served. Targeting the poor will therefore mean recruiting providers in poor areas. (K-MET is now recruiting mid-level providers.) Networking existing private, for-profit providers can expand access to reproductive health services without exacerbating inequity.

Policy implications The network (franchises) of private providers, if organized by an NGO, can be empowered to provide essential services. –Are financially self-sustaining –Do not need to be under government payrolls –Should be recognized by governments as a de-facto and valuable part of their “health system”

What is required? They need: Organization by an in-country NGO They need training (include in government’s own in-service training); low cost loans for equipment; supplies. Tight regulation by government health systems characterized by human resource shortages will not be possible – Regulate through professional associations. Enabling mode

Largest equity gap in public health Unsafe abortions Africa680 South and SE Asia280 Latin America120 Safe abortions (up to 12 weeks) 0.2 – 1.2 Alan Guttmacher Institute. Sharing Responsibility: Women, Society and Abortion Worldwide Deaths per 100,000 abortions

Worldwide there is a lifetime average of about one abortion per woman Abortion rate/1000 women Developed countries (most are safe) 39 Developing countries (most are unsafe) 35 AGI. Sharing Responsibility: Women, Society and Abortion Worldwide. 1999

One quarter of maternal deaths are abortion deaths, and “up to half of maternal mortality in Africa” is abortion related. Andrzej Kulczycki. The Abortion Debate in the World Arena (Mexico, Poland, Kenya) 21% of maternal deaths in Latin America are abortion related. AGI quoting Sing and Sedge 1997, Int’l FP Perspectives 23, % of 585,000 maternal deaths are abortion related (WHO, 1995 estimates) Portion of maternal deaths due to unsafe abortion

K-MET was established to reduce maternal mortality. Achieving Millennium Development Goals for reduced maternal mortality requires reducing the largest inequity in public health between rich and poor. Impact on the health, education and well-being of entire families. The health policy challenge