How to Scale-Down: Adapting a National Primary Health Care Measurement Tool to Subnational Governments
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Khalid, Maryam Jabeen
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CitationKhalid, Maryam Jabeen. 2020. How to Scale-Down: Adapting a National Primary Health Care Measurement Tool to Subnational Governments. Doctoral dissertation, Harvard T.H. Chan School of Public Health.
AbstractNearly half of the world’s population lacks access to essential primary health care, a problem that has negative cascading effects on population health. This is further exacerbated by a lack of adequate data that both describes countries’ health systems and is required for effective health care reform. Access to clear, actionable data allows policymakers to better understand gaps in the system and make targeted improvements.
In light of this problem, in 2015, the Bill & Melinda Gates Foundation, World Bank, WHO, Ariadne Labs, and Results for Development founded the Primary Health Care Performance Initiative as a multi- year, multi-million-dollar investment in improving primary health care provision and measurement. One component of this initiative, and the focus of this research, is Ariadne Labs’ Progression Model. The Model is a mixed methods tool for low-and-middle-income national governments that measures health governance, system inputs, and population health. The Progression Model has been utilized by 11 countries and is proving valuable in summarizing previously uncollected data and prompting conversations on primary health care reform. Yet, many large countries with diverse populations find that nationally aggregated data lacks the utility and granularity required to develop effective policies for the subnational level. Furthermore, little is known about subnational governments’ authority over primary care provision and their ability to effect changes. These countries require an adapted version of the Progression Model based upon subnational data.
This DrPH dissertation attempts to address these gaps by:
1) Developing a subnational classification structure to understand which layers of government have authority over certain indicators.
2) Providing recommendations for improving the Progression Model at the subnational level.
This work was conducted remotely from Boston, Massachusetts, with stakeholders in 10 countries who implemented the Progression Model. I drew from qualitative research methods and realist evaluations to develop recommendations for adapting this work to the subnational level. I conducted Health System Assessments to understand authority dynamics in each country and created subnational classification structures. The two most significant subnational categories were classified as Consulted and Directed, terms that indicate the varying degrees of control that subnational governments exert over primary health care.
Citable link to this pagehttps://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37365690