PROQUEST DTG-High-Quality Primary Health Care: User and Facility Determinants of Best-in-Class Performance

Lewis, Todd (2021) PROQUEST DTG-High-Quality Primary Health Care: User and Facility Determinants of Best-in-Class Performance. Post-Doctoral thesis, Harvard University.

Text High-Quality_Primary_Health_Ca.pdf - Published Version Restricted to Registered users only Download (10MB)

Abstract

Primary care is the foundation of a high-functioning health system and is critical to addressing the growing double burden of disease facing low- and middle-income countries (LMICs). Despite this, primary care services are often of insufficient quality to optimize health. By one estimate, poor quality health systems result in more than 8 million deaths per year in LMICs, many from conditions treatable by primary care. While quality is low overall, some health facilities outperform their counterparts in similar contexts. This suggests that higher quality of care is attainable in many settings within existing resource constraints. However, more evidence is needed on the factors that distinguish best and worst performance among health facilities and how populations can extract better care from the health system. The three chapters that follow investigate variations in primary care quality to understand how health system stakeholders can elevate performance. I used multiple methodologies to develop a rich set of insights into performance, including quantitative analysis to signal potential drivers of quality and qualitative analysis to explore how they operate. Chapter 2 used data from Demographic and Health Surveys in 16 countries in sub-Saharan Africa to show that more empowered mothers of children with fever and malaria may be able to obtain better quality care for their children. In Chapters 3 and 4, I used positive deviance analysis within an explanatory sequential mixed methods framework to understand the factors that distinguish best and worst primary care performance. Chapter 3 is a large, multi-country quantitative analysis of Service Provision Assessment data from seven LMICs. Results identified governance, workforce, and community engagement factors that predicted best versus worst performance among hospitals and clinics. Chapter 4, a qualitative analysis that aimed for deep insight into performance in a particular health system, used primary data from interviews with leaders and clinicians to explore the mechanisms that distinguished best performance in primary health care centers in Nepal. Findings across papers showed that effective facility management, engagement of local leadership, and community accountability were key drivers of facility performance. Together, these papers demonstrate that strong health system management and engagement of users and communities is critical for optimizing health in LMICs. Findings can be used to identify scalable practices that can empower users, elevate primary care performance, and improve service quality in resource-constrained health systems.

Actions (login required)

View Item