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Health service quality in 2929 facilities in six low-income and middle-income countries: a positive deviance analysis
Authors: Todd P Lewis, PhD., Margaret McConnell, PhD., Amit Aryal, MPH., Grace Irimu, PhD., Suresh Mehata, PhD., Mwifadhi Mrisho, PhD., and Prof Margaret E Kruk, MD
Source: Lancet Global Health , 11
Topic(s): Data models
Country: Africa
  Congo Democratic Republic
Latin American/Caribbean
Published: JUN 2023
Abstract: Background: Primary care is of insufficient quality in many low-income and middle-income countries. Some health facilities perform better than others despite operating in similar contexts, although the factors that characterise best performance are not well known. Existing best-performance analyses are concentrated in high-income countries and focus on hospitals. We used the positive deviance approach to identify the factors that differentiate best from worst primary care performance among health facilities across six low-resource health systems. Methods: This positive deviance analysis used nationally representative samples of public and private health facilities from Service Provision Assessments of the Democratic Republic of the Congo, Haiti, Malawi, Nepal, Senegal, and Tanzania. Data were collected starting June 11, 2013, in Malawi and ending Feb 28, 2020, in Senegal. We assessed facility performance through completion of the Good Medical Practice Index (GMPI) of essential clinical actions (eg, taking a thorough history, conducting an adequate physical examination) according to clinical guidelines and measured with direct observations of care. We identified hospitals and clinics in the top decile of performance (defined as best performers) and conducted a quantitative, cross-national positive deviance analysis to compare them with facilities performing below the median (defined as worst performers) and identify facility-level factors that explain the gap between best and worst performance. Findings: We identified 132 best-performing and 664 worst-performing hospitals, and 355 best-performing and 1778 worst-performing clinics based on clinical performance across countries. The mean GMPI score was 0·81 (SD 0·07) for the best-performing hospitals and 0·44 (0·09) for the worst-performing hospitals. Among clinics, mean GMPI scores were 0·75 (0·07) for the best performers and 0·34 (0·10) for the worst performers. High-quality governance, management, and community engagement were associated with best performance compared with worst performance. Private facilities out-performed government-owned hospitals and clinics. Interpretation: Our findings suggest that best-performing health facilities are characterised by good management and leaders who can engage staff and community members. Governments should look to best performers to identify scalable practices and conditions for success that can improve primary care quality overall and decrease quality gaps between health facilities.