Lessons from an eight-country community health data harmonization collaborative

Abstract

ABSTRACT Background: Community health workers (CHWs) are individuals who are trained and equipped to provide essentialhealth services to their neighbors and have increased access tohealthcare in communities worldwide for more than a century.However, the World Health Organization (WHO) Guideline onHealth Policy and System Support to Optimize CommunityHealth Worker Programmes reveals important gaps in theevidentiary certainty about which health system design practiceslead to quality care. Routine data collection across countriesrepresents an important, yet often untapped, opportunity forexploratory data analysis and comparative implementation science.However, epidemiological indicators must be harmonized and datapooled to better leverage and learn from routine data collection.Methods: This article describes a data harmonization and pooling Collaborative led by the organizations of the CommunityHealth Impact Coalition, a network of health practitioners deliveringcommunity-based healthcare in dozens of countries across fourWHO regions.Objectives: The goals of the Collaborative project are to; (i) enable new opportunities for cross-site learning; (ii) usepositive and negative outlier analysis to identify, test, and (if helpful)propagate design practices that lead to quality care; and (iii) createa multi-country ‘brain trust’ to reinforce data and health information systems across sites.Results: This article outlines the rationale and methods used to establish a data harmonization and poolingCollaborative, early findings, lessons learned, and directions forfuture research.