Background: Community health workers (CHWs) are individuals who are trained and equipped to provide essential health services to their neighbors and have increased access to healthcare in communities worldwide for more than a century. However, the World Health Organization (WHO) Guideline on Health Policy and System Support to Optimize Community Health Worker Programmes reveals important gaps in the evidentiary certainty about which health system design practices lead to quality care. Routine data collection across countries represents an important, yet often untapped, opportunity for exploratory data analysis and comparative implementation science. However, epidemiological indicators must be harmonized and data pooled 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 Community Health Impact Coalition, a network of health practitioners delivering community-based healthcare in dozens of countries across four WHO regions.
Objectives: The goals of the Collaborative project are to; (i) enable new opportunities for cross-site learning; (ii) use positive and negative outlier analysis to identify, test, and (if helpful) propagate design practices that lead to quality care; and (iii) create a 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 pooling Collaborative, early findings, lessons learned, and directions for future research.
Keywords: COVID-19; Community health workers.