Abstract
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.
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