Lessons from an eight-country community health data harmonization collaborative

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.

KEYWORDS:

• Community health workers
• COVID-19

Responsible Editor

Jennifer Stewart Williams

Responsible Editor

Jennifer Stewart Williams

Acknowledgments

The authors of the study would like to acknowledge the CHWs and CHW supervisors for their continued service. We owe a debt of gratitude to all member organizations of the Community Health Impact Coalition for your efforts to do the uncomfortable work of transparency and collaboration. We thank the Ministries of Health in all the eight countries for their partnership.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethics and consent

Exempted, as not human subjects research: no individual-level or identifiable patient data were used.

Paper context

The WHO Guideline on CHWs revealed knowledge gaps about which health system practices promote quality care. Community Health Impact Coalition organizations deliver care in over 40 countries, representing an important learning opportunity. To leverage and learn from routine data, however, site-specific data must be harmonized and pooled. This article outlines (i) the rationale and methods used to establish a data harmonization and pooling Collaborative, (ii) early findings, (iii) lessons learned, and (iv) directions for future research.

Additional information

Funding

Focusing Philanthropy (no grant number), Patrick J. McGovern Foundation (no grant number).

Notes on contributors

Madeleine Ballard

All authors conceptualized and actively participated in the Collaborative described. MB and LW analyzed the initial indicator list. MB, HO, AM, and AY performed the initial analyses. MB, CW1, HO, and DR drafted the manuscript. FM, RD, DR, KL, EB, AR1, MA, MC, AW, and RW led data collection and substantially contributed to the interpretation of the results and drafting of the manuscript. All the authors reviewed, improved, and ultimately approved the manuscript.