Lessons from an eight-country community health data harmonization collaborative.

Area of Science:

• Global Health
• Health Systems Research
• Implementation Science

Background:

• Community health workers (CHWs) have a long history of improving healthcare access globally.
• Existing guidelines highlight gaps in evidence regarding CHW program design and quality of care.
• Routine data collection offers untapped potential for analyzing and improving CHW programs.

Purpose of the Study:

• To describe a data harmonization and pooling collaborative for CHW programs.
• To enable cross-site learning and identify effective CHW program design practices.
• To create a multi-country network for strengthening data and health information systems.

Main Methods:

• A collaborative approach involving organizations from the Community Health Impact Coalition.
• Data harmonization and pooling across multiple countries and WHO regions.
• Utilizing outlier analysis to identify and propagate quality-enhancing design practices.

Main Results:

• Establishment of a data harmonization and pooling collaborative.
• Early findings and lessons learned from the collaborative process.
• Identification of directions for future research in CHW program optimization.

Conclusions:

• Data harmonization and pooling are crucial for learning from CHW programs.
• Collaborative efforts can strengthen health information systems and improve care quality.
• Further research is needed to fully leverage routine data for CHW program enhancement.