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Abstract Background With the 40th anniversary of the Declaration of Alma-Ata, a global effort is underway to re-focus on strengthening primary health care systems, with emphasis on leveraging community health workers (CHWs) towards the goal of achieving universal health coverage for all. Institutionalizing effective, sustainable community health systems is currently limited by a lack of standard metrics for measuring CHW performance and the systems they work within. Developed through iterative consultations, supported by the Bill & Melinda Gates Foundation and in partnership with USAID and UNICEF, this paper details a framework, list of indicators, and measurement considerations for monitoring CHW performance in low- and middle-income countries. Methods A review of peer-reviewed articles, reports, and global data collection tools was conducted to identify key measurement domains in monitoring CHW performance. Three consultations were successively convened with global stakeholders, community health implementers, advocates, measurement experts, and Ministry of Health representatives using a modified Delphi approach to build consensus on priority indicators. During this process, a structured, web-based survey was administered to identify the importance and value of specific measurement domains, sub-domains, and indicators determined through the literature reviews and initial stakeholder consultations. Indicators with more than 75% support from participants were further refined with expert qualitative input. Results Twenty-one sub-domains for measurement were identified including measurement of incentives for CHWs, supervision and performance appraisal, data use, data reporting, service delivery, quality of services, CHW absenteeism and attrition, community use of services, experience of services, referral/counter-referral, credibility/trust, and programmatic costs. Forty-six indicators were agreed upon to measure the sub-domains. In the absence of complete population enumeration and digitized health information systems, the quality of metrics to monitor CHW programs is limited. Conclusions Better data collection approaches at the community level are needed to strengthen management of CHW programs and community health systems. The proposed list of metrics balances exhaustive and pragmatic measurement of CHW performance within primary healthcare systems. Adoption of the proposed framework and associated indicators by CHW program implementors may improve programmatic effectiveness, strengthen their accountability to national community health systems, drive programmatic quality improvement, and plausibly improve the impact of these programs.

The emerging field of outbreak analytics calls attention to the need for data from multiple sources to inform evidence-based decision making in managing infectious diseases outbreaks. To date, these approaches have not systematically integrated evidence from social and behavioural sciences. During the 2018–2020 Ebola outbreak in Eastern Democratic Republic of the Congo, an innovative solution to systematic and timely generation of integrated and actionable social science evidence emerged in the form of the Cellulle d’Analyse en Sciences Sociales (Social Sciences Analytics Cell) (CASS), a social science analytical cell. CASS worked closely with data scientists and epidemiologists operating under the Epidemiological Cell to produce integrated outbreak analytics (IOA), where quantitative epidemiological analyses were complemented by behavioural field studies and social science analyses to help better explain and understand drivers and barriers to outbreak dynamics. The primary activity of the CASS was to conduct operational social science analyses that were useful to decision makers. This included ensuring that research questions were relevant, driven by epidemiological data from the field, that research could be conducted rapidly (ie, often within days), that findings were regularly and systematically presented to partners and that recommendations were co-developed with response actors. The implementation of the recommendations based on CASS analytics was also monitored over time, to measure their impact on response operations. This practice paper presents the CASS logic model, developed through a field-based externally led consultation, and documents key factors contributing to the usefulness and adaption of CASS and IOA to guide replication for future outbreaks.

The journey to universal health coverage (UHC) is full of challenges, which to a great extent are specific to each country. ‘Learning for UHC’ is a central component of countries’ health system strengthening agendas. Our group has been engaged for a decade in facilitating collective learning for UHC through a range of modalities at global, regional and national levels. We present some of our experience and draw lessons for countries and international actors interested in strengthening national systemic learning capacities for UHC. The main lesson is that with appropriate collective intelligence processes, digital tools and facilitation capacities, countries and international agencies can mobilise the many actors with knowledge relevant to the design, implementation and evaluation of UHC policies. However, really building learning health systems will take more time and commitment. Each country will have to invest substantively in developing its specific learning systemic capacities, with an active programme of work addressing supportive leadership, organisational culture and knowledge management processes.