Mind the Gap: Reflections on the future of data-driven Community Health Worker programmes

28 April 2025

ReBUILD for Resilience PhD candidate, Carlson Nkwain, recently attended the Community Health Impact Coalition roundtable. Here he talks about the session and its links to his own research on strategies to support community health workers working in fragile urban contexts, using the anglophone regions in Cameroon as a case study.

Community health workers (CHWs) provide vital services, not just in terms of the health care they provide but also for the data they collect. Some of that data directly informs local health responses, policy decisions, and resource allocation. Other data is about CHW programmes, ensuring accountability, sustainability, and evidence-based scaling. On March 28th 2025, the Community Health Impact Coalition [opens new tab], a network of organisations united by a goal of establishing professional community health workers as a global standard, convened a unique roundtable with the Fleming Initiative [opens new tab]. The aim was ambitious and clear: to develop a best-practice guide for funders investing in data-driven CHW programmes. This event represented more than just participation; it provided an opportunity to apply my five years of dedicated research on CHWs in fragile and conflict-affected settings (FCAS), to shape how funders approach and understand CHW programmes.

Overview of the roundtable discussions

The roundtable was a unique experience. It felt like a meaningful “matchmaking” moment, bringing CHWs, programme implementers, and funders, such as Gates Ventures, Partners in Health, Crown Family Philanthropies and Lwala Community Alliance, together into the same room. Usually, these stakeholders operate somewhat independently, so having everyone present to openly discuss the shape and direction of funding guidelines was refreshing. Throughout the discussions, there was a consensus on the core aspirations of funders and agreement on the overall purpose of the guiding document, i.e. helping funders effectively evaluate and support data-driven CHW programmes. We explored key themes through various collaborative exercises, from carefully defining the ideal funder audience to mapping out their decision-making journeys, pain points, and information gaps. What stood out to me was how practically we transitioned these insights into tangible recommendations, covering topics from ethical data governance and digital infrastructure to ensuring quality and genuinely involving communities in data co-design. We even discussed the best ways to package and communicate these recommendations, so they resonate clearly with funders.

In the days leading up to the roundtable, I reflected on what we mean when talking about “data” in the context of CHWs. Are we focusing more on data about CHWs or data collected by CHWs themselves? Both perspectives were the core of the discussions, especially with CHWs from Kenya, Mexico and Malawi physically present. For them, data about CHWs, such as their training status, supervision structures, or performance metrics, was meaningful. It signified recognition, accountability, and care from the health system itself. It showed them they weren’t invisible and that their role mattered enough to be carefully tracked, understood, and supported. Yet in practice, this promise often falls short. In my fieldwork in Cameroon, for example, official records of CHW numbers frequently diverged from those actually active, making planning and evaluation an uphill battle.

Equally important was the data that CHWs collected directly from their communities. CHWs viewed this data as a powerful reflection of their impact, proof of their daily work and a source for identifying gaps in their knowledge and skills. It acts as a form of self-assessment, offering insights into areas for improvement. However, this comes with a catch: CHWs often lack direct access to the data they work hard to collect. This restricts the ability of CHW programmes and, by extension, the CHWs themselves, to reflect, learn, and effectively adjust their approaches.

A speaker at the Community Health Impact Coalition roundtable

My research in the conflict-affected Buea Health District in Cameroon highlights the challenges and the promise of CHW data. On one hand, routine data on neglected tropical diseases, immunisations, or community based surveillance can be lost to the elements of nature (rain-soaked paper forms) or even destroyed when facilities are burnt down, as was the case in certain parts of conflict-affected Anglophone regions of Cameroon. On the other hand, when CHWs are equipped and empowered, like those trained on the WHO Early Warning, Alert and Response System (EWARS) who reported the first COVID-19 case in their community, their community-generated data offer early alerts and prompt interventions. This dual reality drives home how essential it is to strengthen both the systems that track CHWs and the channels through which CHWs share their data.

From the funders’ perspective, another insightful discussion was about advocating more deliberately for mixed-method approaches in grants and impact-investing evaluations; an area traditionally dominated by quantitative analysis. Funders expressed an openness to mixed methods, recognising that quantitative measures alone often fail to tell the full story of CHWs’ impact. This represents a significant opportunity for funders and implementers to collaboratively develop guidelines that clearly define the role and application of mixed methods. Such guidelines should outline how qualitative insights can provide deeper, context-rich understandings, painting the “big picture” of CHWs’ contributions beyond numerical outcomes alone.

A particularly insightful moment came when stakeholders debated how to ensure that data both about and by CHWs translates into tangible impacts at the community level. It became evident that we must actively triangulate different data types. For instance, combining data about CHWs’ performance indicators (training, supervision, retention rates) with data collected by CHWs on specific disease outcomes could offer richer insights. Such triangulation could pinpoint precisely where CHW programmes excel, identify specific community health trends, and inform targeted interventions, ultimately enhancing effectiveness and accountability for donors.

Looking ahead

Reflecting on this roundtable has only deepened my resolve to advocate for CHW professionalisation and data-driven support for CHWs and their programmes. Yet real progress is dependent on overcoming key barriers, including limited political will to formally recognise CHWs, fragmented funding streams that prioritise short-term pilots over sustained investment, and the risk of overloading CHWs with data tasks without adequate resources or training. In fragile and conflict-affected settings, insecurity, infrastructure breakdowns, and deep trust deficits compound these challenges, demanding flexible, low-tech solutions and safeguards for CHW safety. Moving forward, I’m particularly excited about opportunities for collaboration, whether in further developing these guidelines, contributing to the evidence base around CHW professionalisation, or advocating alongside funders and implementers to embed these practices in global health financing.

Further information

Blog post: Strengthening community health workers programmes in conflict settings: Insights from Buea, Cameroon

Lead image: Frontline health workers in Somalia working under very challenging circumstances. These women are working to reach every child through a polio vaccination (nOPV2) campaign for nomadic populations. Putland, Somalia – October 2023 © WHO [opens new tab]