more workers, less oversight

Problem statement

BRAC's Shasthya Shebika (community health worker) program is the world's largest CHW network, with over 100,000 workers across Bangladesh. The model's effectiveness was established at smaller scale: each CHW serves ~250 households, supervised by a Shasthya Kormi (health supervisor) covering 10–12 CHWs. As the program scaled beyond 50,000 workers, supervision ratios stretched — supervisors now cover 15–20+ CHWs across wider geographic areas, and the quality-maintaining feedback loops that made the model effective at pilot scale have weakened. The degradation is non-linear: a 50% increase in supervisor caseload produces far more than 50% loss in supervision quality because travel time, not meeting time, is the binding constraint.

Why this matters

CHW programs are the backbone of primary care delivery in low-income countries. WHO estimates that achieving universal health coverage requires 4.45 million additional health workers, and CHW programs are the primary strategy for closing this gap. BRAC's model is widely replicated — Bangladesh, Uganda, Tanzania, Sierra Leone, Liberia — but every replication inherits the supervision scalability problem. Dropout rates among BRAC CHWs in urban Dhaka slums reached 37% within two years, driven primarily by inadequate supervision and support rather than by low compensation. When supervision quality drops, CHW performance doesn't just decline — it becomes variable, eroding community trust in the entire system.

What’s been tried and why it hasn’t worked

BRAC has experimented with group supervision (monthly cluster meetings replacing individual field visits), mobile phone-based reporting, and performance incentive structures. Group meetings reduce travel burden but lose the observational component — supervisors can't assess clinical technique from a meeting room. Mobile reporting captures activity metrics (visits completed, referrals made) but not quality metrics (correct assessment, appropriate counseling). Performance incentives tied to quantitative targets produce predictable gaming: CHWs log visits without delivering services, or concentrate on easy-to-count activities (product sales) over harder-to-measure ones (health education). The fundamental constraint is that quality supervision requires co-present observation, and co-present observation doesn't scale geometrically with workforce size.

What would unlock progress

Peer supervision models — where experienced CHWs supervise newer ones — could reduce the supervision ratio without proportionally increasing supervisory staff. Digital tools that capture process quality rather than activity counts (e.g., audio-recorded counseling sessions reviewed by AI or supervisors remotely) could decouple quality assessment from physical co-presence. Community accountability mechanisms — where households themselves provide structured feedback on CHW performance — could create a distributed quality signal that doesn't depend on supervisor visits. The key insight from BRAC's own research is that supervision's value is motivational and problem-solving, not primarily compliance-checking — redesigning for those functions may scale differently.

Entry points for student teams

A systems team could model the non-linear relationship between supervision ratio and quality outcomes across urban and rural geographic densities, using the published BRAC and CHW-performance literature and travel-time geometry to find where restructuring pays off — a desk study needing nothing but the papers and a laptop. A design team could prototype a lightweight community feedback tool — SMS-based or paper card — that captures household satisfaction and CHW performance indicators, and test whether the instrument gives stable, discriminating ratings using role-played household visits scripted at deliberately good and degraded levels of CHW performance; whether that signal tracks real supervisor-observed quality is the validation study to design and hand to BRAC's Research and Evaluation Division, not to run. An HCI team could design a CHW self-assessment tool that guides reflection on practice quality without a supervisor present, scoring its items against the supervision and performance-management domains of the free CHW AIM toolkit (USAID/UNICEF/Community Health Impact Coalition, 2018) and reviewing it with global-health practitioners and diaspora nurses who can be reached without field access. Anything tested inside BRAC's live program needs a research agreement with BRAC RED plus Bangladeshi ethical clearance, and BRAC owns that access — so the semester deliverable is the instrument and its evaluation protocol.