India’s public health system has a problem of geography. National policy is set in Delhi and state budgets are allocated in state capitals. Health services themselves, including primary health centres, frontline workers, cold chains and drug supply, are run at the district level. The District Collector manages a budget and makes the operational decisions that determine whether a pregnant woman gets an ultrasound or walks home without one.
A climate and health fund working across Indian districts had to choose whether to design its programme around states, districts or villages.
Why districts
States are too large. A state health director in Jharkhand manages 24 districts with very different health profiles, and an intervention that works in Ranchi may not work in Khunti. Designing at the state level smooths over the variation, and the problem lies in the variation.
Villages are too small. A funder cannot design a grant around 600,000 individual villages. The village is the wrong administrative unit for the funding cycle, the reporting cycle and the monitoring cycle.
The district is the right size. It is small enough for a programme manager to know the ground: the particular health centres, the particular gaps in staffing and the particular road conditions that affect the vaccine cold chain. It is large enough for a funder to allocate a meaningful budget. It is also where the government officers with real decision-making power, the District Collector and the Chief Medical Officer, sit.
What this meant in practice
The fund built its whole structure around the district. Each of four districts, Chamarajanagar (Karnataka), Dhubri (Assam), Khunti (Jharkhand) and West Singhbhum (Jharkhand), received a base paper. Each paper gave a detailed profile of the district’s health system, climate vulnerabilities, demographic patterns and institutional capacity. They were written as operational documents for a programme manager, setting out what they had to work with, what was broken and where the intervention should land.
The fund then set up a fellowship programme in each district, placing fellows inside the district health system to work with government officers on specific problems such as heat action plans, surveillance of vector-borne disease, and nutrition during extreme weather. The fellows worked from inside the system. They attended district health meetings, used district data systems and reported to district officers.
The learning layer
Most development funds evaluate at the end. This fund designed a learning layer that ran in real time and produced evidence while the fund was operating, before the money was spent.
The learning layer tracked three things: what the fellows were doing (activity data), what the district health system was changing (process data), and which health outcomes were moving (outcome data). The three streams were cross-referenced every month. If the activity data showed that a fellow had introduced a new tool for screening heat vulnerability, the process data could show whether the district health system adopted it, and the outcome data could eventually show whether patterns of heat-related illness changed.
The standard evaluation model works differently: a consultant arrives after the programme ends, collects data, writes a report and leaves. Here the learning layer was part of the fund’s governance, and the programme committee used its data to adjust priorities during the cycle.
Where this leads
Working at the district level forced more honesty about what change in a health system looks like. A state-level programme can report improvement on average while particular districts get worse. A district-level programme cannot hide that, because the variation is what it is built to see.
The Measurement Checklist makes the same argument about indicators: the number you choose to report shapes the story you tell. A state average tells one story and a district profile tells another. The district story is harder to compile, harder to fund and harder to spin. It is also more useful to the District Collector deciding how to spend her budget on a Monday morning.