Defining Documenting Catchment Areas of Urban Health Centres on Web Portal

Problem Statement

In rural areas there are geographically and demographically well defined unitsvillages attached to a PHC / Subcenter (HWC) In Urban areas like Delhi, where lac after lac of population just stretches in continuity, it is important that each health center knows its catchment population for promotive and preventive health interventions and that each ANM and ASHA has a geographically and demographically defined population for which she is responsible. And the same must be available to the functionaries.

Programme Description

The Electoral database generated by Census was used to facilitate mapping of population with health facilities. Population level data is available for polling booths which have a population of 1500 to 2500 each. A group of confluent polling stations around the centre were used to provide the area description and the estimated population of the catchment area of the centre. Primary healthcare facilities of Government of National Capital Territory of Delhi (GNCTD) and Municipal Corporation of Delhi (MCDs) were mapped and infrastructure data compiled. Webbased software with electoral databases were provided to the UPHC teams/district nodal officers and training of MO I/Cs and their teams from GNCTD and MCD undertaken. Polling stations surrounding the health centres within 1.5 to 2 km identified with population totalling up to around 50,000 and attached to each health facility. Overlaps were removed and unserved / underserved groups were documented by multi-agency district task groups. Each ANM, MO I/C, district nodal officer were provided with access to this information.

Programme Outcomes

The effort enabled

• Defining, codification and documentation of the areas for all GNCTD / MCD health centres.
• Defining, codification and documentation of 8000 – 12000 population pockets as ANM areas and around 2000 population pockets as ASHA areas.
• Generating the denominator for benchmarks for various activities and resolution of overlapping areas. Identification of unserved areas and their attachment to existing / new centres.
• Creating accountability for areas assigned and availability of data for targeted interventions.
• The data can be further used to build name / family folderbased empanelment of the attached population as the state progresses towards the provision of Comprehensive Primary Health Care.

Scalability

The process can be used in all urban areas and even rural areas as the main advantage of use of polling station / booth data is that no geographic pocket / habitation is left out. Mechanisms have been built in to add the population residing in that pocket which is not a part of the electoral data/or has recently migrated in the area. Implementation Partners This was an effort undertaken entirely by the state government.

Financial Implications

The software was developed in-house by team of programmers already deployed for developing multiple modules for the health department. Web- based application is hosted on the Delhi State Health Mission (DSHM) servers. Implementing functionaries were / are the existing health functionaries. Funds for trainings / meetings were sourced from routinely available fund for such activities. 

Source : We Care Coffee Table Book - Good, Replicable and Innovative Practices 2019