Toward building a master health facility list database in Senegal: approaches and outputs from triangulating secondary health facility data

Abstract

Background Having a consolidated, geolocated list of all facilities in a country – a “master facility list” (MFL) – can provide critical inputs for health program planning and implementation. To the best of our knowledge, Senegal has never had a centralized MFL, though many data sources currently exist within the broader Senegalese data landscape that could be used to work toward building a full MFL.

Main text We collated 12,965 facility observations from 16 separate datasets and lists in Senegal, and applied matching algorithms, manual checking and revisions as needed, and verification processes to identify unique facilities and triangulate corresponding GPS coordinates. Our resulting consolidated facility list was a total of 4,685 facilities with 51.5% having at least one GPS coordinate (n=2,414). Key challenges included accounting for variable spelling across datasets, distinguishing between facility type changes (e.g., health huts being upgraded to health posts with the same name) and separate facilities that shared the same name, GPS verification, among others.

Conclusion Developing approaches to leverage existing data for MFL establishment can help bridge data demands and inform more targeted approaches for completing a full facility census based on areas and facility types with the lowest coverage. Going forward, it is crucial to ensure routine updates of current facility lists, and to strengthen government-led mechanisms around such data collection demands and the need for timely data for health decision-making.

Competing Interest Statement

NF, PYL, and GI are paid employees of Gates Ventures. NF, PYL, and GI previously worked at the Institute for Health Metrics and Evaluation (IHME): September 2008-2011 and February 2013-June 2022 for NF; June 2014-September 2017 and January-June 2022 for PYL; and August 2014-July 2020 for GI. NF reports funding from WHO between June and September 2019 for consulting unrelated to this work.

Funding Statement

This work was funded by Gates Ventures.

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