Stability of healthcare quality measures for maternal and child services: Analysis of the continuous service provision assessment of health facilities in Senegal, 2012-2018.

OBJECTIVE: High-quality healthcare is essential to ensuring maternal and newborn survival. Efficient measurement requires knowing how long measures of quality provide consistent insight for intended uses. METHODS: We used a repeated health facility assessment in Senegal to calculate structural and process quality of antenatal care (ANC), delivery and child health services in facilities assessed 2 years apart. We tested agreement of quality measures within facilities and regions. We estimated how much input-adjusted and process quality-adjusted coverage measures changed for each service when calculated using quality measurements from the same facilities measured 2 years apart. RESULTS: Over 6 waves of continuous surveys, 628 paired assessments were completed. Changes at the facility level were substantial and often positive, but inconsistent. Structural quality measures were moderately correlated (0.40-0.69) within facilities over time, more so in hospitals; correlation was <0.20 for process measures based on direct observation of ANC and child visits. Most measures were more strongly correlated once averaged to regions; process quality of child services was not (-0.32). Median relative difference in national-adjusted coverage estimates was 6.0%; differences in subnational estimates were largest for process quality of child services (19.6%). CONCLUSION: Continuous measures of structural quality demonstrated consistency at regional levels and in higher level facilities over 2 years; results for process measures were mixed. Direct observation of child visits provided inconsistent measures over time. For other measures, linking population data with health facility assessments from up to 2 years prior is likely to introduce modest measurement error in adjusted coverage estimates.

A consolidated and geolocated facility list in Senegal from triangulating secondary data.

Having a 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 leveraged and consolidated into a single database - a critical first step toward building a full MFL. 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 has a total of 4,685 facilities, with 2,423 having at least one set of GPS coordinates. Developing approaches to leverage existing data toward future 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.