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Allocating socioeconomic census data to primary care areas: an improvement in small-area analyses
Francisco Estupiñán-Romero1, Santiago Royo-Sierra1, Javier González-Galindo1
1Data Science for Health Services and Policy research group, Institute for Health Sciences in Aragon (IACS), Zaragoza, Spain.
Objective:
Provide a method for reusing National Institute of Statistics (INE) socioeconomic data and reconstructing the Spanish National Health System primary care areas (PCA) from INE census tracts.
Method:
The reconstruction of PCA boundaries entailed aligning, assigning, and integrating census tracts within the limits of the PCA using 2022 INE and 2018 Atlas VPM digital maps.
Results:
36,282 census tracts were assigned to 2,405 PCA. The alignment of digital maps showed a programmatic assignment of 99.7% of the census tracts within PCA; just ten census tracts must be manually assigned. The net average income per capita distribution from INE was consistent along the newly reconstructed PCA.
Conclusions:
We have proposed a reliable solution to integrate socioeconomic data from INE census statistics into PCA, enhancing data researchers' capacities in joint analyses of socioeconomic determinants and healthcare.
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