ArticleJournal of managed care & specialty pharmacy2024
Combining zip code-based population data and pharmacy administrative claims data to create measures of social determinants of health.
Article in Journal of managed care & specialty pharmacy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Access without approval: state-level determinants of peptide availability in sexual medicine.Sexual medicine · 2026Article
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4 authors.
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Abstract
backgroundSocial determinants of health (SDoH) are key factors that impact health outcomes. However, there are many barriers to collecting SDoH data (eg, cost of data collection, technological barriers, and lack of standardized measures). Population data may provide an accessible alternative to collecting SDoH data for patients.
objectiveTo explain how population data can be leveraged to create SDoH measures, assess the association of population SDoH measures with diabetic medication adherence, and discuss how understanding a patient's SDoH can inform care plans and patient engagement.
methodsA nationally representative commercial sample of patients who were aged 18 years and older and met Pharmacy Quality Alliance inclusion criteria for diabetes mellitus were analyzed (N = 37,789). US Census and North American Industry Classification System data were combined with pharmacy administrative claims data to create SDoH measures. Derived measures represent 2 SDoH domains: (1) economic stability (housing density, housing relocation, jobs per resident, and average salary) and (2) health care access and quality (urban/rural classification, distance traveled to prescriber and pharmacy, use of a primary care provider [PCP], and residents per PCP). The association of population SDoH measures with diabetic medication adherence (proportion of days covered) was assessed via logistic regression, which included covariates (eg, sex, age, comorbidities, and prescription plan attributes).
resultsAs housing density (houses per resident) increased, so did the likelihood of adherence (odds ratio = 1.54, 95% CI = 1.21-1.97,
conclusionsLeveraging publicly available population data to create SDoH measures is an accessible option to overcome barriers to SDoH data collection. Derived measures can be used to increase equity in care received by identifying patients who could benefit from assistance with medication adherence.
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