ArticleScandinavian journal of primary health care2026
Case-mix adjustments of patient reported experience measures in general practice: variations between Norwegian municipalities.
Article in Scandinavian journal of primary health care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundUnderstanding patients' experiences with general practice is essential for improving services, and quality indicators are commonly used for that purpose. When reporting at the municipality level, factors beyond municipal control, such as age and country of birth, may influence results. Case-mix adjustment helps ensure fair comparisons. While several international studies have assessed case-mix adjustment for patient experience measures, few studies have examine the impact of case-mix adjustment at the municipality level.
objectiveTo identify relevant municipality-level variables for case-mix adjustment in Norway and measure their impact on aggregated patient experience scores.
methodsWe analysed data from the 2023 national survey on patient experiences with the general practitioner. Linear mixed-effects regression was applied with municipalities as a random effect and patient age, sex, long-term conditions, country of birth, education and household income as fixed effects. Outcomes were municipality-level means for six measures:
resultsAge, birth country and long-term conditions were consistently associated with patient experience measures. Intraclass correlations showed that birth country (4%) and education (2.6%) accounted for the greatest between-municipality variation. Case-mix adjustment most strongly influenced
conclusionPatient characteristics-particularly age and country of birth-are systematically linked to patient reported experience measures, while sex and education are less important. Case-mix adjustment modestly improves fairness in municipality comparisons, underscoring the need for a selective, evidence-based approach when applying adjustment in quality measurement and research.
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