THE RELATIONSHIP BETWEEN REGISTERED POPULATION SIZE AND CHRONIC DISEASE MANAGEMENT PERFORMANCE AMONG FAMILY PHYSICIANS

Kübra Kaplan KASAR, Baki DERHEM

Eurasian Journal of Family Medicine - 2026;15(3):321-329

Department of Family Medicine, Kırıkkale University Faculty of Medicine, Kırıkkale, Türkiye

 

Aim: The increasing prevalence of chronic diseases requires systematic monitoring in primary care. This study examined the association between registered panel size and chronic disease management performance among family physicians and identified associated factors. Methods: In this cross-sectional study, data from 90 family physicians who worked continuously in Kırıkkale province throughout 2025 were obtained from the national health statistics database. The primary analysis examined registered panel size as a continuous variable using Spearman correlation, followed by multivariable linear regression adjusted for age and gender. Secondary categorical comparisons used the sample median (2,886 registrants) and the national administrative threshold (3,500 registrants), analysed with the Mann-Whitney U test. Results: Median Disease Management Platform performance was 76.04% (18.11-91.16). In the primary analysis, panel size analysed as a continuous variable was not significantly associated with Disease Management Platform performance, and the association remained non-significant after adjustment for age and gender. In an exploratory median-based comparison, performance was lower in the high panel size group (median 74.47%) than in the low panel size group (median 79.76%); this difference was not significant when the national administrative threshold of 3,500 registrants was applied. Conclusion: Panel size was not independently associated with Disease Management Platform performance in continuous or adjusted analyses, although an exploratory median-based comparison suggested lower performance among physicians with larger panels. These findings are hypothesis-generating and require confirmation in larger, multicentre studies before conclusions regarding optimal panel size can be drawn.