Ellegård Lina Maria, Laberge Maude
Department of Economics, Lund University, Sweden.
Faculty of Business, Kristianstad University, Sweden.
Med Care. 2025 Jun 1;63(6):430-435. doi: 10.1097/MLR.0000000000002141. Epub 2025 Apr 24.
One of the critical challenges with capitation payment to primary care providers is ensuring that the fixed payments are equitable and adjusted for expected care needs. Patients of lower socioeconomic status (SES) generally have higher health care need. Sweden developed a Care Needs Index, which is used in the capitation payments to primary care providers to account for patient SES.
We aim to examine the potential value of collecting individual-level rather than geographic-level socioeconomic data to support an equitable payment to primary care providers.
We used data from 3 regional administrative care registers, which cover all consultations in publicly funded health care, and Statistics Sweden's registers covering individual background characteristics. We estimated linear regression models and evaluated the model fit using the adjusted R2 with the Care Needs Index at the individual and at the district level. The population consisted of the 3,490,943 individuals residing in the 3 study regions for whom we had complete data.
The main outcome variable was the number of face-to-face consultations with a GP or a nurse at a primary care practice. We use the R2 to compare the predictive power of the models.
The share of the variation explained did not depend on whether the Care Needs Index was measured at the individual level or the small area level.
SES explains very little variation in primary care visits, and there is no gain from having individual-level information about the individual's SES compared with having district-level information only.
向初级保健提供者支付按人头计费的关键挑战之一是确保固定支付公平合理，并根据预期护理需求进行调整。社会经济地位较低的患者通常有更高的医疗需求。瑞典制定了护理需求指数，用于在向初级保健提供者支付人头费时考虑患者的社会经济地位。
我们旨在研究收集个人层面而非地理层面的社会经济数据以支持向初级保健提供者进行公平支付的潜在价值。
我们使用了来自3个区域行政护理登记处的数据，这些数据涵盖了公共资助医疗保健中的所有会诊，以及瑞典统计局涵盖个人背景特征的登记处。我们估计了线性回归模型，并使用个体和地区层面的调整R²来评估模型拟合度。研究人群包括居住在3个研究区域的3,490,943名个体，我们拥有他们的完整数据。
主要结局变量是在初级保健机构与全科医生或护士进行面对面会诊的次数。我们使用R²来比较模型的预测能力。
所解释的变异比例并不取决于护理需求指数是在个体层面还是小区域层面进行测量。
社会经济地位对初级保健就诊次数的变异解释很少，与仅拥有地区层面信息相比，拥有个体层面的社会经济地位信息并无益处。
