Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig-Maximilians-University, Munich, Germany.
Pettenkofer School of Public Health, Munich, Germany.
Eur J Public Health. 2023 Jun 1;33(3):389-395. doi: 10.1093/eurpub/ckad039.
Multimorbidity is associated with higher utilization of healthcare services. However, many countries do not consider multimorbidity when estimating physician supply. The main aim of this study was to assess how regional multimorbidity levels can be integrated when estimating the need for office-based physician supply.
Claims data were used to measure and compare the proportions of multimorbid patients of GPs, ophthalmologists, orthopaedic specialists and neurologists, and examine spatial variations through Bernoulli cluster analysis of regional multimorbidity levels. To explore the interrelationship between current capacities and spatial occurrence of high-rate clusters, clusters were compared with the current supply of physicians.
About 17 239 488 individuals out of approximately 67 million records were classified as multimorbid. Multimorbidity levels varied greatly between physician disciplines (31.5-60.1%). Bernoulli cluster analysis demonstrated that many high-rate areas were found for all specialized physicians, but clusters varied partially by size and location. The comparison with current physician supply at cluster level showed that more than a third of clusters with a significantly higher share of morbid patients seeing a GP are met, on an average, by GP supply below targeted values. In turn, clusters with significantly higher multimorbidity levels of specialized physicians were met, on an average, by supply that exceeded targeted values.
Our study offers an approach to how to include discipline-specific multimorbidity at area level when estimating physician supply and discusses its relevance. The outcomes of our article can be used by policymakers to advance current planning strategies and to improve the quality of office-based care.
多种疾病与更高的医疗服务利用率相关。然而,许多国家在估计医生供给量时并未考虑多种疾病。本研究的主要目的是评估在估计基层医生供给量时,如何整合区域多种疾病水平。
使用索赔数据来衡量和比较全科医生、眼科医生、骨科专家和神经科医生的多病患者比例,并通过贝努利聚类分析区域多种疾病水平来检查空间变化。为了探索当前能力与高发病率集群的空间发生之间的相互关系,将集群与当前医生供给进行比较。
在大约 6700 万条记录中,约有 17239488 人被归类为多病。不同医生专业的多种疾病水平差异很大(31.5-60.1%)。贝努利聚类分析表明,所有专科医生都发现了许多高发病率地区,但集群的大小和位置存在部分差异。与集群层面的当前医生供给进行比较表明,在平均水平上,超过三分之一的 GP 就诊患者中病态患者比例明显较高的集群,其 GP 供给低于目标值。相反,在平均水平上,专科医生多种疾病水平明显较高的集群,其供给超过了目标值。
我们的研究提供了一种在估计医生供给量时如何在区域层面纳入特定学科的多种疾病的方法,并讨论了其相关性。我们文章的结果可以为政策制定者提供信息,以推进当前的规划策略,并提高基层医疗保健的质量。