Brutsche Martin, Rassouli Frank, Gallion Harald, Kalra Sanjay, Roger Veronique L, Baty Florent
Lung Centre, Cantonal Hospital St Gallen, Switzerland.
Department of Medical Coding, Cantonal Hospital St Gallen, Switzerland.
Swiss Med Wkly. 2018 Dec 15;148:w14691. doi: 10.4414/smw.2018.14691. eCollection 2018 Dec 3.
Our aim was to estimate the diagnostic performance of institutions and healthcare regions from a nationwide hospitalisation database.
The Shannon diversity index was used as an indicator of diagnostic performance based on the International Classification of Disease, 10th revision, German Modification (ICD-10-GM codes). The dataset included a total of 9,325,326 hospitalisation cases from 2009 to 2015 and was provided by the Swiss Federal Office for Statistics. A total of 16,435 diagnostic items from the ICD-10-GM codes were taken as the basis for the calculation of the diagnostic diversity index (DDI). Numerical simulations were performed to evaluate the effect of misdiagnoses in the DDI. We arbitrarily defined the minimum clinically important difference (MCID) as 10% misdiagnoses. The R statistical software was used for all analyses.
Diagnostic performance of institutions and healthcare regions as measured by the DDI were strongly associated with caseload and number of inhabitants, respectively. A caseload of >7217 hospitalisations per year for institutions and a population size >363,522 for healthcare regions were indicators of an acceptable diagnostic performance. Among hospitals, there was notable heterogeneity of diagnostic diversity, which was strongly associated with caseload. Application of misdiagnosis-thresholds within each ICD-10-GM category allowed classification of hospitals in four distinct groups: high-volume hospitals with an all-over comprehensive diagnostic performance; high- to mid-volume hospitals with extensive to relevant basic diagnostic performance in most categories; low-volume specialised hospitals with a high diagnostic performance in a single category; and low-volume hospitals with inadequate diagnostic performance in all categories. The diagnostic diversity observed in the 26 Swiss healthcare regions showed relevant heterogeneity, an association with ICD-10-GM code utilisation, and was strongly associated with the size of the healthcare region. The limited diagnostic performance in small healthcare regions was partially, but not fully, compensated for by consumption of health services outside of their own healthcare region.
Calculation of the DDI from ICD-10 codes is easy and complements the information derived from other quality indicators as it sheds a light on the fitness of the institutionalised interplay between primary and specialised medical inpatient care.  .
我们的目的是根据全国住院数据库评估机构和医疗保健区域的诊断性能。
基于第十次修订的《国际疾病分类》德国修订版（ICD-10-GM编码），使用香农多样性指数作为诊断性能的指标。数据集包括2009年至2015年的9325326例住院病例，由瑞士联邦统计局提供。ICD-10-GM编码中的16435个诊断项目作为计算诊断多样性指数（DDI）的基础。进行数值模拟以评估误诊对DDI的影响。我们任意将最小临床重要差异（MCID）定义为10%的误诊率。所有分析均使用R统计软件。
通过DDI衡量的机构和医疗保健区域的诊断性能分别与病例数量和居民数量密切相关。机构每年住院病例数>7217例以及医疗保健区域人口规模>363522人是可接受诊断性能的指标。在医院中，诊断多样性存在显著异质性，这与病例数量密切相关。在每个ICD-10-GM类别中应用误诊阈值可将医院分为四个不同组：病例数量多且具有全面综合诊断性能的医院；病例数量中等至高且在大多数类别中具有广泛至相关基本诊断性能的医院；病例数量少且在单一类别中具有高诊断性能的专科医院；以及病例数量少且在所有类别中诊断性能不足的医院。在瑞士的26个医疗保健区域观察到的诊断多样性显示出相关异质性，与ICD-10-GM编码的使用有关，并且与医疗保健区域的规模密切相关。小医疗保健区域有限的诊断性能部分但未完全由其自身医疗保健区域之外的医疗服务消耗所补偿。
根据ICD-10编码计算DDI很容易，并且补充了从其他质量指标得出的信息，因为它揭示了初级和专科医疗住院护理之间制度化相互作用的适应性。
