Institute of Public Health and Nursing Research, University of Bremen, Bremen, Germany
High Profile Area Health Sciences, University of Bremen, Bremen, Germany.
BMJ Open. 2022 Jun 30;12(6):e063475. doi: 10.1136/bmjopen-2022-063475.
We perform and evaluate record linkage of German Care Needs Assessment (CNA) data to Statutory Health Insurance (SHI) claims data. The resulting dataset should enable the identification of factors in healthcare predicting the time between the onset of long-term care dependency and the admission to a nursing home in Germany in subsequent analyses.
A deterministic record linkage was conducted using the key variables region, sex, date of birth and care level. In further steps, the underlying cause of care dependency (International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10)) was added for a higher level of distinction. Before linkage, the suitability of the two datasets for these procedures was assessed. After linkage, the results of each stage were analysed and the resulting dataset was evaluated cross-sectionally with respect to bias generated through this process.
The study comprises data from the German SHI and Statutory Long-Term Care Insurance.
The study cohort comprised 158 069 individuals who became care dependent in 2006. We obtained CNA data for the year 2006 including 188 935 individuals.
We could link CNAs to 66 310 individuals of the original study cohort, corresponding to 42.0%. Records from two federal states could not be matched due to missing data. Linkage rates were lower where more people shared the same attributes. The resulting dataset showed minor differences regarding age, sex and care level compared to the original cohort.
Data linkage between German SHI claims data and CNA data is feasible. Failure to link was mostly attributable to a lack of distinction between individuals using available identifiers. The resulting dataset contains relevant information from both health services provision and functional status of care dependent people and is suitable for further analyses with critical reflection of representativity.
我们对德国护理需求评估（CNA）数据与法定健康保险（SHI）索赔数据进行记录链接，并对其进行评估。在后续分析中，由此产生的数据集应能够识别医疗保健中预测长期护理依赖发病和入住德国疗养院之间时间的因素。
使用区域、性别、出生日期和护理级别等关键变量进行确定性记录链接。在进一步的步骤中，为了更高的区分度，添加了护理依赖的根本原因（国际疾病分类和相关健康问题第十次修订版（ICD-10））。在链接之前，评估了这两个数据集是否适合这些程序。链接后，分析每个阶段的结果，并从横断面的角度评估由此产生的数据集，以了解该过程产生的偏差。
该研究包括德国 SHI 和法定长期护理保险的数据。
研究队列包括 2006 年依赖护理的 158069 人。我们获得了 2006 年包括 188935 人的 CNA 数据。
我们可以将 CNA 链接到原始研究队列中的 66310 人，占 42.0%。由于数据缺失，两个联邦州的记录无法匹配。记录匹配率在具有相同属性的人越多的情况下越低。与原始队列相比，由此产生的数据集在年龄、性别和护理水平方面差异较小。
德国 SHI 索赔数据与 CNA 数据之间的数据链接是可行的。链接失败主要归因于使用可用标识符对个体的区分度不够。由此产生的数据集包含了来自健康服务提供和护理依赖者功能状态的相关信息，并且适合在对代表性进行批判性反思的情况下进行进一步分析。
