Langner Ingo, Krieg Volker, Heidinger Oliver, Hense Hans Werner, Zeeb Hajo
Klinische Epidemiologie, Leibniz-Institut für Präventionsforschung und Epidemiologie - BIPS, Bremen.
Registerstelle, Landeskrebsregister Nordrhein-Westfalen, Münster.
Gesundheitswesen. 2019 Aug;81(8-09):629-635. doi: 10.1055/s-0043-124669. Epub 2018 Feb 1.
Claims data of the statutory health insurance (SHI) are an important data source for the evaluation of cancer prevention programs. However, this source does not contain relevant information on cause of death. This study examined whether individual claims data can be enriched with data on the required cause of death using record linkage procedures with suitable external data sources.
In the German pharmacoepidemiologic research database (GePaRD) we identified a sample of 25,528 deceased female residents of North Rhine Westphalia (NRW) who, according to GePaRD information, died between 2006 and 2013. Date and cause of all deaths among inhabitants of NRW since 2005 were available in the epidemiological cancer registry of NRW. In cooperation with 2 SHI companies, we tried to match each individual of the sample with a case of death in NRW and the corresponding cause of death using a probabilistic and, alternatively, a deterministic linkage procedure.
Of the study sample, 94.72% were successfully matched by the probabilistic and 93.36% by the deterministic method.
The probabilistic and the deterministic record linkage approach produced comparably high matching rates. Cases without matches are probably due to errors occurring at the stage of personal data entry. Given the lower technical efforts, the deterministic approach appears to be the method of choice for the enrichment of claims data with cause of death information from suitable external data sources in Germany.
法定健康保险(SHI)的理赔数据是评估癌症预防项目的重要数据源。然而,该数据源不包含有关死亡原因的相关信息。本研究探讨了能否通过与合适的外部数据源进行记录链接程序,用所需的死亡原因数据丰富个体理赔数据。
在德国药物流行病学研究数据库(GePaRD)中,我们确定了25528名北莱茵-威斯特法伦州(NRW)已故女性居民的样本,根据GePaRD信息,这些居民于2006年至2013年期间死亡。自2005年以来NRW居民的所有死亡日期和原因可在NRW的癌症流行病学登记处获取。我们与两家SHI公司合作,试图使用概率性和确定性链接程序,将样本中的每个个体与NRW的死亡病例及相应的死亡原因进行匹配。
在研究样本中,概率性方法成功匹配了94.72%,确定性方法成功匹配了93.36%。
概率性和确定性记录链接方法产生了相当高的匹配率。未匹配的病例可能是由于个人数据录入阶段出现的错误。鉴于技术工作量较低,确定性方法似乎是用来自德国合适外部数据源的死亡原因信息丰富理赔数据的首选方法。