Gothe Holger, Matteucci Gothe Raffaella, Arvandi Marjan, Hintringer Katharina, Toell Thomas, Oberaigner Willi, Rajsic Sasa, Kugler Joachim, Kiechl Stefan, Willeit Johann, Siebert Uwe
Department für Public Health, Versorgungsforschung und Health Technology Assessment, UMIT, Hall in Tirol, Austria.
Lehrstuhl Gesundheitswissenschaften/Public Health, Medizinische Fakultät, TU Dresden, Dresden.
Gesundheitswesen. 2020 Mar;82(S 02):S122-S130. doi: 10.1055/a-1101-8949. Epub 2020 Mar 19.
Data linkage is of paramount importance in the evaluation of treatment regimens for chronic diseases where different health care sectors are involved. A comprehensive picture of long-term treatment effects and, in particular, the cost-effectiveness ratio of treatment approaches can only be drawn when data from various sources are merged and analyzed together.
Regarding post-acute stroke care, the present study gives an example of an exact deterministic data linkage procedure including clinical patient records and claims data of TGKK, the main Tyrolean statutory health insurance fund. Typical problems known from other data linkage projects also emerged in the so-called StrokeCard program conducted at the Medical University of Innsbruck. Distinctive Austrian features (the majority of the Austrian population benefits from a mandatory social insurance system without freedom of choice) facilitated the feasibility of the data linkage procedures.
Over the recruitment period 01/2014-12/2015, 540 patients could be assigned to the operative dataset. Of these, 367 patients were part of the StrokeCard group (i. e. the treatment group), and 173 belonged to the usual care group (i. e. the control group); 11 patients did not complete the one-year follow-up period (7 treatment group patients vs. 4 control group patients); 7 of them died during the study (5 treatment group patients vs. 2 control group patients). For all 540 patients, TGKK claims data were available for the time-frames of one year before recruitment and one year after discharge from the University hospital. All data could be used in the health-economic evaluation of the StrokeCard program.
The linking of clinical patient records with data collected by SHI funds opens a window of opportunities for analyses of medical care. Counter-intuitively, Austrian health services research activities have limited experience in data linkage approaches, alhough studies based on the linkage of clinical patient records and claims data are indispensable for the evaluation of complex multi-sectoral treatment schemes. The current project proves the feasibility of data linkage mechanisms in the Austrian context. This should be regarded as an impetus for extending data linkage principles to evaluation studies in the future.
在涉及不同医疗保健部门的慢性病治疗方案评估中，数据关联至关重要。只有将来自各种来源的数据合并并一起分析，才能全面了解长期治疗效果，尤其是治疗方法的成本效益比。
关于急性中风后护理，本研究给出了一个精确确定性数据关联程序的示例，该程序包括临床患者记录以及蒂罗尔州主要法定健康保险基金TGKK的理赔数据。因斯布鲁克医科大学开展的所谓“中风卡”项目也出现了其他数据关联项目中常见的典型问题。奥地利的独特特征（大多数奥地利人口受益于强制性社会保险系统，没有选择自由）促进了数据关联程序的可行性。
在2014年1月至2015年12月的招募期间，540名患者可被纳入手术数据集。其中，367名患者属于“中风卡”组（即治疗组），173名属于常规护理组（即对照组）；11名患者未完成一年的随访期（7名治疗组患者和4名对照组患者）；其中7人在研究期间死亡（5名治疗组患者和2名对照组患者）。对于所有540名患者，TGKK理赔数据在招募前一年和大学医院出院后一年的时间范围内均可获取。所有数据均可用于“中风卡”项目的卫生经济评估。
将临床患者记录与法定健康保险基金收集的数据相联系，为医疗保健分析打开了一扇机会之窗。与直觉相反的是，奥地利的卫生服务研究活动在数据关联方法方面经验有限，尽管基于临床患者记录和理赔数据关联的研究对于评估复杂的多部门治疗方案必不可少。当前项目证明了数据关联机制在奥地利背景下的可行性。这应被视为未来将数据关联原则扩展到评估研究的一个推动力。
