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HIS-based Kaplan-Meier plots - a single source approach for documenting and reusing routine survival information

机译:基于HIS的Kaplan-Meier图-记录和重复使用常规生存信息的单一来源方法

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Background Survival or outcome information is important for clinical routine as well as for clinical research and should be collected completely, timely and precisely. This information is relevant for multiple usages including quality control, clinical trials, observational studies and epidemiological registries. However, the local hospital information system (HIS) does not support this documentation and therefore this data has to generated by paper based or spreadsheet methods which can result in redundantly documented data. Therefore we investigated, whether integrating the follow-up documentation of different departments in the HIS and reusing it for survival analysis can enable the physician to obtain survival curves in a timely manner and to avoid redundant documentation. Methods We analysed the current follow-up process of oncological patients in two departments (urology, haematology) with respect to different documentation forms. We developed a concept for comprehensive survival documentation based on a generic data model and implemented a follow-up form within the HIS of the University Hospital Muenster which is suitable for a secondary use of these data. We designed a query to extract the relevant data from the HIS and implemented Kaplan-Meier plots based on these data. To re-use this data sufficient data quality is needed. We measured completeness of forms with respect to all tumour cases in the clinic and completeness of documented items per form as incomplete information can bias results of the survival analysis. Results Based on the form analysis we discovered differences and concordances between both departments. We identified 52 attributes from which 13 were common (e.g. procedures and diagnosis dates) and were used for the generic data model. The electronic follow-up form was integrated in the clinical workflow. Survival data was also retrospectively entered in order to perform survival and quality analyses on a comprehensive data set. Physicians are now able to generate timely Kaplan-Meier plots on current data. We analysed 1029 follow-up forms of 965 patients with survival information between 1992 and 2010. Completeness of forms was 60.2%, completeness of items ranges between 94.3% and 98.5%. Median overall survival time was 16.4 years; median event-free survival time was 7.7 years. Conclusion It is feasible to integrate survival information into routine HIS documentation such that Kaplan-Meier plots can be generated directly and in a timely manner.
机译:背景生存或结果信息对于临床常规以及临床研究均很重要,应完整,及时和准确地收集。此信息与多种用途相关,包括质量控制,临床试验,观察性研究和流行病学注册表。但是,当地医院信息系统(HIS)不支持此文档,因此该数据必须通过基于纸张或电子表格的方法生成,这可能会导致冗余地记录数据。因此,我们调查了是否将不同部门的后续文档整合到HIS中并将其重新用于生存分析可以使医生及时获取生存曲线,并避免多余的文档。方法我们分析了两个部门(泌尿科,血液科)针对不同文档形式的当前肿瘤患者的随访过程。我们基于通用数据模型开发了一种综合生存文档的概念,并在明斯特大学医院的HIS中实施了后续表格,该表格适用于这些数据的二次使用。我们设计了一个查询以从HIS中提取相关数据,并根据这些数据实施了Kaplan-Meier图。要重新使用此数据,需要足够的数据质量。我们在临床中针对所有肿瘤病例测量了表格的完整性,并且每份表格记录的项目的完整性,因为不完整的信息可能会影响生存分析的结果。结果基于形式分析,我们发现了两个部门之间的差异和一致性。我们确定了52个属性,其中13个是常见属性(例如,程序和诊断日期),并已用于通用数据模型。电子随访表格已整合到临床工作流程中。还回顾性地输入生存数据,以便对综合数据集进行生存和质量分析。医师现在可以根据当前数据及时生成Kaplan-Meier图。我们分析了1992年至2010年间965例具有生存信息的1029例随访表格,表格的完整性为60.2%,项目的完整性为94.3%至98.5%。中位总生存时间为16.4年。中位无事件生存时间为7.7年。结论将生存信息整合到常规HIS文档中是可行的,这样可以直接,及时地生成Kaplan-Meier图。

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