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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.

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