HIS-based support of follow-up documentation – concept and implementation for clinical studies
27 August 2010
accepted: 20 January 2010
16 December 2017 (online)
Objective: Follow-up data must be collected according to the protocol of each clinical study, i.e. at certain time points. Missing follow-up information is a critical problem and may impede or bias the analysis of study data and result in delays. Moreover, additional patient recruitment may be necessary due to incomplete follow-up data. Current electronic data capture (EDC) systems in clinical studies are usually separated from hospital information systems (HIS) and therefore can provide limited functionality to support clinical workflow. In two case studies, we assessed the feasibility of HIS-based support of follow-up documentation.
Methods: We have developed a data model and a HIS-based workflow to provide follow-up forms according to clinical study protocols. If a follow-up form was due, a database procedure created a follow-up event which was translated by a communication server into an HL7 message and transferred to the import interface of the clinical information system (CIS). This procedure generated the required follow-up form and enqueued a link to it in a work list of the relating study nurses and study physicians, respectively.
Results: A HIS-based follow-up system automatically generated follow-up forms as defined by a clinical study protocol. These forms were scheduled into work lists of study nurses and study physicians. This system was integrated into the clinical workflow of two clinical studies. In a study from nuclear medicine, each scenario from the test concept according to the protocol of the single photon emission computer tomography/computer tomography (SPECT/CT) study was simulated and each scenario passed the test. For a study in psychiatry, 128 follow-up forms were automatically generated within 27 weeks, on average five forms per week (maximum 12, minimum 1 form per week).
Conclusion: HIS-based support of follow-up documentation in clinical studies is technically feasible and can support compliance with study protocols.
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