Implementing Single Source: The STARBRITE Proof-of-Concept Study

SummaryObjective: 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 followup 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 followup 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. BackgroundClinical studies typically consist of several visits, and after an initial assessment, several follow-up visits need to be organized and documented. Therefore, follow-up data needs to be collected according to each study protocol at certain time points. According to Chan et al., "data completeness varied substantially across studies" [1] which may be caused by the huge documentation workload of physicians in routine care [2]. Forster et al. have reported that the median rate of loss to followup in a 15-country study was 8.5% [3]. Consequently, data completeness in studies is a critical and unsolved problem. There are different causes of patients being lost to follow-up. First, patients do not return to the physicians, and second, there are organizational issues in hospitals, for example regarding scheduling. Commonly, electronic data capture (EDC) systems are used for research documentation which includes follow-up documents. El Emam et al. state that "Electronic data capture (EDC) tools provide automated support for data collection, reporting, query re...

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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HIS-based support of follow-up documentation – concept and implementation for clinical studies

Herzberg

Rahbar²,

Stegger³

et al. 2011

“…The need for making these data available for scientific reuse has been discussed extensively [1][2][3]. Thus, routine data could be beneficial throughout the whole research lifecycle, as a base for hypothesis generation, estimation of expected study cohort sizes, to enhance patient recruitment in ongoing studies and to reduce duplication of data entry, among other uses.…”

Section: Introductionmentioning

confidence: 99%

Unlocking Data for Clinical Research – The German i2b2 Experience

Ganslandt

Mate²,

Helbing³

et al. 2011

SummaryObjective: Data from clinical care is increasingly being used for research purposes. The i2b2 platform has been introduced in some US research communities as a tool for data integration and querying by clinical users. The purpose of this project was to assess the applicability of i2b2 in Germany regarding use cases, functionality and integration with privacy enhancing tools. Methods: A set of four research usage scenarios was chosen, including the transformation and import of ontology and fact data from existing clinical data collections into i2b2 v1.4 instances. Query performance was measured in comparison to native SQL queries. A setup and administration tool for i2b2 was developed. An extraction tool for CDISC ODM data was programmed. Interfaces for the TMF privacy enhancing tools (PID Generator, Pseudonymization Service) were implemented. Results: Data could be imported in all tested scenarios from various source systems, including the generation of i2b2 ontology definitions. The integration of TMF privacy enhancing tools was possible without modification of the platform. Limitations were found regarding query performance in comparison to native SQL and certain temporal queries. Conclusions: i2b2 is a viable platform for data query tasks in use cases typical for networked medical research in Germany. The integration of privacy enhancing tools facilitates the use of i2b2 within established data protection concepts. Entry barriers should be lowered by providing tools for simplified setup and import of medical standard formats like CDISC ODM.

“…A separate documentation system possesses quite a few disadvantages, for instance "Inefficiencies in clinical trial data collection cause delays, increase costs, and may reduce clinician participation in medical research" [3]. Moreover, "Routine data are potentially cheaper to extract and analyze than designed data…" and "... have the potential to identify patient outcomes captured in remote systems that may be missed in designed data collection" [4].…”

Section: Introductionmentioning

confidence: 99%

Concept and implementation of a single source information system in nuclear medicine for myocardial scintigraphy (SPECT-CT data)

Herzberg

Rahbar²,

Stegger³

et al. 2010

Single source information system, hospital information system, nuclear medicine, myocardialscintigraphy (SPECT/CT-data) SummaryObjective: Data for clinical documentation and medical research are usually managed in separate systems. We developed, implemented and assessed a documentation system for myocardial scintigraphy (SPECT/CT-data) in order to integrate clinical and research documentation. This paper presents concept, implementation and evaluation of this single source system including methods to improve data quality by plausibility checks. Methods: We analyzed the documentation process for myocardial scintigraphy, especially for collecting medical history, symptoms and medication as well as stress and rest injection protocols. Corresponding electronic forms were implemented in our hospital information system (HIS) including plausibility checks to support correctness and completeness of data entry. Research data can be extracted from routine data by dedicated HIS reports. Results: A single source system based on HIS-electronic documentation merges clinical and scientific documentation and thus avoids multiple documentation. Within nine months 495 patients were documented with our system by 8 physicians and 6 radiographers (466 medical history protocols, 466 stress and 414 rest injection protocols). Documentation consists of 295 attributes, three quarters are conditional items. Data quality improved substantially compared to previous paper-based documentation. Conclusion: A single source system to collect routine and research data for myocardial scintigraphy is feasible in a real-world setting and can generate high-quality data through online plausibility checks. Citation: Herzberg S, Rahbar K, Stegger L, Schäfers M, Dugas M. Concept and implementation of a single source information system in nuclear medicine for myocardial scintigraphy (SPECT-CT data).