38 We therefore used a qualitative, participant observer approach to identifying the challenges of using a single source of data for research and patient care. 37 In doing so, we hoped to assess the underlying causes, possibly process-related and social in nature, of the phenomenon under study. Following the example of other informatics implementation research, we employed a single case-study design. To investigate these issues, this project was designed as a proof-of-concept study. Standards have the potential to make this possible by allowing investigational sites to use existing systems without the burden of data transformation ( ▶). Multicenter trials require data from different sites to be submitted to a central data center, with whom the site’s relationship may exist for only a single trial for reuse of patient care data to be feasible, data collection methods must be easy to implement and use, and must minimize disruption at the clinical site. ![]() Many systems allow reuse of patient care data, 6,7,10,12,13,18,27–36 but with rare exceptions 30,36 most examples consist of institution-specific approaches that do not use standards and thus lack the broad interoperability required for multicenter trials. Use of data standards is essential for any successful implementation of a data collection system designed to reuse patient data. 7 Successful integration of research into the patient care setting depends on a full understanding of inherent challenges, and on finding solutions adapted to the realities of the clinical, technological, and regulatory environment. 9 Successful implementations described in the literature 6,26 cite workflow incompatibility, additional research data requirements, and regulatory differences as challenges. Large-scale direct use of healthcare data for research, although advocated by many, 1–18 has thus far eluded researchers. We hypothesized that by introducing data standards and technology that enabled single source data capture within the existing clinical workflow, we would eliminate or reduce redundant data collection and entry without disrupting existing clinical practice. Our goals were to 1) examine the feasibility of using Single Source data capture to increase reuse of clinical information 2) eliminate redundant data collection, medical record abstraction, and multiple data transcription and entry processes 3) minimize disruption to clinical workflow and 4) assess the capability of open standards to enable reuse of clinical information for large-scale prospective multicenter clinical research. In the Single Source proof-of-concept study, we sought to better understand the challenges of using data captured in the healthcare setting in conjunction with appropriate standards to directly support clinical trials. ![]() A standards-based, technology-enabled process using electronic source (eSource) data collection and interchange (eSDI) 25 has the potential to reduce transcription errors, increase sponsor and site personnel efficiency, facilitate information flow, and improve timeliness of data. The Single Source project, an initiative sponsored by the Clinical Data Standards Interchange Consortium (CDISC), 24 seeks to reduce burdens associated with clinical data capture at investigational sites. 2,3,20–23 Given the existing technological capacity to support interoperability and the availability of a core set of data standards for clinical research, it is essential to explore those critical factors still needed in order to foster the convergence of healthcare and clinical research informatics. 8 Further complicating this problem is a lack of therapeutic area data content standards, perpetuating a lack of semantic specificity at the content and clinical definition levels needed to support interoperability. 19 The current system also impedes research activities by creating significant amounts of inefficiency and delay, the expense of which threaten to make clinical research prohibitively expensive and slow. Data that could benefit patients, physicians, investigators, regulators, and the biopharmaceutical industry remain sequestered in disparate databases, stored as narrative text, or confined to paper records. ![]() ![]() Many authors have endorsed secondary uses of healthcare data, including for research purposes 1–18 however, this potential remains largely untapped. Technological advances in the last 20 years have the potential to strengthen links between patient healthcare and clinical research.
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