Abstract
BackgroundClinical trials use many case report forms (CRFs) per patient. Because of the astronomical number of potential CRFs, data element re-use at the design stage is attractive to foster compatibility of data from different trials. The objective of this work is to assess the technical feasibility of a CRF editor with connection to a public metadata registry (MDR) to support data element re-use.ResultsBased on the Medical Data Models portal, an ISO/IEC 11179-compliant MDR was implemented and connected to a web-based CRF editor. Three use cases were implemented: re-use at the form, item group and data element levels.ConclusionsCRF design with data element re-use from a public MDR is feasible. A prototypic system is available. The main limitation of the system is the amount of available MDR content.
Highlights
Clinical trials use many case report forms (CRFs) per patient
Data management in clinical trials is resource-intensive because many case report forms (CRFs) need to be collected: on average, about 180 pages per patient [1]
This article refers to a CRF as an individual documentation form; each trial applies a set of CRFs
Summary
Clinical trials use many case report forms (CRFs) per patient. Because of the astronomical number of potential CRFs, data element re-use at the design stage is attractive to foster compatibility of data from different trials. The objective of this work is to assess the technical feasibility of a CRF editor with connection to a public metadata registry (MDR) to support data element re-use. Conclusions: CRF design with data element re-use from a public MDR is feasible. Data management in clinical trials is resource-intensive because many case report forms (CRFs) need to be collected: on average, about 180 pages per patient [1]. The overlap of data elements between two CRFs is very small when these CRFs are designed independently, even if the medical subject matter is similar. This problem of related but not matching data structures has been described in the literature, such as regarding clinical decision support: ‘The largest barrier to linking knowledge-based medical decision support systems to heterogeneous [databases] is the variety of ways in which similar data are represented’
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