Development of a new seamless data stream from EMR to EDC system using SS‐MIX2 standards applied for observational research in diabetes mellitus. Issue 1 (15th November 2018)

• Record Type: Journal Article
• Authors: Takenouchi, Kiyoteru; Yuasa, Keisuke; Shioya, Masahiro; Kimura, Michio; Watanabe, Hiroshi; Oki, Yutaka; Hakamata, Akio; Watanabe, Hiroshi; Fukushima, Masanori
• Is Part Of: Learning health systems. Volume 3:Issue 1(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-11-15
• Subjects: 21 CFR Part 11 -- CDISC -- CSV -- EMR -- IHE RFD -- SS‐MIX2; Medical care -- Research -- Periodicals; Medical informatics -- Periodicals; Health planning -- Periodicals; 362.1068
• DOI: 10.1002/lrh2.10072
• Languages: English
• ISSNs: 2379-6146

Abstract

Abstract: Over the last decade, redundant entry of data in electronic medical records (EMR) for health care and electronic data capture (EDC) systems for research has been the typical medical research methodology. The corresponding data transcription this methodology requires not only increases the burden for clinician investigators and clinical research coordinators (CRCs), but it also decreases the quality of data. We designed and developed a new standards‐based and platform‐independent system to use data in the EMR to directly populate clinical data management systems in the EDC to eliminate the need for data transcription, streamline the clinical research process, and reduce clinician burden. Standardized structured medical information eXchange2 (SS‐MIX2) was implemented along with the Integrating the Healthcare Enterprise (IHE) Retrieve Form for Data Capture (RFD) Integration Profile. Standards from Clinical Data Interchange Standards Consortium (CDISC) were used to define metadata for research data collection forms and as a means to standardize data exchange semantics. These standards and the associated methodology were applied to observational research in patients with diabetes mellitus. The system we developed complies with global requirements for regulated research. It provides a standard‐based and platform‐independent method that can serve to accelerate the cycle of a learning health system.