Title: Standardising clinical data elements

Authors: Meredith Nahm, Anita Walden, Brian McCourt, Karen Pieper, Emily Honeycutt, Carol D. Hamilton, Robert A. Harrington, Jane Diefenbach, Bron Kisler, Mead Walker, W. Ed Hammond

Addresses: Clinical Research Informatics, DTMI Biomedical Informatics Core, Duke Translational Medicine Institute, Durham, NC, USA; Academic Programs, Duke Center for Health Informatics, Duke University Medical Center, Durham, NC, USA. ' DTMI Biomedical Informatics Core, Duke Translational Medicine Institute, Duke University Medical Center, Durham, NC, USA. ' Clinical Research Informatics, Duke Clinical Research Institute, Duke University Medical Center, Durham, NC, USA. ' Clinical Trials Statistical Operations, Statistics Group, Duke Clinical Research Institute, Duke University Medical Center, Durham, NC, USA. ' Outcomes Research and Assessment Group, Statistics Group, Duke Clinical Research Institute, Duke University Medical Center, Durham, NC, USA. ' Health and Development Sciences, Family Health International, Durham, NC, USA; Department of Medicine, Duke University Medical Center, Durham, NC, USA. ' Duke Clinical Research Institute, Department of Medicine, Division of Cardiology, Duke University Medical Center, Durham, NC, USA. ' PharmaStat LLC, Arlington, VA, USA. ' Strategic Initiatives, Clinical Data Interchange Standards Consortium, Austin, Texas, USA. ' Patient Safety Work Group, Health Level 7, USA. ' Duke Center for Health Informatics Department of Community and Family Medicine Department of Biomedical Engineering Fuqua School of Business, Duke University, Durham, NC, USA

Abstract: We report the development and implementation of a methodology for standardising clinical data elements. The methodology, piloted using Tuberculosis (TB) and Acute Coronary Syndromes (ACS) domains, relies on clinicians for natural language definitions and on informaticists for computable specifications. Data elements are represented using the ISO 11179 standard, UML class, and activity diagrams. Over 2000 candidate data elements were compiled for each domain. Initial sets of 21 data elements for ACS and 139 for TB, plus 300 valid values, were standardised and made publicly available. The methodology is now used in HL7 for data element definition in other clinical areas.

Keywords: standards; EMR; clinical definitions; interoperability; clinical data elements; HL7; domain analysis modelling; standardisation; tuberculosis; TB; acute coronary syndromes; ISO 11179; UML class; activity diagrams; data element definition.

DOI: 10.1504/IJFIPM.2010.040213

International Journal of Functional Informatics and Personalised Medicine, 2010 Vol.3 No.4, pp.314 - 341

Published online: 21 May 2011 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article