Development and evaluation of a comprehensive clinical decision support taxonomy: Comparison of front-end tools in commercial and internally developed electronic health record systems

Adam Wright, Dean F. Sittig, Joan S. Ash, Joshua Feblowitz, Seth Meltzer, Carmit McMullen, Ken Guappone, Jim Carpenter, Joshua Richardson, Linas Simonaitis, R. Scott Evans, W. Paul Nichol, Blackford Middleton

Research output: Contribution to journalArticlepeer-review

101 Scopus citations

Abstract

Background: Clinical decision support (CDS) is a valuable tool for improving healthcare quality and lowering costs. However, there is no comprehensive taxonomy of types of CDS and there has been limited research on the availability of various CDS tools across current electronic health record (EHR) systems. Objective: To develop and validate a taxonomy of front-end CDS tools and to assess support for these tools in major commercial and internally developed EHRs. Study design and methods: We used a modified Delphi approach with a panel of 11 decision support experts to develop a taxonomy of 53 front-end CDS tools. Based on this taxonomy, a survey on CDS tools was sent to a purposive sample of commercial EHR vendors (n=9) and leading healthcare institutions with internally developed state-of-the-art EHRs (n=4). Results: Responses were received from all healthcare institutions and 7 of 9 EHR vendors (response rate: 85%). All 53 types of CDS tools identified in the taxonomy were found in at least one surveyed EHR system, but only 8 functions were present in all EHRs. Medication dosing support and order facilitators were the most commonly available classes of decision support, while expert systems (eg, diagnostic decision support, ventilator management suggestions) were the least common. Conclusion: We developed and validated a comprehensive taxonomy of front-end CDS tools. A subsequent survey of commercial EHR vendors and leading healthcare institutions revealed a small core set of common CDS tools, but identified significant variability in the remainder of clinical decision support content.

Original languageEnglish (US)
Pages (from-to)232-242
Number of pages11
JournalJournal of the American Medical Informatics Association
Volume18
Issue number3
DOIs
StatePublished - May 2011

ASJC Scopus subject areas

  • Health Informatics

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