A scoping review of clinical decision support tools that generate new knowledge to support decision making in real time

Anna Ostropolets, Linying Zhang, George Hripcsak

Research output: Contribution to journalReview articlepeer-review

22 Scopus citations

Abstract

Objective: A growing body of observational data enabled its secondary use to facilitate clinical care for complex cases not covered by the existing evidence. We conducted a scoping review to characterize clinical decision support systems (CDSSs) that generate new knowledge to provide guidance for such cases in real time. Materials and Methods: PubMed, Embase, ProQuest, and IEEE Xplore were searched up to May 2020. The abstracts were screened by 2 reviewers. Full texts of the relevant articles were reviewed by the first author and approved by the second reviewer, accompanied by the screening of articles’ references. The details of design, implementation and evaluation of included CDSSs were extracted. Results: Our search returned 3427 articles, 53 of which describing 25 CDSSs were selected. We identified 8 expert-based and 17 data-driven tools. Sixteen (64%) tools were developed in the United States, with the others mostly in Europe. Most of the tools (n ¼ 16, 64%) were implemented in 1 site, with only 5 being actively used in clinical practice. Patient or quality outcomes were assessed for 3 (18%) CDSSs, 4 (16%) underwent user acceptance or usage testing and 7 (28%) functional testing. Conclusions: We found a number of CDSSs that generate new knowledge, although only 1 addressed confounding and bias. Overall, the tools lacked demonstration of their utility. Improvement in clinical and quality outcomes were shown only for a few CDSSs, while the benefits of the others remain unclear. This review suggests a need for a further testing of such CDSSs and, if appropriate, their dissemination.

Original languageEnglish
Pages (from-to)1968-1976
Number of pages9
JournalJournal of the American Medical Informatics Association
Volume27
Issue number12
DOIs
StatePublished - Dec 1 2020

Keywords

  • Clinical decision support system
  • Electronic health records
  • Evidence-based medicine
  • Observational data

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