Computerized Clinical Decision Support: Contributions from 2014

Yearb Med Inform. 2015 Aug 13;10(1):119-24. doi: 10.15265/IY-2015-036.

Abstract

Objective: To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook.

Method: A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers.

Results: Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy.

Conclusions: As health information technologies spread more and more meaningfully, CDSSs are improving to answer users' needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term.

Keywords: Clinical Decision Support Systems; International Medical Informatics Association; Medical informatics; Yearbook.

Publication types

  • Review

MeSH terms

  • Anti-Bacterial Agents / therapeutic use
  • Bayes Theorem
  • Decision Support Systems, Clinical*
  • Drug Therapy, Computer-Assisted*
  • Humans
  • Precision Medicine

Substances

  • Anti-Bacterial Agents