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Clinical Decision Support Systems and Computerized Provider Order Entry: Contributions from 2020.
Borbolla, Damian; Ficheur, Grégoire.
  • Borbolla D; Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.
  • Ficheur G; Univ. Lille, CHU Lille, ULR 2694 - METRICS, Public health dept, Lille, France.
Yearb Med Inform ; 30(1): 172-175, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1392952
ABSTRACT

OBJECTIVES:

To summarize research contributions published in 2020 in the field of clinical decision support systems (CDSS) and computerized provider order entry (CPOE), and select the best papers for the Decision Support section of the International Medical Informatics Association (IMIA) Yearbook 2021.

METHODS:

Two bibliographic databases were searched for papers referring to clinical decision support systems. From search results, section editors established a list of candidate best papers, which were then peer-reviewed by seven external reviewers. The IMIA Yearbook editorial committee finally selected the best papers on the basis of all reviews including the section editors' evaluation.

RESULTS:

A total of 1,919 articles were retrieved. 15 best paper candidates were selected, the reviews of which resulted in the selection of two best papers. One paper reports on the use of electronic health records to support a public health response to the COVID-19 pandemic in the United States. The second paper proposes a combination of CDSS and telemedicine as a technology-based intervention to improve the outcomes of depression as part of a cluster trial.

CONCLUSIONS:

As shown by the number and the variety of works related to clinical decision support, research in the field is very active. This year's selection highlighted the application of CDSS to fight COVID-19 and a combined technology-based strategy to improve the treatment of depression.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Telemedicine / Decision Support Systems, Clinical / Medical Order Entry Systems Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: Yearb Med Inform Year: 2021 Document Type: Article Affiliation country: S-0041-1726534

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Telemedicine / Decision Support Systems, Clinical / Medical Order Entry Systems Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: Yearb Med Inform Year: 2021 Document Type: Article Affiliation country: S-0041-1726534