scholarly journals Clinical Decision Support Systems and Computerized Provider Order Entry: Contributions from 2020

2021 ◽  
Vol 30 (01) ◽  
pp. 172-175
Author(s):  
Damian Borbolla ◽  
Grégoire Ficheur ◽  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
The United States ◽  
Order Entry ◽  
Public Health Response ◽  
Computerized Provider Order Entry

Summary 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.

Impact of Protocol Watch on Compliance With the Surviving Sepsis Campaign

2011 ◽  
Vol 20 (4) ◽  
pp. 313-321 ◽  
Author(s):  
Karen K. Giuliano ◽  
Michele Lecardo ◽  
LuAnn Staul
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
The United States ◽  
Teaching Hospitals ◽  
Surviving Sepsis Campaign ◽  
Care Protocol

Purpose Clinical decision support systems are intended to improve patients’ care and outcomes, particularly when such systems are present at the point of care. Protocol Watch was developed as a bedside clinical decision support system to improve clinicians’ adherence to the Surviving Sepsis Campaign guidelines. This pre/post-intervention pilot study was done to evaluate the effect of Protocol Watch on compliance with 5 guidelines from the Surviving Sepsis Campaign. Methods Preintervention data on rates and time to complete the resuscitation and management bundles from the Surviving Sepsis Campaign and time to administer antibiotics were collected from intensive care units at 2 large teaching hospitals in the United States. Training on the Protocol Watch application was then provided to clinical staff in the units, and Protocol Watch was installed at all critical care beds in both hospitals. Data were collected on rates and time to completion for 5 Surviving Sepsis Campaign guidelines after installation of Protocol Watch, and univariate analyses were done to evaluate the effect of Protocol Watch on compliance with the guidelines. Results Implementation of Protocol Watch was associated with significant improvements in compliance with the resuscitation bundle (P = .01) and decreased time to administer antibiotics (P = .006). No significant changes were achieved for compliance with the management bundle or time to complete the resuscitation or management bundles. Conclusions Clinical decision support systems such as Protocol Watch may improve adherence to the Surviving Sepsis Campaign guidelines, which potentially may contribute to reduced morbidity and mortality for critically ill patients with sepsis.

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