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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Jun 17, 2021
Date Accepted: Oct 29, 2021

The final, peer-reviewed published version of this preprint can be found here:

Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Adult Inpatients: Scoping Review

Ackermann K, Baker J, Green M, Fullick M, Varinli H, Westbrook J, Li L

Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Adult Inpatients: Scoping Review

J Med Internet Res 2022;24(2):e31083

DOI: 10.2196/31083

PMID: 35195528

PMCID: 8908200

Computerized Clinical Decision Support Systems for Early Detection of Sepsis Among Adult Inpatients: a Scoping Review

  • Khalia Ackermann; 
  • Jannah Baker; 
  • Malcolm Green; 
  • Mary Fullick; 
  • Hilal Varinli; 
  • Johanna Westbrook; 
  • Ling Li

ABSTRACT

Background:

Sepsis is a significant cause of morbidity and mortality worldwide. Early detection of septic patients followed by rapid treatment initiation improves patient outcomes and saves lives. Hospitals are increasingly utilizing computerized clinical decision support (CCDS) systems for the rapid identification of adult septic patients.

Objective:

This scoping review aimed to systematically describe studies reporting on the use and evaluation of CCDS systems for early detection of adult sepsis inpatients.

Methods:

The protocol for this scoping review has been previously published. Ten electronic databases (MEDLINE, Embase, CINAHL, The Cochrane database, LILACS, Scopus, Web of Science, OpenGrey, clinicaltrials.gov, and PQDT) were comprehensively searched to identify relevant studies. Title, abstract, and full-text screening were performed by two independent reviewers using predefined eligibility criteria. Data charting was performed by one reviewer with a second reviewer double checking a random sample of studies. Any disagreements were discussed with input from a third reviewer. In this review we present the results for adult inpatients, including studies that do not specify patient age.

Results:

A search of the electronic databases retrieved 12139 studies following duplicate removal. We identified 124 studies for inclusion after title, abstract, full-text screening, and hand-searching were complete. Nearly all studies (n=121, 97.6%) were published after 2009. Half the studies were journal articles (n=65), and the remainder were conference abstracts and theses (n=54 and 5 respectively). Most studies used a single cohort (n=54; 43.5%) or before-after (n=42; 33.9%) approach. Of all 124 included studies, patient outcomes were the most frequently reported outcomes (n=107; 86.3%), followed by sepsis treatment and management (n=75; 60.5%), CCDS usability (n=14; 11.3%), and cost outcomes (n=9; 7.3%). For sepsis identification, the systemic inflammatory response syndrome (SIRS) criteria were the most commonly used, either alone (n=50; 40.3%), combined with organ dysfunction (n=28; 22.6%) or combined with other criteria (n=23; 18.5%). Over half of the CCDS systems (n=68; 54.8%) were implemented alongside other sepsis-related interventions.

Conclusions:

The current body of literature investigating the implementation of CCDS systems for the early detection of adult sepsis inpatients is extremely diverse. There is substantial variability in study design, CCDS criteria and characteristics, and outcomes measured across the identified literature. Future research on CCDS system usability, cost, and impact on sepsis morbidity is needed.


 Citation

Please cite as:

Ackermann K, Baker J, Green M, Fullick M, Varinli H, Westbrook J, Li L

Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Adult Inpatients: Scoping Review

J Med Internet Res 2022;24(2):e31083

DOI: 10.2196/31083

PMID: 35195528

PMCID: 8908200

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