Automated APACHE II and SOFA score calculation using real-world electronic medical record data in a single center.


Journal

Journal of clinical monitoring and computing
ISSN: 1573-2614
Titre abrégé: J Clin Monit Comput
Pays: Netherlands
ID NLM: 9806357

Informations de publication

Date de publication:
08 2023
Historique:
received: 18 01 2023
accepted: 01 04 2023
medline: 28 7 2023
pubmed: 19 4 2023
entrez: 19 04 2023
Statut: ppublish

Résumé

The integration of illness severity and organ dysfunction scores into clinical practice, including the APACHE II and SOFA scores, has been challenging due to constraints associated to manual score calculation. With electronic medical records (EMR), score calculation automation using data extraction scripts has emerged as a solution. We aimed to demonstrate that APACHE II and SOFA scores calculated with an automated EMR-based data extraction script predict important clinical endpoints. In this retrospective cohort study, every adult patient admitted to one of our three ICUs, between July 1, 2019, and December 31, 2020, were enrolled. For every patient, an automated ICU admission APACHE II score was calculated using EMR data and minimal clinician input. Fully automated daily SOFA scores were calculated for every patient. 4 794 ICU admissions met our selection criteria. Of these ICU admissions, 522 deaths were recorded (10.9% in-hospital mortality rate). The automated APACHE II was discriminant for in-hospital mortality (AU-ROC = 0.83 (95% CI 0.81-0.85)). We observed an association between the APACHE II score and ICU LOS, with a statistically significant mean increase of 1.1 days of ICU LOS (1.1 [1-1.2]; p =  < .0001) for each 10 units increase in APACHE score. SOFA score curves did not discrimate significantly between survivors and non-survivors. A partially automated APACHE II score, calculated with real-world EMR data using an extraction script, is associated with in-hospital mortality risk. The automated APACHE II score could potentially constitute an acceptable surrogate of ICU acuity to be used in resource allocation and triaging, especially in time of high demand for ICU beds.

Identifiants

pubmed: 37074523
doi: 10.1007/s10877-023-01010-8
pii: 10.1007/s10877-023-01010-8
pmc: PMC10113718
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1023-1033

Informations de copyright

© 2023. The Author(s), under exclusive licence to Springer Nature B.V.

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Auteurs

Alexandre Mutchmore (A)

Department of Medicine, Division of Critical Care Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada.

François Lamontagne (F)

Department of Medicine, Division of Critical Care Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada.
Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, 3001, 12Th Avenue N, Sherbrooke, QC, J1H 5N4, Canada.

Michaël Chassé (M)

Department of Medicine (Critical Care), University of Montreal Hospital, Montreal, Canada.
University of Montreal Hospital Research Center (CRCHUM), Montreal, Canada.

Lynne Moore (L)

Department of Social and Preventive Medicine, Faculty of Medicine, Laval University, Québec City, Canada.

Michael Mayette (M)

Department of Medicine, Division of Critical Care Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada. michael.mayette@usherbrooke.ca.
Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, 3001, 12Th Avenue N, Sherbrooke, QC, J1H 5N4, Canada. michael.mayette@usherbrooke.ca.

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