Modified early warning score-based clinical decision support: cost impact and clinical outcomes in sepsis.
costs, electronic health record
critical illness
electronic medical record
modified Early Warning Score
sepsis
Journal
JAMIA open
ISSN: 2574-2531
Titre abrégé: JAMIA Open
Pays: United States
ID NLM: 101730643
Informations de publication
Date de publication:
Jul 2020
Jul 2020
Historique:
received:
09
10
2019
revised:
26
02
2020
accepted:
11
04
2020
entrez:
1
8
2020
pubmed:
1
8
2020
medline:
1
8
2020
Statut:
epublish
Résumé
The objective of this study was to assess the clinical and financial impact of a quality improvement project that utilized a modified Early Warning Score (mEWS)-based clinical decision support intervention targeting early recognition of sepsis decompensation. We conducted a retrospective, interrupted time series study on all adult patients who received a diagnosis of sepsis and were exposed to an acute care floor with the intervention. Primary outcomes (total direct cost, length of stay [LOS], and mortality) were aggregated for each study month for the post-intervention period (March 1, 2016-February 28, 2017, The intervention was associated with a decrease in median total direct cost and hospital LOS by 23% ( The implementation of an mEWS-based clinical decision support system in eight acute care floors at an academic medical center was associated with reduced total direct cost and LOS for patients hospitalized with sepsis. This was seen without an associated increase in intensive care unit utilization or broad-spectrum antibiotic use. An automated sepsis decompensation detection system has the potential to improve clinical and financial outcomes such as LOS and total direct cost. Further evaluation is needed to validate generalizability and to understand the relative importance of individual elements of the intervention.
Identifiants
pubmed: 32734167
doi: 10.1093/jamiaopen/ooaa014
pii: ooaa014
pmc: PMC7382614
doi:
Types de publication
Journal Article
Langues
eng
Pagination
261-268Informations de copyright
© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association.
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