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  5. Digital innovation in healthcare: quantifying the impact of digital sepsis screening tools on patient outcomes-a multi-site natural experiment
 
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Digital innovation in healthcare: quantifying the impact of digital sepsis screening tools on patient outcomes-a multi-site natural experiment
File(s)
e101141.full.pdf (495.29 KB)
Published version
Author(s)
Honeyford, Kate
Timney, Alf
Lazzarino, Runa
Welch, John
Brent, Andrew Jonathan
more
Type
Journal Article
Abstract
Introduction The National Health Service (NHS) ‘move to digital’ incorporating electronic patient record systems (EPR) facilitates the translation of paper-based screening tools into digital systems, including digital sepsis alerts. We evaluated the impact of sepsis screening tools on in-patient 30-day mortality across four multi-hospital NHS Trusts, each using a different algorithm for early detection of sepsis.

Methods Using quasi-experimental methods, we investigated the impact of the screening tools. Individual-level EPR data for 718 000 patients between 2010 and 2020 were extracted to assess the impact on a target cohort and control cohort using interrupted time series analysis, based on a binomial regression model. We included one Trust which uses a paper-based screening tool to compare the impact of digital and paper-based interventions, and one Trust which did not introduce a sepsis screening tool, but did introduce an EPR.

Results All Trusts had lower odds of mortality, between 5% and 12%, after the introduction of the sepsis screening tool, before adjustment for pre-existing trends or patient casemix. After adjustment for existing trends, there was a significant reduction in mortality in two of the three Trusts which introduced sepsis screening tools. We also observed age-specific effects across Trusts.

Conclusion Our findings confirm that patients with similar profiles have a lower mortality risk, consistent with our previous work. This study, conducted across multiple NHS Trusts, suggests that alerts could be tailored to specific patient groups based on age-related effects. Different Trusts may require unique indicators, thresholds, actions and treatments. Including additional EPR information could further enhance personalised care.
Date Issued
2025-04-27
Date Acceptance
2025-04-03
Citation
BMJ Health & Care Informatics, 2025, 32 (1)
URI
https://hdl.handle.net/10044/1/125694
URL
https://informatics.bmj.com/content/32/1/e101141
DOI
https://www.dx.doi.org/10.1136/bmjhci-2024-101141
ISSN
2632-1009
Publisher
BMJ Publishing Group
Journal / Book Title
BMJ Health & Care Informatics
Volume
32
Issue
1
Copyright Statement
© Author(s) (or their employer(s)) 2025. Re-use permitted under CC BY. Published by BMJ Group.
License URL
https://creativecommons.org/licenses/by/4.0/
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/40288808
PII: bmjhci-2024-101141
Subjects
Decision Support Systems, Clinical
Electronic Health Records
Emergency Service, Hospital
Health Care Sciences & Services
Life Sciences & Biomedicine
Medical Informatics
Science & Technology
Publication Status
Published
Coverage Spatial
England
Article Number
e101141
Date Publish Online
2025-04-27
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