Evidence map›Paper›PMID 31743934›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2020

Evaluating a digital sepsis alert in a London multisite hospital network: a natural experiment using electronic health record data.

Kate Honeyford, Graham S Cooke, Anne Kinderlerer, Elizabeth Williamson, Mark Gilchrist, Alison Holmes, Sepsis Big Room, Ben Glampson, Abdulrahim Mulla, Ceire Costelloe

Erratum issuedOpen access · bronzeAbstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
3.4field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Kate HoneyfordGlobal Digital Health Unit, Department of Primary Care and Public Health, Imperial College London, London, United Kingdom.
Graham S CookeInfectious Diseases Section, Imperial College London, London, United Kingdom.
Anne KinderlererSt Mary's Hospital, Imperial College Healthcare NHS Trust, London, United Kingdom.
Elizabeth WilliamsonElectronic Health Records Research Group, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Mark GilchristDepartment of Infectious Diseases, Imperial College Healthcare NHS Trust, London, United Kingdom.
Alison HolmesHealth Protection Research Unit, Imperial College London, London, United Kingdom.
Sepsis Big Room
Ben GlampsonDepartment of Research Informatics, Imperial College Healthcare NHS Trust, London, United Kingdom.
Abdulrahim MullaDepartment of Research Informatics, Imperial College Healthcare NHS Trust, London, United Kingdom.
Ceire CostelloeGlobal Digital Health Unit, Department of Primary Care and Public Health, Imperial College London, London, United Kingdom.
Imperial College Healthcare NHS Trust · GBImperial College London · GBLondon School of Hygiene & Tropical Medicine · GB

Funding

Department of Health CDF-2016-09-015Department of Health NIHR129082Department of Health NIHR-BRC-P68711Medical Research Council MR/M013278/1NIDCR NIH HHS HPRU-2012-10, 047
6 · The paper itself

Abstract

objectiveThe study sought to determine the impact of a digital sepsis alert on patient outcomes in a UK multisite hospital network. MATERIALS AND

methodsA natural experiment utilizing the phased introduction (without randomization) of a digital sepsis alert into a multisite hospital network. Sepsis alerts were either visible to clinicians (patients in the intervention group) or running silently and not visible (the control group). Inverse probability of treatment-weighted multivariable logistic regression was used to estimate the effect of the intervention on individual patient outcomes. OUTCOMES: In-hospital 30-day mortality (all inpatients), prolonged hospital stay (≥7 days) and timely antibiotics (≤60 minutes of the alert) for patients who alerted in the emergency department.

resultsThe introduction of the alert was associated with lower odds of death (odds ratio, 0.76; 95% confidence interval [CI], 0.70-0.84; n = 21 183), lower odds of prolonged hospital stay ≥7 days (OR, 0.93; 95% CI, 0.88-0.99; n = 9988), and in patients who required antibiotics, an increased odds of receiving timely antibiotics (OR, 1.71; 95% CI, 1.57-1.87; n = 4622). DISCUSSION: Current evidence that digital sepsis alerts are effective is mixed. In this large UK study, a digital sepsis alert has been shown to be associated with improved outcomes, including timely antibiotics. It is not known whether the presence of alerting is responsible for improved outcomes or whether the alert acted as a useful driver for quality improvement initiatives.

conclusionsThese findings strongly suggest that the introduction of a network-wide digital sepsis alert is associated with improvements in patient outcomes, demonstrating that digital based interventions can be successfully introduced and readily evaluated.

Indexed as

Electronic Health RecordsSepsisAdultAgedAged, 80 and overAnti-Bacterial AgentsFemaleHospital MortalityHospitalsHumansLength of StayLondonMaleMiddle AgedMonitoring, PhysiologicYoung AdultAnti-Bacterial Agentsalertscritical caredigital healthearly warning scoreselectronic health recordsepsis

Identifiers

PMID31743934
PMCPMC7025344
OpenAlexW2991272467

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.