Evidence map›Paper›PMID 30872387›Full record

Trial reportBMJ quality & safety2019

Electronic health record-based clinical decision support alert for severe sepsis: a randomised evaluation.

Norman Lance Downing, Joshua Rolnick, Sarah F Poole, Evan Hall, Alexander J Wessels, Paul Heidenreich, Lisa Shieh

Registry-linked trialOpen access · bronzeAbstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BMJ quality & safety, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05213923 (ED Tracking Sheet Implementation), which is not on this map. Cited by 62 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 5 pooled it
9.6field-weighted citation impact, top 1% 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.

NCT05213923 nacompletednot on this mapstarted 2021, after this paper: background citation

ED Tracking Sheet Implementation

TypeinterventionalSponsorDartmouth-Hitchcock Medical CenterRan2021 to 2022Enrolled194ConditionsSepsis, Severe Sepsis, Systemic Inflammatory Response SyndromeArmsED Sepsis Tracking Sheet
3 · Its place in the literature

Who cites it

62 citing papers in PubMed, 5 syntheses or guidelines pooled it, 106 citations in OpenAlex.

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2 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Norman Lance DowningDepartment of Medicine - Biomedical Informatics Research, Hospital Medicine, and Primary Care and Population Health, Stanford University, Stanford, California, USA ldowning@stanford.edu.ORCID 0000-0002-2133-9244
Joshua RolnickDivision of General Internal Medicine, Department of Medicine and the National Clinician Scholars Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Sarah F PooleBiomedical Informatics Training Program, Stanford University, Stanford, California, USA.
Evan HallMedicine, Hematology and Oncology, Stanford University, Stanford, California, USA.
Alexander J WesselsMedicine, Stanford School of Medicine, Stanford, California, USA.
Paul HeidenreichDepartment of Medicine, Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA.
Lisa ShiehMedicine, Stanford School of Medicine, Stanford, California, USA.
Stanford University · USStanford Medicine · USPhiladelphia VA Medical Center · USStanford Health Care · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSepsis remains the top cause of morbidity and mortality of hospitalised patients despite concerted efforts. Clinical decision support for sepsis has shown mixed results reflecting heterogeneous populations, methodologies and interventions.

objectivesTo determine whether the addition of a real-time electronic health record (EHR)-based clinical decision support alert improves adherence to treatment guidelines and clinical outcomes in hospitalised patients with suspected severe sepsis.

designPatient-level randomisation, single blinded.

settingMedical and surgical inpatient units of an academic, tertiary care medical centre. PATIENTS: 1123 adults over the age of 18 admitted to inpatient wards (intensive care units (ICU) excluded) at an academic teaching hospital between November 2014 and March 2015.

interventionsPatients were randomised to either usual care or the addition of an EHR-generated alert in response to a set of modified severe sepsis criteria that included vital signs, laboratory values and physician orders. MEASUREMENTS AND MAIN

resultsThere was no significant difference between the intervention and control groups in primary outcome of the percentage of patients with new antibiotic orders at 3 hours after the alert (35% vs 37%, p=0.53). There was no difference in secondary outcomes of in-hospital mortality at 30 days, length of stay greater than 72 hours, rate of transfer to ICU within 48 hours of alert, or proportion of patients receiving at least 30 mL/kg of intravenous fluids.

conclusionsAn EHR-based severe sepsis alert did not result in a statistically significant improvement in several sepsis treatment performance measures.

Indexed as

Decision Support Systems, ClinicalElectronic Health RecordsAgedAged, 80 and overFemaleGuideline AdherenceHealth Care SurveysHealth Knowledge, Attitudes, PracticeHospital MortalityHumansIntensive Care UnitsMaleMiddle AgedSepsisalertclinical decision supportelectronic health recordprotocolsepsis

Identifiers

PMID30872387
PMCPMC6860967
OpenAlexW2921640653

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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.