Evidence map›Paper›PMID 29159719›Full record

ArticleJournal of medical systems2017

Effect of a Real-Time Electronic Dashboard on a Rapid Response System.

Grant S Fletcher, Barry A Aaronson, Andrew A White, Reena Julka

Abstract read
In one paragraph

Article in Journal of medical systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 5 pooled it
–field-weighted citation impact
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

17 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Systematic review and narrative synthesis of computerized audit and feedback systems in healthcare.Journal of the American Medical Informatics Association : JAMIA · 2022
    Pooled it
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  5. Novel displays of patient information in critical care settings: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2019
    Pooled it
  6. Review
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  17. Rapid response systems.Resuscitation · 2018
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Grant S FletcherDepartment of Medicine, Hospital Medicine Program, Harborview Medical Center, University of Washington, 325 Ninth Avenue, Box 359780, Seattle, WA, 98104, USA.
Barry A AaronsonDepartment of Hospital Medicine, Virginia Mason Medical Center, 925 Seneca St, Seattle, WA, 98101, USA.
Andrew A WhiteDepartment of Medicine and the Center for Scholarship in Patient Care Quality and Safety, University of Washington, 1959 NE Pacific, Box 356429, Seattle, WA, 98195, USA. andwhite@uw.edu.
Reena JulkaDupage Medical Group, 25 N Winfield St, Winfield, IL, 60190, USA.

Funding

University of Washington Biomedical Informatics and Data Science Research Training ProgramT15LM007442 · NLM · UNIVERSITY OF WASHINGTON · PI JOHN H. GENNARI, Andrea L. Hartzler · 2002 to 2026
$19.6M
NLM NIH HHS T15 LM007442U.S. National Library of Medicine (US) LM007442-07
6 · The paper itself

Abstract

A rapid response system (RRS) may have limited effectiveness when inpatient providers fail to recognize signs of early patient decompensation. We evaluated the impact of an electronic medical record (EMR)-based alerting dashboard on outcomes associated with RRS activation. We used a repeated treatment study in which the dashboard display was successively turned on and off each week for ten 2-week cycles over a 20-week period on the inpatient acute care wards of an academic medical center. The Rapid Response Team (RRT) dashboard displayed all hospital patients in a single view ranked by severity score, updated in real time. The dashboard could be seen within the EMR by any provider, including RRT members. The primary outcomes were the incidence rate ratio (IRR) of all RRT activations, unexpected ICU transfers, cardiopulmonary arrests and deaths on general medical-surgical wards (wards). We conducted an exploratory analysis of first RRT activations. There were 6736 eligible admissions during the 20-week study period. There was no change in overall RRT activations (IRR = 1.14, p = 0.07), but a significant increase in first RRT activations (IRR = 1.20, p = 0.04). There were no significant differences in unexpected ICU transfers (IRR = 1.15, p = 0.25), cardiopulmonary arrests on general wards (IRR = 1.46, p = 0.43), or deaths on general wards (IRR = 0.96, p = 0.89). The introduction of the RRT dashboard was associated with increased initial RRT activations but not overall activations, unexpected ICU transfers, cardiopulmonary arrests, or death. The RRT dashboard is a novel tool to help providers recognize patient decompensation and may improve initial RRT notification.

Indexed as

Clinical DeteriorationAcademic Medical CentersAdultAgedAged, 80 and overElectronic Health RecordsFemaleHeart ArrestHospital MortalityHospital Rapid Response TeamHumansMaleMiddle AgedPilot ProjectsTime FactorsElectronic alertsElectronic dashboardsMedical early warning scoreRapid response systemsSituational awareness

Identifiers

PMID29159719
PMCPMC12908619

What OpenQuestion holds

Textmetadata
LicenceTDM
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.