Evidence map›Paper›PMID 25451991›Full record

Observational studyJournal of general internal medicine2015

Predicting and communicating risk of clinical deterioration: an observational cohort study of internal medicine residents.

John T Ratelle, Diana J Kelm, Andrew J Halvorsen, Colin P West, Amy S Oxentenko

Abstract readObservational Study
In one paragraph

Observational study in Journal of general internal medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

5 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

John T RatelleDivision of Hospital Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
Diana J Kelm
Andrew J Halvorsen
Colin P West
Amy S Oxentenko

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite its importance, little is known about internal medicine (IM) residents' ability to assess and communicate a patient's overnight risk during the resident-to-resident handoff.

objectiveTo evaluate IM residents' ability to identify patients at risk for clinical deterioration using the Patient Acuity Rating (PAR) tool (scored on a 1-7 symmetric scale; 1="Extremely unlikely", 7="Extremely likely"), and to measure how well IM residents conveyed a patient's potential for clinical deterioration during day-to-night handoff. DESIGN AND

participantsObservational cohort study of 46 postgraduate year 1 (PGY-1) and 32 postgraduate year 3 (PGY-3) internal medicine residents rotating on one of four general medicine services from October 2013 through January 2014. MAIN MEASURES: Primary outcomes were (1) level of agreement between resident handoff giver and receiver regarding patients' clinical risk and (2) accuracy of resident-assigned PAR score in predicting a patient's risk of clinical deterioration over the subsequent 24 hours. KEY

resultsAnalysis of PGY-1 giver-receiver handoff agreement revealed an intraclass correlation coefficient (ICC) (95 % CI) of 0.51 (0.45-0.56), while PGY-3 giver-receiver agreement yielded an ICC (95 % CI) of 0.42 (0.36-0.47). Based on 865 ratings of 378 patients, PGY-1 handoff giver PAR scores of 5 and 6+ were significantly associated with increased odds of clinical deterioration within 24 hours (aOR = 6.5 and 12.4; P = 0.03 and 0.005, respectively). For the 1,170 PAR ratings of 438 patients assigned by PGY-3 handoff givers, PAR scores of 4, 5, and 6+ were significantly associated with increased odds of an event within 24 hours (aORs = 6.0, 9.6, and 18.1; P = 0.03, 0.01, and 0.0008, respectively).

conclusionsThe PAR is a useful tool to quantify IM residents' judgment of patient stability, and may be particularly valuable during resident handoff, given that the level of agreement between giver and receiver regarding patient risk is only fair.

Indexed as

CommunicationSeverity of Illness IndexAgedAged, 80 and overClinical CompetenceCohort StudiesFemaleForecastingHumansInternal MedicineInternship and ResidencyMaleMiddle AgedPatient HandoffRisk Factors

Identifiers

PMID25451991
PMCPMC4370993

What OpenQuestion holds

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Registered trials

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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.