Evidence map›Paper›PMID 30984828›Full record

ArticleMedEdPORTAL : the journal of teaching and learning resources2016

Team-Based Simulation for Medical Student Handoff Education.

Alanna Higgins Joyce

Abstract read
In one paragraph

Article in MedEdPORTAL : the journal of teaching and learning resources, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Hyperkalemic Arrest: Developing Team Cognition.MedEdPORTAL : the journal of teaching and learning resources · 2017
    Article
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

1 author.

Alanna Higgins JoyceAssistant Professor, Department of Pediatrics, Northwestern University The Feinberg School of Medicine.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionGood handoffs require teamwork, clear communication, a cognitively safe environment, and a good understanding of the patient's medical needs. Complex tertiary care training institutions require multiple handoffs over a patient's time in the hospital. Medical students need better handoff education. We designed a handoff training exercise using a simulated patient care environment for students to practice and observe multiple handoffs over time.

methodsAn initial large-group didactic session provides direct instruction on handoffs. In small groups, students are subsequently assigned roles as individual physicians in a chain of providers during a simulated patient hospitalization over several days, with an additional student as an observer. Blinded to any prior discussion, student physicians sequentially give and receive handoffs about the patient from a previous physician as their simulated hospital course evolves. The observer shares his or her insights, and a large-group structured debriefing exercise follows.

resultsIn both 2015 and 2016, we implemented this session with a cohort of 30 fourth-year medical students. Most recently we implemented this with chief residents, and a group of 20 third-year pediatric clerkship students. We reviewed a selection of the discussion guides and found reporters/ observers noted that participants stated the primary problem 95% of the time (19 of 20 handoffs), the patient acuity 90% of the time (18 of 20 handoffs), and a clear contingency plan 85% of the time (17 of 20 handoffs). DISCUSSION: We found students initially to be preoccupied with making correct clinical decisions instead of giving effective handoffs, and consequently we clarified details and adjusted clinical information to be more transparent. Results suggest the session achieves our goals of using a structured handoff method to communicate higher-level information and debrief effectively with peers. We envision this activity to be applicable to teaching handoffs to residents, nurses, and other health care professionals, as well as possibly in diverse clinical environments or in collaboration with outpatient providers.

Indexed as

DebriefingFeedbackHandoffsPatient HandoffSimulationSmall-Group Learning

Identifiers

PMID30984828
PMCPMC6440419

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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.