Evidence map›Paper›PMID 25846349›Full record

ArticleJournal of community hospital internal medicine perspectives2015

TRACER: an 'eye-opener' to the patient experience across the transition of care in an internal medicine resident program.

Lauren B Meade, Susana L Hall, Reva W Kleppel, Kevin T Hinchey

Abstract read
In one paragraph

Article in Journal of community hospital internal medicine perspectives, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Editor's notes.Journal of community hospital internal medicine perspectives · 2015
    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

4 authors.

Lauren B MeadeBaystate Medical Center, Tufts University School of Medicine, Springfield, MA, USA; Lauren.meade@bhs.org.
Susana L HallRemedy Partners, Inc, Yale New Haven Hospital, New Haven, CT, USA.
Reva W KleppelBaystate Medical Center, Tufts University School of Medicine, Springfield, MA, USA.
Kevin T HincheyBaystate Medical Center, Tufts University School of Medicine, Springfield, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA safe patient transition requires a complex set of physician skills within the interprofessional practice.

objectiveTo evaluate a rotation which applies self-reflection and workplace learning in a TRAnsition of CarE Rotation (TRACER) for internal medicine (IM) residents. TRACER is a 2-week required IM resident rotation where trainees join a ward team as a quality officer and follow patients into postacute care.

methodsIn 2010, residents participated in semistructured, one-on-one interviews as part of ongoing program evaluation. They were asked what they had learned on TRACER, the year prior, and how they used those skills in their practice. Using transcripts, the authors reviewed and coded each transcript to develop themes.

resultsFive themes emerged from a qualitative, grounded theory analysis: seeing things from the other side, the 'ah ha' moment of fragmented care, team collaboration including understanding nursing scope of practice in different settings, patient understanding, and passing the learning on. TRACER gives residents a moment to breathe and open their eyes to the interprofessional practice setting and the patient's experience of care in transition.

conclusionsResidents learn about transitions of care through self-reflection. This learning is sustained over time and is valued enough to teach to their junior colleagues.

Indexed as

educationgrounded theoryinterprofessional practiceprofessional identityreflectiontransition of care

Identifiers

PMID25846349
PMCPMC4387321

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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.