Evidence map›Paper›PMID 24851196›Full record

ArticleIEEE transactions on human-machine systems2013

Considering Factors of and Knowledge About Patients in Handover Assessment.

Sharon Meth, Ellen J Bass, George Hoke

Abstract read
In one paragraph

Article in IEEE transactions on human-machine systems, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Sharon MethDepartment of Systems and Information Engineering, University of Virginia, Charlottesville, VA 22903 USA.
Ellen J BassCollege of Information Science and Technology, College of Nursing and Health Professions, Drexel University, Philadelphia, PA 19104 USA.
George HokeDepartment of Medicine, University of Virginia, Charlottesville, VA 22903 USA.

Funding

Systems Engineering Focus on Clinical InformaticsT15LM009462 · NLM · UNIVERSITY OF VIRGINIA · PI BASS, ELLEN J · 2007 to 2012
$3.6M
NLM NIH HHS T15 LM009462
6 · The paper itself

Abstract

The healthcare system is moving from one primary physician who assumes responsibility for each patient to a more team-based approach. Thus, assessing team communication is critical. This study characterizes and assesses the quality of hospitalist handover communications at shift change using the literature recommended content and language form elements. Quality handovers should contain the following content: patient identifiers, active issues, and care plans. Quality handovers also should include utterances in the following language forms: explanations, rationales, and directives. Interviews, observation, recording, and conversation analysis of hospitalist handover communications were used. Hospitalist handover utterances were assigned both content and language form codes. The proportion of quality element verbalization across all patient handovers was calculated. In addition, the impact of patient factors (new admission, new problem, acuity level) and handover receiver knowledge on the inclusion of quality elements was examined. The 106 individual patient handovers across 16 handover sessions were recorded. 39% contained all six quality elements. While the majority of handovers contained five out of six quality elements, only 48% included directives. There was also no difference in the inclusion of quality elements based on patient factors or handover receiver knowledge. Hospitalist handovers are lacking in directives. Efforts to improve handovers through enhanced electronic medical record systems and training may need to expand to hospitalists and other attending level physicians.

Indexed as

Communicationscontinuity of care transitionshandoverhuman factorspatient safetyquality improvementshift changesign out

Identifiers

PMID24851196
PMCPMC4025927

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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.