Evidence map›Paper›PMID 34396056›Full record

ArticleJAMIA open2021

Classification and analysis of asynchronous communication content between care team members involved in breast cancer treatment.

Bryan D Steitz, Lina Sulieman, Jeremy L Warner, Daniel Fabbri, J Thomas Brown, Alyssa L Davis, Kim M Unertl

Abstract read
In one paragraph

Article in JAMIA open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Article
  7. Managing diabetes during treatment for breast cancer: oncology and primary care providers' views on barriers and facilitators.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2022
    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

7 authors.

Bryan D SteitzDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0003-2066-8692
Lina SuliemanDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Jeremy L WarnerDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Daniel FabbriDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
J Thomas BrownDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Alyssa L DavisDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Kim M UnertlDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0003-0094-3677

Funding

Vanderbilt Biomedical Informatics Training ProgramT15LM007450 · NLM · VANDERBILT UNIVERSITY · PI Jessica S. Ancker, Bradley A. Malin · 2002 to 2026
$19.7M
NLM NIH HHS T15 LM007450
6 · The paper itself

Abstract

objectiveA growing research literature has highlighted the work of managing and triaging clinical messages as a major contributor to professional exhaustion and burnout. The goal of this study was to discover and quantify the distribution of message content sent among care team members treating patients with breast cancer. MATERIALS AND

methodsWe analyzed nearly two years of communication data from the electronic health record (EHR) between care team members at Vanderbilt University Medical Center. We applied natural language processing to perform sentence-level annotation into one of five information types: clinical, medical logistics, nonmedical logistics, social, and other. We combined sentence-level annotations for each respective message. We evaluated message content by team member role and clinic activity.

resultsOur dataset included 81 857 messages containing 613 877 sentences. Across all roles, 63.4% and 21.8% of messages contained logistical information and clinical information, respectively. Individuals in administrative or clinical staff roles sent 81% of all messages containing logistical information. There were 33.2% of messages sent by physicians containing clinical information-the most of any role. DISCUSSION AND

conclusionOur results demonstrate that EHR-based asynchronous communication is integral to coordinate care for patients with breast cancer. By understanding the content of messages sent by care team members, we can devise informatics initiatives to improve physicians' clerical burden and reduce unnecessary interruptions.

Indexed as

breast cancerburnoutelectronic health recordsmultidisciplinary communicationworkflow

Identifiers

PMID34396056
PMCPMC8358477

What OpenQuestion holds

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LicenceCC BY-NC
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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.