Evidence map›Paper›PMID 38638863›Full record

ArticleProceedings of the 2023 7th International Conference on Medical and Health Informatics (ICMHI 2023) : May 12-14, 2023, Kyoto, Japan. International Conference on Medical and Health Informatics (7th : 2023 : Kyoto, Japan)2023

A Study of Healthcare Team Communication Networks using Visual Analytics.

Hsiao-Ying Lu, Yiran Li, Brittany Garcia, Shin-Ping Tu, Kwan-Liu Ma

Abstract read
In one paragraph

Article in Proceedings of the 2023 7th International Conference on Medical and Health Informatics (ICMHI 2023) : May 12-14, 2023, Kyoto, Japan. International Conference on Medical and Health Informatics (7th : 2023 : Kyoto, Japan), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. L-VISP: LSTM Visualization for Interpretable Symptom Prediction in Patient Cohorts.Computer graphics forum : journal of the European Association for Computer Graphics · 2026
    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

5 authors.

Hsiao-Ying LuUniversity of California at Davis, Davis, CA, USA.
Yiran LiUniversity of California at Davis, Davis, CA, USA.
Brittany GarciaUC Davis Health, Sacramento, USA.
Shin-Ping TuUC Davis Health, Sacramento, USA.
Kwan-Liu MaUniversity of California at Davis, Davis, USA.

Funding

SMART Cancer Care Teams: Enhancing EHR Communication to Improve Interprofessional Teamwork - Diversity SupplementR01CA273058 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Kwan-Liu Ma, Daniel Sewell · 2022 to 2026
$3.6M
SCH: Smart EHR Data Analytics to Enhance Cancer Care Multiteam SystemsR01CA270454 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI MA, KWAN-LIU, TU, SHIN-PING · 2022 to 2024
$791k
NCI NIH HHS R01 CA270454NCI NIH HHS R01 CA273058
6 · The paper itself

Abstract

Cooperation among teams or individuals of healthcare professionals (HCPs) is one of the crucial factors towards patients' survival outcome. However, it is challenging to uncover and understand such factors in the complex Multiteam System (MTS) communication networks representing daily HCP cooperation. In this paper, we present a study on MTS communication networks constructed with real-world cancer patients' Electronic Health Record (EHR) access logs. We adopt a visual analytics workflow to extract associations between semantic characteristics of MTS communication networks and the patients' survival outcomes. The workflow consists of a

Indexed as

Electronic Health RecordsHealthcareInterpretabilityMachine LearningNetworksVisual Analytics

Identifiers

PMID38638863
PMCPMC11025723

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.