Evidence map›Paper›PMID 38408043›Full record

ArticlePLOS digital health2024

Theory of radiologist interaction with instant messaging decision support tools: A sequential-explanatory study.

John Lee Burns, Judy Wawira Gichoya, Marc D Kohli, Josette Jones, Saptarshi Purkayastha

Abstract read
In one paragraph

Article in PLOS digital health, 2024. 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. Review
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.

John Lee BurnsDepartment of Radiology & Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, United States of America.ORCID https://orcid.org/0000-0003-3188-9298
Judy Wawira GichoyaDepartment of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, United States of America.
Marc D KohliDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America.
Josette JonesDepartment of BioHealth Informatics, Indiana University Luddy School of Informatics, Computing, and Engineering, Indianapolis, Indiana, United States of America.
Saptarshi PurkayasthaDepartment of BioHealth Informatics, Indiana University Luddy School of Informatics, Computing, and Engineering, Indianapolis, Indiana, United States of America.ORCID https://orcid.org/0000-0003-3625-534X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiology specific clinical decision support systems (CDSS) and artificial intelligence are poorly integrated into the radiologist workflow. Current research and development efforts of radiology CDSS focus on 4 main interventions, based around exam centric time points-after image acquisition, intra-report support, post-report analysis, and radiology workflow adjacent. We review the literature surrounding CDSS tools in these time points, requirements for CDSS workflow augmentation, and technologies that support clinician to computer workflow augmentation. We develop a theory of radiologist-decision tool interaction using a sequential explanatory study design. The study consists of 2 phases, the first a quantitative survey and the second a qualitative interview study. The phase 1 survey identifies differences between average users and radiologist users in software interventions using the User Acceptance of Information Technology: Toward a Unified View (UTAUT) framework. Phase 2 semi-structured interviews provide narratives on why these differences are found. To build this theory, we propose a novel solution called Radibot-a conversational agent capable of engaging clinicians with CDSS as an assistant using existing instant messaging systems supporting hospital communications. This work contributes an understanding of how radiologist-users differ from the average user and can be utilized by software developers to increase satisfaction of CDSS tools within radiology.

Identifiers

PMID38408043
PMCPMC10896537

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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.