Evidence map›Paper›PMID 41726505›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2024

Leveraging Provocative Design Methods to Address Implicit Bias in Clinical Interactions through Technology.

Deepthi Mohanraj, Raina Langevin, Libby Shah, Janice Sabin, Brian R Wood, Wanda Pratt, Nadir Weibel, Andrea L Hartzler

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2024. 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

8 authors.

Deepthi MohanrajUniversity of Washington, Seattle, Washington.
Raina LangevinUniversity of Washington, Seattle, Washington.
Libby ShahUniversity of Washington, Seattle, Washington.
Janice SabinUniversity of Washington, Seattle, Washington.
Brian R WoodUniversity of Washington, Seattle, Washington.
Wanda PrattUniversity of Washington, Seattle, Washington.
Nadir WeibelUniversity of California San Diego, La Jolla, California.
Andrea L HartzlerUniversity of Washington, Seattle, Washington.

Funding

Transform Dissemination and Implementation Science in CTSA ProgramsUL1TR002319 · NCATS · UNIVERSITY OF WASHINGTON · PI John K. Amory · 2017 to 2026
$100.0M
UnBIASED: Understanding Biased patient-provider Interaction And Supporting Enhanced DiscourseR01LM013301 · NLM · UNIVERSITY OF WASHINGTON · PI HARTZLER, ANDREA L. · 2019 to 2023
$3.0M
NCATS NIH HHS UL1 TR002319NLM NIH HHS R01 LM013301
6 · The paper itself

Abstract

Implicit bias impacts the quality of patient-clinician interactions, influencing patient outcomes and trust in healthcare. Most interventions to mitigate bias rely solely on expensive human assessments, rather than leveraging AI technology with clinician input. To explore clinician-envisioned interventions, we conducted interviews with 16 primary care clinicians using provocative design methods to facilitate innovative ideation on using technology to address implicit bias. Themes from interviews included: patient communication monitoring, clinician self-awareness, systemic solutions, optimizing workflow, clinician education, and patient feedback. These envisioned interventions provide design considerations for technology-based implicit bias feedback tools. The broad range of innovative solutions generated by clinicians at various career stages reflects the utility of provocative design methods in unlocking creative thinking among a population that is not often encouraged to think beyond structured real-world constraints.

Indexed as

Attitude of Health PersonnelPhysician-Patient RelationsBiasDigital HealthHumansInterviews as Topic

Identifiers

PMID41726505
PMCPMC12919562

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.