ArticleProceedings of the SIGCHI conference on human factors in computing systems. CHI Conference2024
Designing Communication Feedback Systems To Reduce Healthcare Providers' Implicit Biases In Patient Encounters.
Article in Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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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.
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Who cites it
7 citing papers in PubMed.
- Twelve tips for teaching medical communication skills in a second language.BMC medical education · 2026Review
- Envisioning the future of primary care: intervention strategies to support patient-centered communication feedback technology.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Deploying and Examining Beacon for At-Home Patient Self-Monitoring with Critical Flicker Frequency.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2025Article
- Artificial intelligence-generated feedback on social signals in patient-provider communication: technical performance, feedback usability, and impact.JAMIA open · 2024Article
- ConverSense: An Automated Approach to Assess Patient-Provider Interactions using Social Signals.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2024Article
- Article
- Implementing artificial intelligence (AI)-supported communication tools in healthcare: System-level perspectives.Digital healthArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Healthcare providers' implicit bias, based on patients' physical characteristics and perceived identities, negatively impacts healthcare access, care quality, and outcomes. Feedback tools are needed to help providers identify and learn from their biases. To incorporate providers' perspectives on the most effective ways to present such feedback, we conducted semi-structured design critique sessions with 24 primary care providers. We found that providers seek feedback designed with transparent metrics indicating the quality of their communication with a patient and trends in communication patterns across visits. Based on these metrics and trends, providers want this feedback presented in a dashboard paired with actionable, personalized tips about how to improve their communication behaviors. Our study provides new insights for interactive systems to help mitigate the impact of implicit biases in patient-provider communication. New systems that build upon these insights could support providers in making healthcare more equitable, particularly for patients from marginalized communities.
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Registered trials
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.