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Using artificial intelligence to analyse and teach communication in healthcare
Open accessAbstract
Communication is a core component of effective healthcare that impacts many patient and doctor outcomes, yet is complex and challenging to both analyse and teach. Human-based coding and audit systems are time-intensive and costly; thus, there is considerable interest in the application of artificial intelligence to this topic, through machine learning using both supervised and unsupervised learning algorithms. In this article we introduce health communication, its importance for patient and health professional outcomes, and the need for rigorous empirical data to support this field. We then discuss historical interaction coding systems and recent developments in applying artificial intelligence (AI) to automate such coding in the health setting. Finally, we discuss available evidence for the reliability and validity of AI coding, application of AI in training and audit of communication, as well as limitations and future directions in this field. In summary, recent advances in machine learning have allowed accurate textual transcription, and analysis of prosody, pauses, energy, intonation, emotion and communication style. Studies have established moderate to good reliability of machine learning algorithms, comparable with human coding (or better), and have identified some expected and unexpected associations between communication variables and patient satisfaction. Finally, application of artificial intelligence to communication skills training has been attempted, to provide audit and feedback, and through the use of avatars. This looks promising to provide confidential and easily accessible training, but may be best used as an adjunct to human-based training.
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“Some AI systems are designed to provide employees with communication -oriented games and activities to help them practise their communication skills and change their communication strategies (Butow & Hoque, 2020).”
From The Impact of Artificial Intelligence on Workers' Skills: Upskilling and Reskilling in Organisations (2023) · cites this paper as Butow & Hoque, 2020
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“while other educators have proposed using AI to analyze and teach communication in health care [42].”
From Reimagining Core Entrustable Professional Activities for Undergraduate Medical Education in the Era of Artificial Intelligence (2023) · cites this paper as [42]
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“Some AI systems are designed to provide employees with communication - oriented games and activities to help them practise their communication skills and change their communication strategies (Butow & Hoque, 2020).”
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Metadata
- Authors
- Butow, P., & Hoque, E.
- Affiliations
- The University of Sydney (AU)
- Corresponding author
- Butow, Phyllis
- ORCID
- Butow, Phyllis
- Venue
- The Breast
- Publisher
- Elsevier BV
- Published
- 2020-04
- Volume
- 50
- Pages
- 49-55
- ISSN
- 0960-9776 (ISSN-L)
- PMC
- PMC7375542
- OpenAlex
- W2999911199
- Cited by
- 118
- References
- 49
- Citations by year
- 2026: 21 · 2025: 24 · 2024: 23 · 2023: 18 · 2022: 12 · 2021: 14 · 2020: 6
- FWCI
- 13.05
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The Breast (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › General Health Professions › Patient-Provider Communication in Healthcare
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- health communication, physician-patient communication, artificial intelligence, machine learning, communication skills training, audit and feedback, avatars, patient satisfaction, textual transcription
- MeSH terms
- Machine Learning, Artificial Intelligence, Humans, Reproducibility of Results, Health Communication, Health Information Systems
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