AccScience Publishing / DP / Volume 2 / Issue 1 / DOI: 10.36922/dp.7675
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ARTICLE

Balancing innovation and trust: Assessing artificial intelligence’s role in medical history taking and physician perspectives on patient care

Felix Höpfl1* ,  Marina Schellhorn1
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1 Faculty of Applied Health and Social Science, Rosenheim Technical University of Applied Sciences, Bavaria, Germany
DP 2025, 2(1), 7675 https://doi.org/10.36922/dp.7675
Submitted: 16 December 2024 | Revised: 22 February 2025 | Accepted: 25 February 2025 | Published: 11 March 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

This study explores the potential of artificial intelligence (AI) in medical history taking (anamnesis) and assesses its acceptance using technology acceptance models. Through nine expert interviews with physicians from diverse medical backgrounds, the study aims to understand concerns and anticipated benefits of AI in the doctor–patient relationship. To demonstrate AI’s applications, digital anamnesis surveys were conducted with two actual patients, and the resulting data were interpreted by AI and reviewed by physicians. Findings indicate that physicians view AI as potentially beneficial, expecting that AI can facilitate improvements in care quality, efficiency, and time savings. Despite initial concerns about AI’s ability to address individual patient needs and its impact on the doctor–patient relationship, there is significant interest in integrating AI tools into daily practice. Key issues include patient constitution, the effort-to-benefit ratio, and potential risks to patient trust. The study identifies six areas for further research: Economic impact and cost-benefit analysis, patient acceptance and trust, stress reduction and job satisfaction, effects on doctor–patient relationships, development of verification mechanisms, and ethical and legal considerations. These findings underscore the complexities of AI integration in health care, emphasizing the need to address concerns about patient individuality, data privacy, and interpersonal relationships while harnessing AI’s potential.

Graphical abstract
Keywords
AI-enhanced anamnesis systems
AI technology acceptance
AI quality assumptions
Idana
AI in medical history taking
Funding
This research received no external funding. The study was conducted as part of the author’s academic role at Rosenheim Technical University of Applied Sciences, without any additional financial support.
Conflict of interest
The authors declare they have no competing interests.
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