» Articles » PMID: 37081503

The Impact of Artificial Intelligence on the Person-centred, Doctor-patient Relationship: Some Problems and Solutions

Overview
Publisher Biomed Central
Date 2023 Apr 20
PMID 37081503
Authors
Affiliations
Soon will be listed here.
Abstract

Artificial intelligence (AI) is often cited as a possible solution to current issues faced by healthcare systems. This includes the freeing up of time for doctors and facilitating person-centred doctor-patient relationships. However, given the novelty of artificial intelligence tools, there is very little concrete evidence on their impact on the doctor-patient relationship or on how to ensure that they are implemented in a way which is beneficial for person-centred care.Given the importance of empathy and compassion in the practice of person-centred care, we conducted a literature review to explore how AI impacts these two values. Besides empathy and compassion, shared decision-making, and trust relationships emerged as key values in the reviewed papers. We identified two concrete ways which can help ensure that the use of AI tools have a positive impact on person-centred doctor-patient relationships. These are (1) using AI tools in an assistive role and (2) adapting medical education. The study suggests that we need to take intentional steps in order to ensure that the deployment of AI tools in healthcare has a positive impact on person-centred doctor-patient relationships. We argue that the proposed solutions are contingent upon clarifying the values underlying future healthcare systems.

Citing Articles

Applications of Machine Learning in the Diagnosis and Prognosis of Patients with Chiari Malformation Type I: A Scoping Review.

Symeou S, Lampros M, Zagorianakou P, Voulgaris S, Alexiou G Children (Basel). 2025; 12(2).

PMID: 40003345 PMC: 11853870. DOI: 10.3390/children12020244.


Commentary on "Can AI Answer My Questions? Utilizing Artificial Intelligence in the Perioperative Assessment for Abdominoplasty Patients".

Habibabadi M, Bouya S, Mamaghani A Aesthetic Plast Surg. 2025; .

PMID: 39984666 DOI: 10.1007/s00266-025-04776-1.


Advancing Medical Research Through Artificial Intelligence: Progressive and Transformative Strategies: A Literature Review.

Al-Qudimat A, Fares Z, Elaarag M, Osman M, Al-Zoubi R, Aboumarzouk O Health Sci Rep. 2025; 8(2):e70200.

PMID: 39980823 PMC: 11839394. DOI: 10.1002/hsr2.70200.


Cultural variation in trust and acceptability of artificial intelligence diagnostics for dementia.

Chandra A, Senthilvel K, Anjum R, Uchegbu I, Smith L, Beaumont H J Alzheimers Dis. 2025; :13872877251319353.

PMID: 39956979 PMC: 7617421. DOI: 10.1177/13872877251319353.


The Use of AI in Mental Health Services to Support Decision-Making: Scoping Review.

Auf H, Svedberg P, Nygren J, Nair M, Lundgren L J Med Internet Res. 2025; 27:e63548.

PMID: 39854710 PMC: 11806275. DOI: 10.2196/63548.


References
1.
Dagher L, Shi H, Zhao Y, Marrouche N . Wearables in cardiology: Here to stay. Heart Rhythm. 2020; 17(5 Pt B):889-895. DOI: 10.1016/j.hrthm.2020.02.023. View

2.
Young A, Amara D, Bhattacharya A, Wei M . Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review. Lancet Digit Health. 2021; 3(9):e599-e611. DOI: 10.1016/S2589-7500(21)00132-1. View

3.
Singer T, Klimecki O . Empathy and compassion. Curr Biol. 2014; 24(18):R875-R878. DOI: 10.1016/j.cub.2014.06.054. View

4.
McDougall R . Computer knows best? The need for value-flexibility in medical AI. J Med Ethics. 2018; 45(3):156-160. DOI: 10.1136/medethics-2018-105118. View

5.
Hojat M, Louis D, Markham F, Wender R, Rabinowitz C, Gonnella J . Physicians' empathy and clinical outcomes for diabetic patients. Acad Med. 2011; 86(3):359-64. DOI: 10.1097/ACM.0b013e3182086fe1. View