Understanding the impact of Artificial Intelligence on physician-patient relationship: a revisitation of conventional relationship models in the light of new technological frontiers

Main Article Content

Francesca Greco
Mario Picozzi

Keywords

physician-patient relationship, relationship models, healthcare, artificial intelligence

Abstract

The physician-patient relationship has undergone a transition throughout the ages. The introduction of Artificial Intelligence (AI) in recent years, however, is redefining this relationship. The four main relationship models described by Emanuel in 1992 are known as paternalistic, informative, interpretive, and deliberative. The aim of this study is to understand how conventional models of doctor-patient relationships are changing when considering the impact AI has on medical practice.


The introduction of AI could strengthen the physician's role resulting in the so-called digital paternalism or even undermining the physician's role.


Also, doctors and patients could experience decision paralysis when AIs’ recommendations are difficult to understand or explain to patients and it may affect the organizational aspects of healthcare contexts. It becomes necessary to define the source of the information presented to the patient.


On another hand, AI could increase the patient's trust in the doctor by knowing that various therapeutic choices are being discussed and fully explained.


It’s complicated to understand whether the trust relationship established between doctor and patient remains bi-univocal, by incorporating AI in the clinician’s figure, or whether AI must be introduced as a separate entity implying an asymmetry in this relationship.


Shared decision-making, guidelines and training, together with an effort in communication are fundamental to best incorporate AI into clinical practice. It is relevant to educate doctors on the new models of relationships that can be created, in addition to studying patient populations within the context of these models’ framework.

Abstract 22 | PDF Downloads 14

References

1. Honavar SG. Patient-physician relationship – Communication is the key. Indian J Ophthalmol 2018; 66:1527-8.
2. Ridd M, Shaw A, Lewis G, Salisbury C. The patient-doctor relationship: A synthesis of the qualitative literature on patients’ perspectives. Br J Gen Pract. 2009;59(561):268-275.
3. Nagy M, Sisk B. STATE OF THE ART AND SCIENCE How Will Artificial Intelligence Affect Patient-Clinician Relationships? AMA J Ethics. 2020;22(5):395-400.
4. Agarwal AK, Murinson BB. New Dimensions in Patient-Physician Interaction: Values, Autonomy, and Medical Information in the Patient-Centered Clinical Encounter. Rambam Maimonides Med J. 2012;3(3):e0017.
5. Szasz TS, Hollender MH. A contribution to the philosophy of medicine: the basic models of the doctor-patient relationship. AMA Arch Intern Med. 1956;97(5):585-592.
6. Kaba R, Sooriakumaran P. The evolution of the doctor-patient relationship. Int J Surg. 2007;5(1):57-65.
7. Aoun A, Al Hayek S, El Jabbour F. The need for a new model of the physician–patient relationship: A challenge for modern medical practice. Fam Med Prim Care Rev. 2018;20(4):379-384.
8. Emanuel EJ, Emanuel LL. Four models of the physician-patient relationship. JAMA J Am Med Assoc. 1992;267(16):2221-2226.
9. Ahuja AS. What is the best model of the physician-patient relationship? J Eval Clin Pract. 2019;25(6):1111-1112.
10. Clarke G, Rosencrance G, Hall RT. Physician-patient relations: No more models. Am J Bioeth. 2004;4(2):W16-W19.
11. Tan SSL, Goonawardene N. Internet health information seeking and the patient-physician relationship: A systematic review. J Med Internet Res. 2017;19(1).
12. Kerasidou A. Artificial intelligence and the ongoing need for empathy, compassion and trust in healthcare. Bull World Health Organ. 2020;98(4):245-250.
13. LaRosa E, Danks D. Impacts on Trust of Healthcare AI. AIES 2018 - Proc 2018 AAAI/ACM Conf AI, Ethics, Soc. Published online 2018:210-215.
14. Salla E, Pikkarainen M, Leväsluoto J, Blackbright H, Johansson PE. AI innovations and their impact on healthcare and medical expertise. In: ISPIM Innovation Symposium. The International Society for Professional Innovation Management (ISPIM). 2018:1-15.
15. Churcher PR. The impact of artificial intelligence on leisure. AI Soc. 1991;5(2):147-155.
16. De Micco F, Fineschi V, Banfi G, et al. From COVID-19 Pandemic to Patient Safety: A New “Spring” for Telemedicine or a Boomerang Effect? Front Med. 2022;9(June):1-12.
17. Aminololama-Shakeri S, López JE. The doctor-patient relationship with artificial intelligence. Am J Roentgenol. 2019;212(2):308-310.
18. Ilkilic I. Reshaping the Patient-Physician Relationship through Artificial Intelligence in Medicine? -Promises, Opportunities, and Ethical Challenges. J AI Humanit. 2020;6(0):9-31.
19. Kühler M. Exploring the phenomenon and ethical issues of AI paternalism in health apps. Bioethics. 2022;36(2):194-200.
20. Triberti S, Durosini I, Pravettoni G. A “Third Wheel” Effect in Health Decision Making Involving Artificial Entities: A Psychological Perspective. Front Public Heal. 2020;8(April):1-9.
21. Nov O, Aphinyanaphongs Y, Lui YW, et al. The transformation of patient-clinician relationships with AI-based medical advice. Commun ACM. 2021;64(3):46-48.
22. Paranjape K, Schinkel M, Panday RN, Car J, Nanayakkara P. Introducing artificial intelligence training in medical education. JMIR Med Educ. 2019;5(2).
23. Kundu S. How will artificial intelligence change medical training? Commun Med. 2021;1(1):8-10.
24. Grossi AA, Nicoli F, de Feo TM, et al. The 3-T Model of Informed Consent for Nonstandard Risk Donors: A Proposal for Transplant Clinical Practice. Transplant Direct. 2021;7(11):1-8.
25. Grossi AA, De Feo TM, Ambrosini A, Picozzi M. Shared decision-making and disclosure of adverse events: critical aspects for the quality and safety of kidney transplant practice. J Nephrol. 2022 May;35(4):1305-1307. Epub 2021 Nov 16. PMID: 34787797.