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Cited by 232Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AIEmpathy and Medical Education

Artificial intelligence and the ongoing need for empathy, compassion and trust in healthcare

Open access
Kerasidou, Angeliki·2020·Bulletin of the World Health Organization
DOI 10.2471/blt.19.237198PMC PMC7133472
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Abstract

Empathy, compassion and trust are fundamental values of a patient-centred, relational model of health care. In recent years, the quest for greater efficiency in health care, including economic efficiency, has often resulted in the side-lining of these values, making it difficult for health-care professionals to incorporate them in practice. Artificial intelligence is increasingly being used in health care. This technology promises greater efficiency and more free time for health-care professionals to focus on the human side of care, including fostering trust relationships and engaging with patients with empathy and compassion. This article considers the vision of efficient, empathetic and trustworthy health care put forward by the proponents of artificial intelligence. The paper suggests that artificial intelligence has the potential to fundamentally alter the way in which empathy, compassion and trust are currently regarded and practised in health care. Moving forward, it is important to re-evaluate whether and how these values could be incorporated and practised within a health-care system where artificial intelligence is increasingly used. Most importantly, society needs to re-examine what kind of health care it ought to promote.

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  • The ANA Code of Ethics includes 10 provisions that encompass compassion, respect for human dignity, commitment to care, trust, advocacy, responsibility, accountability, and integrity.

    “The ANA Code of Ethics is the standard for ethical nursing practice and includes 10 provisions that encompass compassion, respect for human dignity, commitment to care, trust, advocacy, responsibility, accountability, and integrity.10”

    From Empathic and agentic artificial intelligence in nursing: perspectives on a human-centered framework for cancer care navigation in the United States of America (2026) · cites this paper as [10]

    The “Empathy, compassion and trust” section describes those values as fundamental to health care, but does not connect them to the ANA Code of Ethics. Searches for the ANA Code, its ten provisions, and the listed nursing obligations found no passage addressing the code or its contents. (LLM, conf=0.76)

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  • The ANA Code of Ethics is the standard for ethical nursing practice.

    “The ANA Code of Ethics is the standard for ethical nursing practice and includes 10 provisions that encompass compassion, respect for human dignity, commitment to care, trust, advocacy, responsibility, accountability, and integrity.10”

    From Empathic and agentic artificial intelligence in nursing: perspectives on a human-centered framework for cancer care navigation in the United States of America (2026) · cites this paper as [10]

    The “Empathy, compassion and trust” section describes values of good health-care practice, but does not discuss the ANA Code of Ethics or identify it as the standard for ethical nursing practice. Searches for the ANA Code and its provisions found no passage addressing that claim in our copy. (LLM, conf=0.76)

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References 34 · Cited by 232

Research works printed but not linked: 29

  1. [1]Emanuel EJ, Emanuel LL. Four models of the physician–patient relationship. JAMA. 1992 4 22–29; 267(16): 2221– 6. 10.1001/jama.1992.03480160079038 1556799 · DOI
  2. [2]Bauchat JR, Seropian M, Jeffries PR. Communication and empathy in the patient-centered care model: why simulation-based training is not optional. Clin Simul Nurs. 2016; 12(8): 356– 9. 10.1016/j.ecns.2016.04.003 · DOI
  3. [5]Spiro H. Commentary: the practice of empathy. Acad Med. 2009 9; 84(9): 1177– 9. 10.1097/ACM.0b013e3181b18934 19707052 · DOI
  4. [6]Halpern J. From detached concern to empathy: humanizing medical practice. New York: Oxford University Press; 2001 10.1093/acprof:osobl/9780195111194.001.0001 · DOI
  5. [7]Nussbaum M. Compassion: the basic social emotion. Soc Philos Policy. 1996; 13(01): 27– 58. 10.1017/S0265052500001515 · DOI
  6. [9]Charon R. The patient–physician relationship. Narrative medicine: a model for empathy, reflection, profession, and trust. JAMA. 2001 10 17; 286(15): 1897– 902. 10.1001/jama.286.15.1897 11597295 · DOI
  7. [10]Chin JJ. Doctor–patient relationship: a covenant of trust. Singapore Med J. 2001 12; 42(12): 579– 81. 11989581
  8. [11]O’Neill O. Autonomy and trust in bioethics. Cambridge: Cambridge University Press; 2002 10.1017/CBO9780511606250 · DOI
  9. [12]Mechanic D. Changing medical organization and the erosion of trust. Milbank Q. 1996; 74(2): 171– 89. 10.2307/3350245 8632733 · DOI
  10. [13]Halpern J. What is clinical empathy? J Gen Intern Med. 2003 8; 18(8): 670– 4. 10.1046/j.1525-1497.2003.21017.x 12911651 PMC1494899 · DOI · Paper page
  11. [14]Kelley JM, Kraft-Todd G, Schapira L, Kossowsky J, Riess H. The influence of the patient–clinician relationship on healthcare outcomes: a systematic review and meta-analysis of randomized controlled trials. PLoS One. 2014 4 9; 9(4): e94207. 10.1371/journal.pone.0094207 24718585 PMC3981763 · DOI
  12. [15]Joffe S, Manocchia M, Weeks JC, Cleary PD. What do patients value in their hospital care? An empirical perspective on autonomy centred bioethics. J Med Ethics. 2003 4; 29(2): 103– 8. 10.1136/jme.29.2.103 12672891 PMC1733711 · DOI
  13. [16]Kerasidou A, Kingori P, Legido-Quigley H. “You have to keep fighting”: maintaining healthcare services and professionalism on the frontline of austerity in Greece. Int J Equity Health. 2016 7 26; 15(1): 118. 10.1186/s12939-016-0407-8 27457098 PMC4960903 · DOI
  14. [17]Kerasidou A, Horn R. Making space for empathy: supporting doctors in the emotional labour of clinical care. BMC Med Ethics. 2016 1 27; 17(1): 8. 10.1186/s12910-016-0091-7 26818248 PMC4728886 · DOI
  15. [22]Kerasidou A. Empathy and efficiency in healthcare at times of austerity. Health Care Anal. 2019 9; 27(3): 171– 84. 10.1007/s10728-019-00373-x 31152291 PMC6667398 · DOI
  16. [23]Kerasidou A, Kingori P. Austerity measures and the transforming role of A&E professionals in a weakening welfare system. PLoS One. 2019 2 13; 14(2): e0212314. 10.1371/journal.pone.0212314 30759147 PMC6373963 · DOI
  17. [24]Darzi L. The Lord Darzi review of health and care. London: Institute for Public Policy Research, 2018.
  18. [25]Topol E. The Topol review: preparing the healthcare workforce to deliver the digital future. London: National Health Service; 2019.
  19. [28]Hannun AY, Rajpurkar P, Haghpanahi M, Tison GH, Bourn C, Turakhia MP, et al. Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nat Med. 2019 1; 25(1): 65– 9. 10.1038/s41591-018-0268-3 30617320 PMC6784839 · DOI · Paper page
  20. [29]Fraser KC, Meltzer JA, Rudzicz F. Linguistic features identify Alzheimer’s disease in narrative speech. J Alzheimers Dis. 2015; 49(2): 407– 22. 10.3233/JAD-150520 26484921 · DOI · Paper page
  21. [30]Patel BN, Rosenberg L, Willcox G, Baltaxe D, Lyons M, Irvin J, et al. Human–machine partnership with artificial intelligence for chest radiograph diagnosis. NPJ Digit Med. 2019 11 18; 2(1): 111. 10.1038/s41746-019-0189-7 31754637 PMC6861262 · DOI · Paper page
  22. [34]Nundy S, Hodgkins ML. The application of AI to augment physicians and reduce burnout [internet]. Health Affairs Blog. 2018 Sep 18. Available from: https://www.healthaffairs.org/do/10.1377/hblog20180914.711688/full/ [cited 2019 Apr 27]. · DOI
  23. [37]Wright S. Trust and trustworthiness. Philosophia. 2010; 38(3): 615– 27. 10.1007/s11406-009-9218-0 · DOI
  24. [41]McDougall RJ. Computer knows best? The need for value-flexibility in medical AI. J Med Ethics. 2019 3; 45(3): 156– 60. 10.1136/medethics-2018-105118 30467198 · DOI · Paper page
  25. [42]el Kaliouby R. We need computers with empathy. Cambridge: MIT Technology Review; 2017.
  26. [44]Srivastava K, Das RC. Empathy: process of adaptation and change, is it trainable? Ind Psychiatry J. 2016 Jan-Jun; 25(1): 1– 3. 10.4103/0972-6748.196055 28163400 PMC5248406 · DOI
  27. [45]Goldhahn J, Rampton V, Spinas GA. Could artificial intelligence make doctors obsolete? BMJ. 2018 11 7; 363: k4563. 10.1136/bmj.k4563 30404897 · DOI
  28. [46]Beresford MJ. Medical reductionism: lessons from the great philosophers. QJM. 2010 9; 103(9): 721– 4. 10.1093/qjmed/hcq057 20395240 · DOI
  29. [48]Loh E. Medicine and the rise of the robots: a qualitative review of recent advances of artificial intelligence in health. BMJ Leader. 2018; 2(2): 59– 63. 10.1136/leader-2018-000071 · DOI

Authors
Kerasidou, A.
Affiliations
University of Oxford (GB)
Corresponding author
Kerasidou, Angeliki
ORCID
Kerasidou, Angeliki
Venue
Bulletin of the World Health Organization
Publisher
WHO Press
Published
2020-01-27
Volume
98
Issue
4
Pages
245-250
ISSN
0042-9686 (ISSN-L)
DOI
10.2471/blt.19.237198
PMC
PMC7133472
OpenAlex
W3014635233
Cited by
232
References
34
Citations by year
2026: 53 · 2025: 55 · 2024: 52 · 2023: 31 · 2022: 20 · 2021: 16 · 2020: 5
FWCI
5.30
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Bulletin of the World Health Organization (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • Wellcome Trust
  • University of Oxford
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Health Sciences › Medicine › Psychiatry and Mental health › Empathy and Medical Education
Keywords
artificial intelligence in healthcare, empathy, compassion, trust in healthcare, patient-centered care, relational care, humanized care, values in health care
MeSH terms
Artificial Intelligence, Delivery of Health Care, Empathy, Humans, Trust

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