Enjeux éthiques à l’utilisation éventuelle de prédicteurs des préférences du patient pour soutenir la prise de décision substituée
DOI :
https://doi.org/10.7202/1126615arMots-clés :
prise de décision, soins de fin de vie, inaptitude décisionnelle, consentement substitué, principisme, autonomie relationnelle, bienfaisance/non-malfaisance, justiceLangue(s) :
FrenchRésumé
En 2010, Annette Rid et David Wendler proposaient que soient développés des prédicteurs des préférences du patient (PPP) pour guider les décisions de soins pour une personne inapte dont les volontés sont inconnues. Un PPP serait construit à partir des corrélations observées entre les préférences de soins et les caractéristiques sociodémographiques de répondants à un sondage. Il serait ensuite utilisé pour prédire les volontés inconnues du patient sur la base de ses propres caractéristiques. Un PPP pourrait améliorer la capacité à fournir aux patients inaptes des soins qui correspondent à leurs préférences, en plus d’atténuer la détresse que ressentent de nombreux décideurs substituts en raison de l’incertitude quant aux volontés du patient. Malgré ces attraits, de nombreuses objections au PPP ont été formulées au cours des 15 dernières années. Nous souhaitions mieux comprendre le débat éthique entourant ces outils d’aide à la décision, afin de déterminer s’il est opportun d’en entreprendre le développement. S’appuyant sur un modèle conceptuel de la prise de décision en contexte de démence, nous avons analysé 65 publications traitant d’enjeux éthiques associés au PPP. Les enjeux relevés ont été catégorisés selon le principe éthique auquel ils se rattachent. Nous concluons en faveur du développement de PPP, en autant qu’ils servent à soutenir, et non à remplacer, les décisions humaines. Nous soulignons ensuite le besoin d’évaluer leur acceptabilité sociale et leur performance réelle sur le terrain. Enfin, nous proposons des mesures susceptibles de réduire les risques associés à leur utilisation et de renforcer la confiance des utilisateurs.
Références
1. Société Alzheimer du Canada. Les multiples facettes des troubles neurocognitifs au Canada. Société Alzheimer du Canada; 2025.
2. Mattos MK, Gibson JS, Wilson D, et al. Shared decision-making in persons living with dementia: A scoping review. Dementia. 2023;22(4):875-909.
3. Wendler D. Promoting the values for surrogate decision-making. JAMA. 2022;328(3):243-4.
4. Kelly B, Rid A, Wendler D. Systematic review: Individuals’ goals for surrogate decision-making. Journal of the American Geriatrics Society. 2012;60(5):884-95.
5. Rid A, Wesley R, Pavlick M, et al. Patients’ priorities for treatment decision making during periods of incapacity: quantitative survey. Palliative & Supportive Care. 2015;13(5):1165-83.
6. Jardas EJ, Wesley R, Pavlick M, Wendler D, Rid A. Patients’ priorities for surrogate decision-making: possible influence on misinformed beliefs. AJOB Empirical Bioethics. 2022;13(3):137-51.
7. Loi concernant les soins de fin de vie. RLRQ, 2024, c. S-32.0001.
8. Plaisance A, Lalonde S-A. Planification anticipée des soins, expertise notariale à consolider. Magazine de la Chambre des notaires du Québec. 2024;32(4):42-8.
9. Anderson BK, Mihilli S, Kumaresh M, et al. Advance care planning for seniors diagnosed with dementia: A scoping review of the Canadian literature. Canadian Journal on Aging. 2022;41(3):377-403.
10. Bernier L, Régis C. Regard critique sur le régime québécois des directives médicales anticipées comme véritable consécration de l’autonomie. Revue générale de droit médical. 2017;62:35-64.
11. Bernier L, Régis C. Improving advance medical directive: Lessons from Quebec. IRPP Insight. No. 26, Mar 2019.
12. Morrison RS. Advance directives/care planning: Clear, simple, and wrong. Journal of Palliative Medicine. 2020;23(7):878-9.
13. Sulmasy DP. Why dementia-specific advance directives are a misguided idea. Journal of the American Geriatrics Society. 2020;68(7):1603-5.
14. Code civil du Québec. Articles 12 et 15. L.Q. 1991, c. 64.
15. Buchanan AR, Brock DW. Deciding for Others: The Ethics of Surrogate Decision Making. New York: Cambridge University Press; 1990.
16. Shalowitz DI, Garrett-Mayer E, Wendler D. The accuracy of surrogate decision makers: A systematic review. Archives of Internal Medicine. 2006;166(5):493-7.
17. Bravo G, Sene M, Arcand M. Surrogate inaccuracy in predicting older adults’ desire for life-sustaining interventions in the event of decisional incapacity: Is it due in part to erroneous quality-of-life assessments? International Psychogeriatrics. 2017;29(7):1062-8.
18. Spalding R. Accuracy in surrogate end-of-life medical decision-making: A critical review. Applied Psychology: Health and Well-Being. 2021;13(1):3-33.
19. Rid A, Wendler D. Can we improve treatment decision-making for incapacitated patients? Hastings Center Report. 2010;40(5):36-45.
20. Wendler D. A call for a patient preference predictor. Critical Care Medicine. 2021;49(6):877-80.
21. Rogers AH, Lopez RP. Systematic review revisited, 2010-2020: The effect on surrogates of making treatment decisions for others. Journal of Palliative Care. 2023;38(1):71-7.
22. Rid A, Wendler D. Use of a patient preference predictor to help make medical decisions for incapacitated patient. Journal of Medicine and Philosophy. 2014;39(2):104-29.
23. Rid A, Wendler D. Treatment decision making for incapacitated patients: Is development and use of a patient preference predictor feasible? Journal of Medicine and Philosophy. 2014;39(2):130-52.
24. Smucker WD, Houts RM, Danks JH, et al. Modal preferences predict elderly patients’ life-sustaining treatment choices as well as patients’ chosen surrogates do. Medical Decision Making. 2000;20(3):271-80.
25. Houts RM, Smucker WD, Jacobson JA, Ditto PH, Danks JH. Predicting elderly outpatients’ life-sustaining treatment preferences over time: the majority rules. Medical Decision Making. 2002;22(1):39-52.
26. Shalowitz DI, Garret-Mayer E, Wendler D. How should treatment decisions be made for incapacitated patients, and why? PLoS Medicine. 2007;4(3):e35.
27. Wendler D, Wesley B, Pavlick M, Rid A. A new method for making treatment decisions for incapacitated patients: what do patients think about the use of a patient preference predictor? Journal of Medical Ethics. 2016;42(4):235-41.
28. Howard D, Rivlin A, Candilis P, et al. Surrogate perspectives on patient preference predictors: Good idea, but I should decide how they are used. AJOB Empirical Bioethics. 2022;13(2):125-35.
29. Biller-Andorno N, Ferrario A, Joebges S, et al. AI support for ethical decision-making around resuscitation: Proceed with care. Journal of Medical Ethics. 2022;48(3):175-83.
30. Ferrario A, Gloeckler S, Biller-Andorno N. Ethics of the algorithmic prediction of goal of care preferences: From theory to practice. Journal of Medical Ethics. 2023;49(3):165-74.
31. Earp BD, Porsdam Mann SP, Allen J, et al. A personalized patient preference predictor for substituted judgments in healthcare: technically feasible and ethically desirable. American Journal of Bioethics. 2024;24(7):13-26.
32. Jardas EJ, Wasserman D, Wendler D. Autonomy-based criticisms of the patient preference predictor. Journal of Medical Ethics. 2022;48(5):304-10.
33. Makins N. Algorithms advise, humans decide: The evidential role of the patient preference predictor. Journal of Medical Ethics. 2026;52(e1):e30-35.
34. McCullough LB, Coverdale JH, Chervenak FA. Constructing a systematic review for argument-based clinical ethics literature: The example of concealed medications. Journal of Medicine and Philosophy. 2007;32(1):65-76.
35. McDougall R. Systematic reviews in bioethics: Types, challenges, and value. Journal of Medicine and Philosophy. 2014;39(1):89-97.
36. O’Neil C. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York: Crown Publishers; 2016.
37. Bengio Y, Régis C. Il y a urgence à adopter la Loi sur l’intelligence artificielle et les données. La Presse. 19 avril 2023.
38. Lamanna C, Byrne L. Should artificial intelligence augment medical decision making? The case for an autonomy algorithm. AMA Journal of Ethics. 2018;20(9):e902-10.
39. Biller-Andorno N, Biller A. Algorithm-aided prediction of patient preferences – An ethics sneak peek. New England Journal of Medicine. 2019;381(15):1480-5.
40. Hubbard R, Greenblum J. Surrogates and artificial intelligence: Why AI trumps family. Science and Engineering Ethics. 2020;26(6):3217-27.
41. Berg J. Response to open peer commentaries on "Surrogate decision making in the internet age". American Journal of Bioethics. 2012;12(10):W1-2.
42. Rid A. Will a patient preference predictor improve treatment decisions making for incapacitated patients? Journal of Medicine and Philosophy. 2014;39(2):99-103.
43. Breen CM, Abernethy AP, Abbott KH, Tulsky JA. Conflict associated with decisions to limit life-sustaining treatment in intensive care units. Journal of General Internal Medicine. 2001;16(5):283-9.
44. Mason TM, Tofthagen CS, Buck HG. Complicated grief: Risk factors, protective factors, and interventions. Journal of Social Work in End-of-Life and Palliative Care. 2020;16(2):151-74.
45. Davies N, De Souza T, Rait G, Meehan J, Sampson EL. Developing an applied model for making decisions towards the end of life about care for someone with dementia. PLoS One. 2021;16(5):e0252464.
46. Légaré F, Stacey D, Gagnon S, et al. Validating a conceptual model for an inter-professional approach to shared decision making: A mixed methods study. Journal of Evaluation in Clinical Practice. 2011;17(4):554-64.
47. Gomez-Virseda C, de Maeseneer Y, Gastmans C. Relational autonomy: What does it mean and how is it used in end-of-life care? A systematic review of argument-based ethics literature. BMC Medical Ethics. 2019;20:76.
48. Gomez-Virseda C, de Maeseneer Y, Gastmans C. Relational autonomy in end-of-life care ethics: A contextualized approach to real-life complexities. BMC Medical Ethics. 2020; 21:50.
49. Bernier L, Bernatchez S, Beaudry AS. L’avortement tardif et l’aide médicale à mourir au-delà de l’autonomie individuelle: comment réguler les pratiques pour assurer le vivre ensemble? Canadian Journal of Bioethics/Revue canadienne de bioéthique. 2022;5(2):1-15.
50. Klein E. Relational autonomy and the clinical relationship in dementia care. Theoretical Medicine and Bioethics. 2022;43(4):277-88.
51. Fried TR. Giving up the objective of providing goal-concordant care: Advance care planning for improving caregiver outcomes. Journal of the American Geriatrics Society. 2022;70(10):3006-11.
52. Beauchamp TL, Childress JL. Principles of Biomedical Ethics. Oxford: Oxford University Press; 2019.
53. Nancy B. c. Hôtel-Dieu de Québec. 1992 R.J.Q. 361 (C.S.).
54. Jonsen AR, Siegler M, Winslade WJ. Clinical Ethics: A Practical Approach to Ethical Decisions in Clinical Medicine. New York: McGraw-Hill Education; 2022.
55. Gundersen T, Baeroe K. Ethical algorithmic advice: Some reasons to pause and think twice. American Journal of Bioethics. 2022;22(7):26-8.
56. Institut national de santé publique du Québec. Le « principisme » et les cadres de référence en matière d’éthique en santé publique. Gouvernement du Québec; 2016.
57. Conseil de recherches en sciences humaines du Canada, Conseil de recherches en sciences naturelles et en génie du Canada, Instituts de recherche en santé du Canada. Énoncé de politique des trois Conseils : Éthique de la recherche avec des êtres humains. Gouvernement du Canada; décembre 2022.
58. Page K. The four principles: Can they be measured and do they predict ethical decision making? BMC Medical Ethics. 2012;13:10.
59. Meslin EM, Sutherland HJ, Lavery JV, Till JE. Principlism and the ethical appraisal of clinical trials. Bioethics. 1995;9(5):399-418.
60. Quinn GP, Stearsman DK, Campo-Engelstein L, Murphy D. Preserving the right to future children: An ethical case analysis. American Journal of Bioethics. 2012;12(6):38-43.
61. Hall H, Smithard DG. A principlist justification of physical restraint in the emergency department. New Bioethics. 2021;27(2):176-84.
62. Monteverde E. Respect for individual autonomy and a collective benefit: Arguments in favor of compulsory SARS-CoV-2 vaccination among health care professionals. Archivos Argentinos de Pediatria. 2021;119(4):e298-e302.
63. Mackensie C, Stoljar N (éds.). Relational Autonomy: Feminist Perspectives on Autonomy, Agency, and the Social Self. New York: Oxford University Press; 2000.
64. Largent EA, Clapp J, Blumenthal-Barby JS, et al. Deciding with others: Interdependent decision making. Hastings Center Report. 2022;52(6):23-32.
65. Cordeiro JJ, Kirjanenko M. Relational autonomy, the ethics of responsibility, and supported decision-making for patients with diminished capacity. AJOB Neuroscience. 2023;14(3):244-6.
66. Blackler L. Compromised autonomy. When families pressure patients to change their wishes. Journal of Hospice & Palliative Nursing. 2016;18(4):284-9.
67. Semler LR, Robinson EM, Cremens MC, Romain F. An end-of-life ethics consult in the ICU. Who has the final say–The patient or the family? CHEST. 2025;67(3):825-30.
68. Siddiqui S. A wider understanding of a patient’s relational autonomy at the time of death. Journal of Clinical Ethics. 2022;33(1):58-62.
69. Ho A. Relational autonomy or undue pressure? Family’s role in medical decision-making. Scandinavian Journal of Caring Sciences. 2008;22(1):128-35.
70. Berger JT. Patients’ interests in their family members’ well-being: An overlooked, fundamental consideration within substituted judgments. Journal of Clinical Ethics. 2005;16(1):3-10.
71. McIntree M-F, Madigan McCown L, Chessa F, Hutchinson R. “The patient is being pressured!” Coercion versus relational autonomy. Journal of Palliative Medicine. 2024;27(7):964-7.
72. Lee G. Navigating complex end-of-life decisions in a family-centric society. Nursing Ethics. 2020;27(4):1003-11.
73. Laryionava K, Pfeil TA, Dietrich M, et al. The second patient? Family members of cancer patients and their role in end-of-life decision making. BMC Palliative Care. 2018;17:29.
74. Sherwin S, Winsby M. A relational perspective on autonomy for older adults residing in nursing homes. Health Expectations. 2010;14(2):182-90.
75. Downie J, Llewellyn J (éditeurs.) Being Relational: Reflections on Relational Theory and Health Law. Vancouver: UBC Press; 2012.
76. Wasserman D, Wendler D. Response to commentaries: “autonomy-based criticisms of the patient preference predictor”. Journal of Medical Ethics. 2023;49(8):580-2.
77. Sharadin NP. Patient preference predictors and the problem of naked statistical evidence. Journal of Medical Ethics. 2018;44(12):857-62.
78. Brock DW. Reflections on the patient preference predictor proposal. Journal of Medicine and Philosophy. 2014;39(2):153-60.
79. O’Neil C. Commentary on ‘Autonomy-based criticisms of the patient preference predictor’. Journal of Medical Ethics. 2022;48(5):315-6.
80. Ditto PH, Clark CJ. Predicting end-of-life treatment preferences: Perils and practicalities. Journal of Medicine and Philosophy. 2014;39(2):196-204.
81. Lindemann H, Lindemann Nelson J. The surrogate’s authority. Journal of Medicine and Philosophy. 2014;39(2):161-8.
82. Kim SYH. Improving medical decisions for incapacitated persons: Does focusing on “accurate predictions” lead to an inaccurate picture? Journal of Medicine and Philosophy. 2014;39(2);187-95.
83. Um S. Autonomy, shared agency and prediction. Journal of Medical Ethics. 2022;48(5):313-4.
84. Wendler D, Wesley R, Pavlick M, Rid A. Do patients want their families or their doctors to make treatments decisions in the event of incapacity, and why? AJOB Empirical Bioethics. 2016;7(4):251-9.
85. Sulmasy DP, Hugues MT, Yenokyan G, et al. The Trial of Ascertaining Individual Preferences for Loved Ones’ Role in End-of-Life Decisions (TAILORED) Study: A randomized controlled trial to improve surrogate decision making. Journal of Pain and Symptom Management. 2017;54(4):455-65.
86. Sulmasy DP, Hugues MT, Thompson RE, et al. How would terminally ill patients have others make decisions for them in the event of decisional incapacity? A longitudinal study. Journal of the American Geriatrics Society. 2007;55(12): 1981-8.
87. John S. Patient preference predictors, apt categorization, and respect for autonomy. Journal of Medicine and Philosophy. 2014;39(2):169-77.
88. John SD. Messy autonomy: Commentary on patient preference predictors and the problem of naked statistical evidence. Journal of Medical Ethics. 2018;44(12):864.
89. Sharadin N. Personalized patient preference predictors are neither technically feasible nor ethically desirable. American Journal of Bioethics. 2024;24(7):62-5.
90. Sharadin N. Should aggregate patient preference data be used to make decisions on behalf of unrepresented patients? AMA Journal of Ethics. 2019;21(7):E566-74.
91. Schwan B. Sovereignty, authenticity and the patient preference predictor. Journal of Medical Ethics. 2022;48(5):311-2.
92. Tribe LH. Trial by mathematics: Precision and ritual in the legal process. Harvard Law Review. 1971;84(6):1329-93.
93. Mast L. Against autonomy: How proposed solutions to the problems of living wills forgot its underlying principle. Bioethics. 2020;34(3):264-71.
94. Mainz JT. The patient preference predictor and the objection from higher-order preferences. Journal of Medical Ethics. 2023;49(3):221-2.
95. Jesudason E. Fracking our humanity. Journal of Medical Ethics. 2023;49(3):181-2.
96. Klugman CM, Gerke S. Rise of the bioethics AI: Curse or blessing? American Journal of Bioethics. 2022;22(7):35-7.
97. Tretter M, Samhammer D. For the sake of multifacetedness. Why artificial intelligence patient preference predictor system shouldn’t be for next of kin. Journal of Medical Ethics. 2023;49(3):175-6.
98. Wendler D, Rid A. Systematic review: The effect on surrogates of making treatment decisions for others. Annals of Internal Medicine. 2011;154(5):336-46.
99. Schwan B. Weighing patient preferences: Lessons for a patient preference predictor. American Journal of Bioethics. 2024;24(7):38-40.
100. Rahimzadeh V, Lawson J, Baek J, Dove ES. Automating justice: An ethical responsibility of computational bioethics. American Journal of Bioethics. 2022;22(7):30-3.
101. Drolet M-J. A typology of ethical issues to better support the development of ethical sensitivity among healthcare professionals. Canadian Journal of Bioethics/Revue canadienne de bioéthique. 2024;7(4):96-101.
102. Meier LJ, Hein A, Diepold K, Buyx A. Clinical Ethics – To compute, or not to compute? American Journal of Bioethics. 2022;22(12):W1-4.
103. Diaz Milian R, Bhattacharyya A. Artificial intelligence paternalism. Journal of Medical Ethics. 2023;49(3):183-4.
104. Ferrario A, Gloeckler S, Biller-Andorno N. AI knows best? Avoiding the traps of paternalism and other pitfalls of AI-based patient preference prediction. Journal of Medical Ethics. 2023;49(3):185-6.
105. Dresser R. Law, ethics, and the patient preference predictor. Journal of Medicine and Philosophy. 2014;39(2):178-86.
106. Alzheimer’s Disease International, Aguzzoli E, Comas-Herrera A, Farina N, Evans-Lacko S, Read S. World Alzheimer Report 2024: Global Changes in Attitudes to Dementia. Alzheimer’s Disease International; 2024.
107. Meier LJ. Systemising triage: COVID-19 guidelines and their underlying theories of distributive justice. Medicine, Health Care and Philosophy. 2022;25(4):703-14.
108. Benzinger L, Ursin F, Balke W-T, Kacprowski T, Salloch S. Should artificial intelligence be used to support clinical ethical decision-making? A systematic review of reasons. BMC Medical Ethics. 2023;24:48.
109. Meier LJ, Hein A, Diepold K, Buyx A. Algorithms for ethical decision-making in the clinic: A proof of concept. American Journal of Bioethics. 2022;22(7):4-20.
110. Baeroe K, Gundersen T, Henden E, Rommetveit K. Can medical algorithms be fair? Three ethical quandaries and one dilemma. BMJ Health & Care Informatics. 2022;29(1):e100445.
111. Mehrabi N, Morstatter F, Saxena N, Lerman K, Galstyan A. A survey on bias and fairness in machine learning. ACM Computing Surveys (CSUR). 2021;54(6):1-15.
112. Gianfrancesco MA, Tamang S, Yazdany J, Schmajuk G. Potential biases in machine learning algorithms using electronic health record data. JAMA Internal Medicine. 2018;178(11):1544-7.
113. Binkley CE, Kemp DS, Scully BB. Should we rely on AI to help avoid bias in patient selection for major surgery? AMA Journal of Ethics. 2022;24(8):E773-80.
114. Rezk E, Eltorki M, El-Dakhakhni W. Leveraging artificial intelligence to improve the diversity of dermatological skin color pathology: Protocol for an algorithm development and validation study. JMIR Research Protocols. 2022;11(3):e34896.
115. Birhane A. Algorithm injustice: A relational ethics approach. Patterns. 2021;2(2):100205.
116. Char DS, Shah NH, Magnus D. Implementing machine learning in health care – Addressing ethical challenges. New England Journal of Medicine. 2018;378(11):981-3.
117. Yoon CH, Torrance R, Scheinerman N. Machine learning in medicine: Should the pursuit of enhanced interpretability be abandoned? Journal of Medical Ethics. 2022;48(9):581-5.
118. Skeem JL, Louden JE. Assessment of Evidence on the Quality of the Correctional Offender Management Profiling for Alternative Sanctions (COMPAS). Center for Public Policy Research. 26 décembre 2007.
119. Angwin J, Larson J, Mattu S, Kirchner L. Machine Bias. ProPublica. 23 mai 2016.
120. Dressel J, Farid H. The accuracy, fairness, and limits of predicting recidivism. Science Advances. 2018;4(1):eaao5580.
121. Gundersen T, Baeroe K. The future ethics of artificial intelligence in medicine: Making sense of collaborative models. Science and Engineering Ethics. 2022;28:17.
122. FitzGerald C, Hurst S. Implicit bias in healthcare professionals: A systematic review. BMC Medical Ethics. 2017;18:19.
123. Phillips-Beck W, Eni R, Lavoie JG, et al. Confronting racism within the Canadian healthcare system: Systemic exclusion of First Nations from quality and consistent care. International Journal of Environmental Research and Public Health. 2020;17(22):8343.
124. Azria É. Biais implicites et soins différenciés dans l’étude des inégalités sociales de santé entre migrants et non-migrants. Revue française d’éthique appliquée. 2019;2(8):8-11.
125. Moscou K, Bhagaloo A, Onilude Y, Zaman I, Said A. Broken promises: Racism and access to medicines in Canada. Journal of Racial and Ethnic Health Disparities. 2024;11(3):1182-98.
126. Supiot A. La gouvernance par les nombres. Paris: Fayard; 2015.
127. McDougall RJ. Computer knows best? The need for value-flexibility in medical AI. Journal of Medical Ethics. 2019;45(3):156-60.
128. Définitions Digital. Algocratie.
129. Pozzi G. Automated opioid risk scores: A case for machine learning-induced epistemic injustice in healthcare. Ethics and Information Technology. 2023;25:3.
130. Pilkington B, Binkley C. Disproof of concept: Resolving ethical dilemmas using algorithms. American Journal of Bioethics. 2022;22(7):81-3.
131. Albrecht GL, Devlieger PJ. The disability paradox: High quality of life against all odds. Social Sciences in Medicine. 1999;48(8):977-88.
132. Ubel PA, Loewenstein G, Schwarz N, Smith D. Misimagining the unimaginable: The disability paradox and health care decision making. Health Psychology. 2005;24(4 Suppl):S57-62.
133. Ministère de la Santé et des Services sociaux. L’aide médicale à mourir pour les personnes en situation d’inaptitude: le juste équilibre entre le droit à l’autodétermination, la compassion et la prudence. Gouvernement du Québec; 2019.
134. Chan HY. Video advance directives: A turning point for advance decision‑making? A consideration of their roles and implications for law and practice. Liverpool Law Review. 2020;41:1-26.
135. Gloeckler S, Ferrario A, Biller-Andorno N. An ethical framework for incorporating digital technology into advance directives: Promoting informed advance decision making in healthcare. Yale Journal of Biology and Medicine. 2020;95(3):349-53.
136. Cardona-Morrell M, Kim JCH, Turner RM, et al. Non-beneficial treatments in hospital at the end of life: A systematic review on extent of the problem. International Journal for Quality in Health Care. 2016;28(4):456-69.
137. Nicolas LH, Langa KM, Halpern SD, Macis M. How do surrogates make treatment decisions for patients with dementia: An experimental survey study. Health Economics. 2024;33(6):1211-28.
138. Streuli JC, Anderson J, Alef-Defoe S, et al. Combining the best interest standard with shared decision-making in paediatrics–introducing the shared optimum approach based on a qualitative study. European Journal of Pediatrics. 2021;180(3):759-66.
139. Wilkins JM. Narrative interest standard: A novel approach to surrogate decision-making for people with dementia. Gerontologist. 2018;58(6):1016-20.
140. Kerasidou CX, Kerasidou A, Buscher M, Wilkinson S. Before and beyond trust: Reliance in medical AI. Journal of Medical Ethics. 2022;48(11):852-6.
141. Grote T. Randomised controlled trials in medical AI: Ethical considerations. Journal of Medical Ethics. 2022;48(11):899-906.
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