AI-based clinical decision-making systems in palliative medicine: ethical challenges.
end of life care
ethics
Journal
BMJ supportive & palliative care
ISSN: 2045-4368
Titre abrégé: BMJ Support Palliat Care
Pays: England
ID NLM: 101565123
Informations de publication
Date de publication:
Jun 2023
Jun 2023
Historique:
received:
29
01
2021
accepted:
28
06
2021
medline:
22
5
2023
pubmed:
15
7
2021
entrez:
14
7
2021
Statut:
ppublish
Résumé
Improving palliative care (PC) is demanding due to the increase in people with PC needs over the next few years. An early identification of PC needs is fundamental in the care approach: it provides effective patient-centred care and could improve outcomes such as patient quality of life, reduction of the overall length of hospitalisation, survival rate prolongation, the satisfaction of both the patients and caregivers and cost-effectiveness. We reviewed literature with the objective of identifying and discussing the most important ethical challenges related to the implementation of AI-based data processing services in PC and advance care planning. AI-based mortality predictions can signal the need for patients to obtain access to personalised communication or palliative care consultation, but they should not be used as a unique parameter to activate early PC and initiate an ACP. A number of factors must be included in the ethical decision-making process related to initiation of ACP conversations, among which are autonomy and quality of life, the risk of worsening healthcare status, the commitment by caregivers, the patients' psychosocial and spiritual distress and their wishes to initiate EOL discussions CONCLUSIONS: Despite the integration of artificial intelligence (AI)-based services into routine healthcare practice could have a positive effect of promoting early activation of ACP by means of a timely identification of PC needs, from an ethical point of view, the provision of these automated techniques raises a number of critical issues that deserve further exploration.
Sections du résumé
BACKGROUND
BACKGROUND
Improving palliative care (PC) is demanding due to the increase in people with PC needs over the next few years. An early identification of PC needs is fundamental in the care approach: it provides effective patient-centred care and could improve outcomes such as patient quality of life, reduction of the overall length of hospitalisation, survival rate prolongation, the satisfaction of both the patients and caregivers and cost-effectiveness.
METHODS
METHODS
We reviewed literature with the objective of identifying and discussing the most important ethical challenges related to the implementation of AI-based data processing services in PC and advance care planning.
RESULTS
RESULTS
AI-based mortality predictions can signal the need for patients to obtain access to personalised communication or palliative care consultation, but they should not be used as a unique parameter to activate early PC and initiate an ACP. A number of factors must be included in the ethical decision-making process related to initiation of ACP conversations, among which are autonomy and quality of life, the risk of worsening healthcare status, the commitment by caregivers, the patients' psychosocial and spiritual distress and their wishes to initiate EOL discussions CONCLUSIONS: Despite the integration of artificial intelligence (AI)-based services into routine healthcare practice could have a positive effect of promoting early activation of ACP by means of a timely identification of PC needs, from an ethical point of view, the provision of these automated techniques raises a number of critical issues that deserve further exploration.
Identifiants
pubmed: 34257065
pii: bmjspcare-2021-002948
doi: 10.1136/bmjspcare-2021-002948
doi:
Types de publication
Review
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
183-189Informations de copyright
© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.
Déclaration de conflit d'intérêts
Competing interests: None declared.