TY - JOUR T1 - AI-based clinical decision-making systems in palliative medicine: ethical challenges JF - BMJ Supportive & Palliative Care JO - BMJ Support Palliat Care SP - 183 LP - 189 DO - 10.1136/bmjspcare-2021-002948 VL - 13 IS - 2 AU - Ludovica De Panfilis AU - Carlo Peruselli AU - Silvia Tanzi AU - Carlo Botrugno Y1 - 2023/06/01 UR - http://spcare.bmj.com/content/13/2/183.abstract N2 - 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 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 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 discussionsConclusions 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. ER -