The ethics of machine learning-based clinical decision support: an analysis through the lens of professionalisation theory.

BACKGROUND: Machine learning-based clinical decision support systems (ML_CDSS) are increasingly employed in various sectors of health care aiming at supporting clinicians' practice by matching the characteristics of individual patients with a computerised clinical knowledge base. Some studies even indicate that ML_CDSS may surpass physicians' competencies regarding specific isolated tasks. From an ethical perspective, however, the usage of ML_CDSS in medical practice touches on a range of fundamental normative issues. This article aims to add to the ethical discussion by using professionalisation theory as an analytical lens for investigating how medical action at the micro level and the physician-patient relationship might be affected by the employment of ML_CDSS. MAIN TEXT: Professionalisation theory, as a distinct sociological framework, provides an elaborated account of what constitutes client-related professional action, such as medical action, at its core and why it is more than pure expertise-based action. Professionalisation theory is introduced by presenting five general structural features of professionalised medical practice: (i) the patient has a concern; (ii) the physician deals with the patient's concern; (iii) s/he gives assistance without patronising; (iv) s/he regards the patient in a holistic manner without building up a private relationship; and (v) s/he applies her/his general expertise to the particularities of the individual case. Each of these five key aspects are then analysed regarding the usage of ML_CDSS, thereby integrating the perspectives of professionalisation theory and medical ethics. CONCLUSIONS: Using ML_CDSS in medical practice requires the physician to pay special attention to those facts of the individual case that cannot be comprehensively considered by ML_CDSS, for example, the patient's personality, life situation or cultural background. Moreover, the more routinized the use of ML_CDSS becomes in clinical practice, the more that physicians need to focus on the patient's concern and strengthen patient autonomy, for instance, by adequately integrating digital decision support in shared decision-making.

Morality and moral conflicts in hospice care: results of a qualitative interview study.

Hospices consider themselves places that practise a holistic form of terminal care, encompassing physical and psychological symptoms, and also the social and spiritual support for a dying patient. So far, the underlying ethical principles have been treated predominantly in terms of a normative theoretical discussion. The interview study discussed in this paper is a qualitative investigation into general and hospice-related conceptions of morality among full-time and voluntary workers in German inpatient hospices. It examines moral conflicts and efforts leading to their solution. The main ideas identified include moral neutrality towards the patients and their requests, the capability of acceptance, the idea of self-restraint with respect to the dying patient and the principle of respect for the natural course of dying. Essential triggers for moral conflicts were the inadequate education of patients, problems of acceptance in view of incurable disease, and disagreements between members of patients' families. The interviewees expressed their scepticism towards formal institutions of ethical counselling. The study has shown a type of virtue ethics that forms an integral part of the overall concept of hospice care, which cannot be treated separately from a holistic idea of care at the end of life.