Empathy, compassion and trust balancing artificial intelligence in health care
Introduction:
Empathy, compassion, and trust are fundamental values of a patient-centred health care. In recent years, the pursuit of greater efficiency in health care, including economic efficiency, has often resulted in these values being side-lined, making it difficult for health-care professionals to incorporate them in practice.
Artificial intelligence is increasingly being used in health care and promises greater efficiency and effectiveness and a level of personalization not possible before. Artificial intelligence could help improve diagnosis and treatment accuracy, streamline workflow processes, and speed up the operation of clinics and hospital departments. The hope is that by improving efficiency, time will be freed for health-care professionals to focus more fully on the human side of care, which involves fostering trust relationships and engaging with patients with empathy and compassion.
Empathy, compassion and trust:
Empathy, compassion, and trust are broadly recognized as fundamental values of good health-care practice. Empathy allows health-care professionals to understand and share the patient’s feelings and perspective. Compassion is the desire to help that is instigated by the empathetic engagement with the patient. Research has shown the benefits of trust and empathetic care, including improved patient satisfaction, increased treatment adherence and improved health outcomes. Despite their importance, empathy and compassion in health care are often side-lined. In recent years, for example, socioeconomic factors, including an ageing population and austerity policies in Europe that followed the 2008 economic collapse, have led to the marginalization of these values. Against this backdrop, artificial intelligence has been heralded to save struggling national health-care systems and transform the future of health care by providing greater efficiency, effectiveness, and high levels of personalized care.
Artificial intelligence in health care:
Artificial intelligence could help health-care systems achieve greater efficiency, including economic efficiency, in two ways: First, by improving time to and accuracy of diagnosis and treatment for patients, and where possible assisting with early prevention; and second, by using health-care staff more efficiently. Research conducted so far has shown that machines can perform as well as, or even better than, humans in detecting skin cancer, heart arrhythmia and Alzheimer disease. Furthermore, human–machine partnerships can provide far better results than either humans or machines alone. Proponents of artificial intelligence technology in health care maintain that outsourcing tasks and decisions to rational machines will free up time for health-care professionals to engage in empathetic care and foster trust relationships with patients.
In which direction health-care delivery will evolve is an important theoretical and practical question that requires examination. Currently, it is still unclear whether and how health-care practice will be transformed by artificial intelligence, and what effect it may have, particularly on the role of health-care professionals and on the therapeutic relationship.
Potential implication of artificial intelligence:
The use of artificial intelligence to optimize accuracy of diagnosis and treatment could raise issues of accountability when things go wrong, not only in cases where doctors follow the recommendations of artificial intelligence, but also when they decide to override these recommendations. In such
situations, it is unclear who should be held accountable, whether responsibility should lie with the algorithm developer, the data provider, the health system that adopted the artificial intelligence tool, or the health-care professional who used it.
Furthermore, as mentioned earlier in patient-centred care, empathy allows health-care professionals to understand the patients’ perspective, and thus helps health professionals tailor care to promote the patients’ values and address their individual needs. Empathy and compassion therefore play a very important role in an interpersonal model of care that rejects medical paternalism and brings the doctor and the patient together to discuss options and find appropriate solutions. To preserve this ideal of patient-centred care, artificial intelligence systems should be built in a way that allows for value-plurality, meaning the possibility that different patients might hold different values and have different priorities related to for their care. In this way, the ethical ideal of shared decision-making can be maintained and not be replaced by another form of paternalism, one practised not by doctors, but by artificial intelligence algorithms.
Conclusion:
The potential impact of artificial intelligence on health care, in general, and on the therapeutic relationship between health-care providers and patients is widely acknowledged, as is the fact that society needs to learn how to deal “with new forms of agents, patients and environments.” Artificial intelligence has great potential to improve efficiency and effectiveness in health care. However, whether artificial intelligence can support other values central to the delivery of a patient-centred care, such as empathy, compassion, and trust, requires careful examination.
