Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of Complexity

Abstract

<jats:p>Artificial intelligence (AI) is seen as a strategic lever to improve access, quality, and efficiency of care and services and to build learning and value-based health systems. Many studies have examined the technical performance of AI within an experimental context. These studies provide limited insights into the issues that its use in a real-world context of care and services raises. To help decision makers address these issues in a systemic and holistic manner, this viewpoint paper relies on the health technology assessment core model to contrast the expectations of the health sector toward the use of AI with the risks that should be mitigated for its responsible deployment. The analysis adopts the perspective of payers (ie, health system organizations and agencies) because of their central role in regulating, financing, and reimbursing novel technologies. This paper suggests that AI-based systems should be seen as a health system transformation lever, rather than a discrete set of technological devices. Their use could bring significant changes and impacts at several levels: technological, clinical, human and cognitive (patient and clinician), professional and organizational, economic, legal, and ethical. The assessment of AI’s value proposition should thus go beyond technical performance and cost logic by performing a holistic analysis of its value in a real-world context of care and services. To guide AI development, generate knowledge, and draw lessons that can be translated into action, the right political, regulatory, organizational, clinical, and technological conditions for innovation should be created as a first step.</jats:p>

Artificial intelligence in hospitals: providing a status quo of ethical considerations in academia to guide future research

“…Research on ethical considerations of AI in hospitals is no longer a mere part of science fiction but a real-world concern (Luxton 2014a , b ). Despite existing studies on ethics of AI in healthcare (e.g., Alami et al 2020 ; Arnold and Scheutz 2018 ; Ploug and Holm 2020 ), we argue that current research does not consider the growing significance of the topic in a diversified enough manner, but is rather narrowly focused on traditional explorations.…”

“…Recent AI implementations in hospitals and in healthcare in general come with a variety of ethical considerations. For example, AI is associated with bias, discrimination, opacity, and rational concerns and intentions (e.g., Arnold and Scheutz 2018 ; Gruson et al 2019 ; Ploug and Holm 2020 ) as much as it is associated with transparency, trust, responsibility, liability, and explainability (e.g., Alami et al 2020 ; Wang 2020 ). A recent study by Ploug and Holm ( 2020 ) investigated the ethical concerns of AI for medical diagnostics and treatment planning.…”

“…Furthermore, Ploug and Holm ( 2020 ) explain that there are problems regarding bias and opacity for the patient, related implications for the entire healthcare sector, and rational concerns about impacts on society. Another study by Alami et al ( 2020 ) provides a synthesis of key challenges posed by AI. Besides technological, organizational, and economic issues, the authors also raise several ethical obstacles.…”

“…However, it is yet to be defined who is held responsible for AI-based decisions leading to errors in the treatment process. Another issue illustrated by Alami et al ( 2020 ) is the potential unexplainability of algorithmic outcomes, i.e. black box, posing a high risk to patients’ well-being (Knight 2017 ; Rudin 2019 ).…”

“…Scholars and practitioners are also concerned with preventing inequitable usage and unfair information practices (Salerno et al 2017 ; Sonja et al 2018 ; Libaque-Sáenz et al 2020 ). Furthermore, AI still learns from medical data that is preprocessed by humans and thus might contain bias or prejudices (Kara et al 2006 ; Hirschauer et al 2015 ; Ploug and Holm 2020 ; Alami et al 2020 ).…”