Organizational Governance of Emerging Technologies: AI Adoption in Healthcare

Development and preliminary testing of Health Equity Across the AI Lifecycle (HEAAL): A framework for healthcare delivery organizations to mitigate the risk of AI solutions worsening health inequities

“…The data scientists reported that the analysis of some procedures was conducted too late or too early. To address this issue, they recommended listing the procedures of all assessment domains in a sequential order based on the previously developed HAIP 8 key decision points of the AI product life cycle [34].…”

“…Feedback from the data scientists was incorporated into revising the first prototype and generating the second prototype of the framework. The second prototype mapped procedures from the 6 domains of assessment to the HAIP 8 key decision points of the AI product life cycle [34]. At this stage, tags were added to each procedure for relevant stakeholders to be involved, relevant dataset(s) required for analyses, and equity assessment domains.…”

“…Our prior work revealed that healthcare delivery leaders find it challenging to identify and objectively measure the potential impact of an AI product on health inequities. We interviewed 89 individuals from 10 US healthcare delivery organizations and ecosystem partners [34]. Even though we interviewed 13 AI ethics and bias experts, we were not able to reach a consensus on the best approaches to assess AI products for potential impacts on health inequities.…”

Editorial: Governance of emerging health-related technologies

“…(3) Health AI Partnership (HAIP) (Duke University School of Medicine, USA) aims to better define the requirements for adequate organizational governance of AI systems in healthcare settings and support health system leaders to make more informed decisions around AI adoption (Kim et al, 2023);…”

“…Specifically, The National Academy of Medicine Leadership Consortium Project to Develop Health Care AI Code of Conduct (2023/2025) (USA) is aimed at providing a guiding framework to ensure that AI algorithms and their application in health, health care and biomedical science perform accurately, safely, reliably and ethically in the service of better health for all (NAM, 2023b). The planned outputs are: (1) a harmonized and broadly supported Code of Conduct; (2) a comprehensive landscape assessment that includes a systematic review of the literature; a review of the guidelines/frameworks/blueprints from federal agencies; and the guidelines issued by medical specialty societies; (3) a description of the roles and responsibilities of each stakeholder at each stage of the AI lifecycle; (4) a description of the national architecture needed to support responsible health care AI and (5) identification of priority actions going forward;The National Academies of Sciences, Engineering and Medicine, in collaboration with the National Academy of Medicine (NAM), established the Committee on Creating a Framework for Emerging Science, Technology and Innovation in Health and Medicine (CESTI) to provide leadership and engage broad communities in developing a framework for aligning the development and use of transformative technologies with ethical and equitable principles (Mathews et al ., 2022a, b); Health AI Partnership (HAIP) (Duke University School of Medicine, USA) aims to better define the requirements for adequate organizational governance of AI systems in healthcare settings and support health system leaders to make more informed decisions around AI adoption (Kim et al ., 2023); The Governance of Emerging Technologies (GET) research program at the Oxford Internet Institute (2019–2024) (UK) investigates legal, ethical and social aspects of AI, machine learning and other emerging information technologies; research projects include issues such as data protection and inferential analytics, algorithmic bias, fairness, diversity and nondiscrimination as well as explainable and accountable AI. The NHS Artificial Intelligence Laboratory (NHS AI Lab) (UK) was established in 2019 to address that challenge by bringing together government, health and care providers, academics and technology companies, identifying gaps and opportunities for international governance and coherence towards ensuring AI-driven technologies are properly governed, regulated and used for maximal benefit in health systems. The Center for Advanced Studies in Bioscience Innovation Law (Denmark) explores the legal challenges and the rapid developments in the biotechnological area. The center brings together scholars from the world's leading research institutions in interdisciplinary collaboration while also engaging stakeholders from industry, government and civil society.…”