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Data Ownership in the AI-Powered Integrative Health Care Landscape

Data Ownership in the AI-Powered Integrative Health Care Landscape

The study sheds light on the significance of patient-centric data governance, providing insights into the legal and ethical implications and considerations for ensuring responsible and transparent AI implementation within integrative health (IH). IHC embraces a holistic approach to wellness and centers on the interconnectedness of the mind, body, and spirit, advocating for comprehensive healing that addresses all facets of an individual’s health [1].

Shuimei Liu, L Raymond Guo

JMIR Med Inform 2024;12:e57754

Ethics and Governance of Neurotechnology in Africa: Lessons From AI

Ethics and Governance of Neurotechnology in Africa: Lessons From AI

Such a governance approach is needed to protect and promote human rights and fundamental freedoms. It is an approach that requires the integration of relevant values and principles that reflects the contexts within which the technology will be applied. So far, the discussion on ethics and governance of neurotechnology has neglected narratives, values, principles, and contexts in Africa.

Damian Eke

JMIR Neurotech 2024;3:e56665

Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review

Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review

Governance was primarily noted as a key facilitating factor, playing the role of enabling the full cycle of AI. It is critical to have a governance structure in place to oversee the development and rollout of AI from conception to implementation, with governance tools providing guidance on various stages of the process. Governance should include diverse professionals with clear articulation of accountability, including nuances in reactions to accountability [35,40,55,58,64].

Masooma Hassan, Andre Kushniruk, Elizabeth Borycki

JMIR Hum Factors 2024;11:e48633

Preferences on Governance Models for Mental Health Data: Qualitative Study With Young People

Preferences on Governance Models for Mental Health Data: Qualitative Study With Young People

Adults’ views on sharing their data and data governance have been quite consistent across the studies, but we lack evidence of what young people think. A global mental health data bank containing information about how various factors affect young people’s mental health would provide valuable resources for mental health researchers. Terms of governance acceptable to young people must be established before such a resource is developed.

Emma Grace Carey, Faith Oluwasemilore Adeyemi, Lakshmi Neelakantan, Blossom Fernandes, Mina Fazel, Tamsin Ford, The MindKind Consortium, Anne-Marie Burn

JMIR Form Res 2024;8:e50368

Building a Sustainable Learning Health Care System for Pregnant and Lactating People: Interview Study Among Data Access Providers

Building a Sustainable Learning Health Care System for Pregnant and Lactating People: Interview Study Among Data Access Providers

By providing insight into the views and interests of people representing DAPs in this particular LHS, this study intends to inform a governance framework for LHSs and, in turn, to help facilitate the development of a sustainable LHS in which public and private organizations collaborate.

Marieke J Hollestelle, Rieke van der Graaf, Miriam C J M Sturkenboom, Marianne Cunnington, Johannes J M van Delden

JMIR Pediatr Parent 2024;7:e47092

Evaluating Staff Attitudes, Intentions, and Behaviors Related to Cyber Security in Large Australian Health Care Environments: Mixed Methods Study

Evaluating Staff Attitudes, Intentions, and Behaviors Related to Cyber Security in Large Australian Health Care Environments: Mixed Methods Study

The most frequently repeated individual codes within perceived usefulness included risk, governance, and proposed solutions, whereas the most common drivers from subjective norms were people and relationships, patient confidentiality, and clinical exceptions (to rules and policies). The top 100 most frequently occurring words mentioned by the interview participants (after excluding common or irrelevant words) are shown in Multimedia Appendix 7.

Martin Dart, Mohiuddin Ahmed

JMIR Hum Factors 2023;10:e48220

Understanding Views Around the Creation of a Consented, Donated Databank of Clinical Free Text to Develop and Train Natural Language Processing Models for Research: Focus Group Interviews With Stakeholders

Understanding Views Around the Creation of a Consented, Donated Databank of Clinical Free Text to Develop and Train Natural Language Processing Models for Research: Focus Group Interviews With Stakeholders

In the United Kingdom, the application of NLP for health care text research is largely limited to within large NHS hospital trusts with academic affiliations and in-house NLP expertise owing to complex governance requirements arising from increased concerns around the potential risk of reidentifying patients.

Natalie K Fitzpatrick, Richard Dobson, Angus Roberts, Kerina Jones, Anoop D Shah, Goran Nenadic, Elizabeth Ford

JMIR Med Inform 2023;11:e45534

Assessment of Stakeholder Perceptions and Attitudes Toward Health Data Governance Principles in Botswana: Web-Based Survey

Assessment of Stakeholder Perceptions and Attitudes Toward Health Data Governance Principles in Botswana: Web-Based Survey

Consequently, the need for strengthening health data governance (HDG) has arisen, as noted in pronouncements such as the Sustainable Development Goals [8] and Universal Health Coverage (UHC) [9]. The Data Governance Institute (DGI) defines data governance as “a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods” [10].

Kagiso Ndlovu, Kabelo Leonard Mauco, Star Chibemba, Steven Wanyee, Tom Oluoch

JMIR Form Res 2023;7:e41408

Patients’ and Publics’ Preferences for Data-Intensive Health Research Governance: Survey Study

Patients’ and Publics’ Preferences for Data-Intensive Health Research Governance: Survey Study

Various proposals exist for an ethical governance framework for data-intensive health research [1,2]. However, lessons learned point out that no fit-for-purpose governance framework currently exists [3,4]. At the same time, oversight in large, big data–driven research projects cannot be achieved by simply collecting and synthesizing existing governance elements of databases that participate in the project [3,5].

Sam H A Muller, Ghislaine J M W van Thiel, Marilena Vrana, Menno Mostert, Johannes J M van Delden

JMIR Hum Factors 2022;9(3):e36797