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Accepted for/Published in: JMIR Formative Research

Date Submitted: Jun 28, 2021
Open Peer Review Period: Jun 28, 2021 - Jul 1, 2021
Date Accepted: Oct 13, 2021
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Governing Data and Artificial Intelligence for Health Care: Developing an International Understanding

Morley J, Murphy L, Mishra A, Joshi I, Karpathakis K

Governing Data and Artificial Intelligence for Health Care: Developing an International Understanding

JMIR Form Res 2022;6(1):e31623

DOI: 10.2196/31623

PMID: 35099403

PMCID: 8844981

Governing Data and AI for Healthcare: Developing an International Understanding

  • Jessica Morley; 
  • Lisa Murphy; 
  • Abhishek Mishra; 
  • Indra Joshi; 
  • Kassandra Karpathakis

ABSTRACT

Background:

While advanced analytical techniques falling under the umbrella heading of Artificial Intelligence (AI) may improve healthcare, the use of AI in health raises safety and ethical concerns. There are currently no internationally recognized Governance mechanisms (policies, ethical standards, evaluation, regulation) for developing and using AI technologies in healthcare. A lack of international consensus creates technical and social barriers for using health AI, while hampering market competition.

Objective:

To review current health AI Governance mechanisms being developed or used by Global Digital Health Partnership (GDHP) member countries: identify commonalities and gaps in approaches, identify examples of best practice and understand the rationale for policies. Changes in the use of AI-driven technologies during the COVID-19 pandemic were sought.

Methods:

Data were collected by: (1) a rapid review of academic literature, (2) a desktop analysis of policy documents published by selected GDHP member countries, (3) semi-structured interviews exploring 10 countries' experience of AI-driven technologies in healthcare and associated governance, and (4) a focus group with professionals working in international health and technology to discuss the themes and proposed policy recommendations. Policy recommendations were developed based on the aggregated research findings.

Results:

Semi-structured interviews (N=10) and focus group (N=10) revealed four core areas for international collaborations: (1) leadership and oversight, (2) an ecosystem approach, (3) standards and regulatory processes, and (4) engagement with stakeholders and the public. There was a broad range of maturity in health AI activity amongst participants, with varying data infrastructure, application of standards across the AI lifecycle and strategic approaches to both development and deployment. A demand for further consistency through international level and policies was identified, to support a robust innovation pipeline. Thirteen policy recommendations were developed to support GDHP member countries overcome core AI Governance barriers, and establish common ground for international collaboration.

Conclusions:

Internationally, AI-driven technology research and development for healthcare outpaces the creation of supporting AI Governance. International collaboration and coordination on AI Governance for healthcare is needed to ensure coherent solutions and allow countries to support and benefit from each others' work. International bodies and initiatives have a leading role to play in the international conversation, including the production of tools and sharing of practical approaches to the utilization of AI-driven technologies for healthcare. Clinical Trial: N/A


 Citation

Please cite as:

Morley J, Murphy L, Mishra A, Joshi I, Karpathakis K

Governing Data and Artificial Intelligence for Health Care: Developing an International Understanding

JMIR Form Res 2022;6(1):e31623

DOI: 10.2196/31623

PMID: 35099403

PMCID: 8844981

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