Towards an AI-enabled Learning Healthcare System

Learning healthcare systems are health systems where the activities associated with data analytics and clinical practice are fully integrated to reduce the delay in applying insights from data analysis to patient care. While these systems have great potential to enhance patient health and clinical efficiency, they have thus far proven challenging to implement due to a variety of ethical, technical and practical obstacles. Recent advances in AI are now widely recognized for their potential to improve patient outcomes, healthcare equity, and efficiency, but also for the practical challenges they pose. However, AI's ability to process large datasets and continuously learn also presents a key opportunity to realize a learning healthcare system, though this benefit, and the obstacles relating to its realisation, has received less attention in the literature.

The goal of this Research Topic is to bring together a collection of papers discussing the ethical, regulatory and legal issues associated with achieving a learning healthcare system through AI implementation. While AI systems hold potential to assist in realising learning healthcare systems in practice, doing so faces a variety of obstacles. For example, ensuring data quality and standardization across diverse healthcare settings is crucial, as inconsistent data can lead to inaccurate insights and hinder effective decision-making. Additionally, concerns about patient privacy and the security of sensitive health information, algorithmic bias and health inequalities, healthcare systems being optimised for efficiency rather than focusing on their duty of care, as well as that systems will become more mechanistic pose significant challenges that must be addressed to build trust among both patients and providers. Regulatory strategies for addressing continual learning in medical AI systems are also heavily debated. This Research Topic aims to identify, evaluate, and address these current legal, ethical, and regulatory obstacles for using AI to contribute to realising a learning healthcare system in practice. More specifically, it aims to address questions associated with ensuring robust and reliable performance in continual learning AI systems, combining medical AI for clinical research and medical AI for clinical practice, and improving the performance of medical AI systems on an ongoing basis.

We welcome contributions that focus on AI and learning healthcare systems. More specifically, we are seeking articles that investigate and address challenges associated with realising a learning healthcare system using AI and machine learning technologies. These may include discussions of questions including (but not limited to):

• What are the ethical challenges associated with using AI systems to enable a continual learning healthcare system in practice, and how might they be addressed?
• How should ongoing learning in medical AI systems be regulated?
• What legal challenges are generated using AI systems to enable a continual learning healthcare system, and how might they be addressed?

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Classification
• Clinical Trial
• Community Case Study
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Classification
• Clinical Trial
• Community Case Study
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: Artificial Intelligence, learning healthcare system, continual learning, ethics, regulation, implementation

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.