Towards successful implementation of artificial intelligence in healthcare practice: A research program (Preprint)

Abstract

The uptake of artificial intelligence (AI) in healthcare is at an early stage. Recent studies have shown the lack of AI-specific implementation theories, models or frameworks that could provide guidance for how to translate the potential of AI into daily healthcare practices. This protocol provides an outline for the first five years of a research program seeking to address this knowledge-practice gap through collaboration and co-design between researchers, healthcare professionals, patients and industry stakeholders.

The first part of the program focuses on two specific objectives. First, to develop a theoretically informed framework for AI implementation in healthcare that can be applied to facilitate such implementation in routine healthcare practice. Second, to carry out empirical AI implementation studies guided by the framework for AI implementation, and generating learning for enhanced knowledge and operational insights to guide further refinement of the framework. The second part of the program addresses a third objective, to apply the developed framework in clinical practice to develop regional capacity to provide the practical resources, competencies and organizational structure required for AI implementation although this is beyond the scope of this protocol.

This research program uses a logic model to structure the development of a methodological framework for planning and evaluating implementation of AI systems in healthcare and to support capacity building for its use in practice. The logic model is divided into time-separated stages, with a focus on theory driven and co-produced framework development. The activities are based on both knowledge development, utilizing existing theory and literature reviews, and method development by means of co-design and empirical investigations. The activities involve researchers, healthcare professionals and other stakeholders, thus creating a multi-perspective understanding of how the implementation of AI systems should be approached to increase likelihood of successful implementation and application in clinical practice.

The project started 1 July 2021 and will continue until 31 June 2026.

There is a need to advance theory and empirical evidence on implementation requirements of AI systems in healthcare, and an opportunity to bring together insights from research on the development, introduction and evaluation of AI systems and existing knowledge about implementation research literature. Therefore, we intend in this research program to build an understanding, using both theoretical and empirical approaches, of how implementation of AI systems should be approached to increase the likelihood of successful and widespread application in clinical practice.