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Identifying the barriers and facilitators for implementing Machine Learning to achieve Value-Based Healthcare in Wales

 

Study details

  • Full study title: Identifying the barriers and facilitators for implementing Machine Learning to achieve Value-Based Healthcare in Wales
  • Study design: Mixed-methods
  • Chief Investigator: Dr Michal Pruski
  • Sponsor: Cardiff and Vale University Health Board
  • IRAS: 345131
  • REC ref: 24/HCRW/0021
  • Sponsor ref: 8870
  • Funding: Internal funding from the Welsh Value in Health Centre and Health Education and Improvement Wales

 

Background

Implementing new technologies in the clinical setting is difficult for many reasons, and one of these reasons is that people simply do not want to use them. In this study we are looking at what might encourage or discourage both clinicians and members of the public from having artificial intelligence (AI) technologies used in healthcare. Specifically, we will focus on a type of AI known as machine learning (ML) and its potential to be used as a tool to support treatment/therapy decision-making. We focus on this because Wales is a leader in collecting Patient Reported Outcome Measures (PROMs), and PROMs data has a potential to be used in such technologies. We hope that this research will provide information for those developing and implementing such digital technologies, so that they can make these technologies and put them into practice in a way that will be acceptable by both clinicians and members of the public. This will potentially prevent the health system from spending time and money on technologies which people will not want to use.

Based on some preliminary research (Pruski, M., 2024a, 2024b, 2024c, 2023), as well considering the aims of the project, we have undertaken some systematic searches of the academic literature. We looked at how PROMs data and ML technologies have been used together to make clinical predictions. We also looked barriers and facilitators to the adoption of AI in healthcare, with a special focus on ethical challenges relating to this. Some of this work has now been submitted for peer-review and links will be provided once it becomes published.