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

Lay Summary

This project aims to find out what would encourage or discourage people living in Wales, or healthcare professionals working in Wales, to have artificial intelligence (AI) technologies used to support healthcare decision-making. It will looking at the opinions of people who are:

• At least 16 years old and live in Wales, or

• Are registered healthcare professionals working in Wales and are making treatment or therapy decisions with patients or for patients

The findings from this study can help us understand how artificial intelligence (AI) technologies should be designed and put into practice in a way that is acceptable to patients receiving care in Wales and healthcare staff working in Wales.

The project will first involve undertaking an online survey. This part of the study aims to collect the opinions of as many eligible participants as possible, and so ensure that people across Wales had the opportunity to express their opinions. The second part of the study will involve focus groups or interviews. This part of the project will allow us to get more detailed answers as to why people might perceive some things as barriers or facilitators to the introduction of AI in healthcare. This part of the project will also allow those who are otherwise digitally excluded to participate in this project and courage those who are between 16 and 18 years old to participate as well. This should ensure that our results represent the opinions of all people who might be taking part in making healthcare decisions.

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.

CEDAR's role

  • Background review of the literature
  • Development of the methodology and study paperwork
  • Submission to HRA/HCRW
  • Submission of amendments
  • Data collection and analysis
  • Dissemination of results

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

Want to take part?

We are running a Wales-wide survey to find out what are peoples preferences and worries relating to the potential use of AI technologies in healthcare decision-making. For more information, or to take part, click here.