Project Details
Description
The healthcare sector is facing substantial shortages when recruiting suitable and qualified occupational health (OH) personnel. Suitable candidates may be found and employed, who after some time search for better opportunities and leave unfilled vacancies, increasing recruitment costs and incurring additional training costs.
To overcome this problem, and to increase productivity, Heales Innovation Ltd (holding company) and subsidiaries (including Heales Health Services Ltd) is undertaking significant R&D related to AI and machine learning within its operations. This learning involves one or more generative AI models trained within the organisation to undertake various tasks. Anecdotally Heales staff, (including nurses and doctors) accept this technology, however there is a need to better understand how much the staff understand the technology, its use and potential impacts of use, whether they use it externally themselves, whether they feel the organisation should use it more or whether they are concerned about its use with health care, especially OH for any reason. We need to understand any barriers we may face as we begin to use AI within our industry more and more.
If the solution is realised, then it will result in a system that can provide answers to health queries signficantly reducing clinician time to compile the answers. By expediting this process, patients will be offered a better quality service that could result in fewer telephone calls of concern. Users interacting with this new system will also have upskilling of their digital skills, thus offering Heales medical a well skilled workforce. If this system is well implemented, it would lead to the development of more GAIs in Heales Medical that could result in better services offered to patients. This opportunity will also afford the associate and academic supervisor with knowledge and information about GAI development and implementation, a very niche and unique area of research interest. For Heales it provides an opportunity to have a first mover advantage in the GAI area for occupational health and a better skilled developer team.
To overcome this problem, and to increase productivity, Heales Innovation Ltd (holding company) and subsidiaries (including Heales Health Services Ltd) is undertaking significant R&D related to AI and machine learning within its operations. This learning involves one or more generative AI models trained within the organisation to undertake various tasks. Anecdotally Heales staff, (including nurses and doctors) accept this technology, however there is a need to better understand how much the staff understand the technology, its use and potential impacts of use, whether they use it externally themselves, whether they feel the organisation should use it more or whether they are concerned about its use with health care, especially OH for any reason. We need to understand any barriers we may face as we begin to use AI within our industry more and more.
If the solution is realised, then it will result in a system that can provide answers to health queries signficantly reducing clinician time to compile the answers. By expediting this process, patients will be offered a better quality service that could result in fewer telephone calls of concern. Users interacting with this new system will also have upskilling of their digital skills, thus offering Heales medical a well skilled workforce. If this system is well implemented, it would lead to the development of more GAIs in Heales Medical that could result in better services offered to patients. This opportunity will also afford the associate and academic supervisor with knowledge and information about GAI development and implementation, a very niche and unique area of research interest. For Heales it provides an opportunity to have a first mover advantage in the GAI area for occupational health and a better skilled developer team.
| Short title | ESRC IAA Round III/2024-25 |
|---|---|
| Status | Active |
| Effective start/end date | 2/12/25 → 1/12/26 |
Funding
- UKRI - Economic and Social Research Council (ESRC): £5,000.00
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