Macdonald, TB;
Hogg, HDJ;
Dinnes, J;
Verrinder, L;
Maniatopoulos, G;
Taylor-Phillips, S;
Shinkins, B;
... Denniston, AK; + view all
(2025)
Target product profiles for digital health technologies including those with artificial intelligence: a systematic review.
Frontiers in Health Services
, 5
, Article 1537016. 10.3389/frhs.2025.1537016.
Preview |
Text
TPP AI DHT.pdf - Published Version Download (577kB) | Preview |
Abstract
Digital health technologies (DHTs), including those incorporating artificial intelligence (AI), have the potential to improve healthcare access, efficiency, and quality, reducing gaps between healthcare capacity and demand. Despite prioritisation in health policy, the adoption of DHTs remains limited, especially for AI, in part due to complex system requirements. Target product profiles (TPPs) are documents outlining the characteristics necessary for medical technologies to be utilised in practice and offer a way to align DHTs’ research and development with health systems’ needs. This systematic review examines current DHT TPPs’ methodologies, stakeholders, and contents. A total of 14 TPPs were identified, most targeted at low- and middle-income settings and communicable diseases. Only one TPP outlined the requirements for an AI device specifically. In total, 248 different characteristics were reported across the TPPs identified and were consolidated down to 33 key characteristics. Some considerations for DHTs’ successful adoption, such as regulatory requirements or environmental sustainability, were reported inconsistently or not at all. There was little standardisation in TPP development or contents, and limited transparency in reporting. Our findings emphasise the need for guidelines for TPP development, could help inform these, and could be used as a basis to develop future DHT TPPs. Systematic Review Registration: https://www.researchprotocols.org/2024/1/e50568/authors.
| Type: | Article |
|---|---|
| Title: | Target product profiles for digital health technologies including those with artificial intelligence: a systematic review |
| Location: | Switzerland |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/frhs.2025.1537016 |
| Publisher version: | https://doi.org/10.3389/frhs.2025.1537016 |
| Language: | English |
| Additional information: | © 2025 Macdonald, Hogg, Dinnes, Verrinder, Maniatopoulos, Taylor-Phillips, Shinkins, Dunbar, Solebo, Sutton, Attwood, Pogose, Given-Wilson, Greaves, Macrae, Pearson, Tufail, Liu and Denniston. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | AI, TPP, digital health technology, quality by design, target product profile |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10210170 |
Archive Staff Only
 |
View Item |
