An Evaluation Framework for Healthcare Professionals’ Digital Health and AI Technologies: Evidence-Based Policy Recommendations
Author(s)
Afua van Haasteren, PhD1, Paola Botrugno, MSc2, George A Wharton, MSc3, Robin van Kessel, PhD3, Stephanie Winitsky, MSc3, Jelena Schmidt, MSc3.
1Rotkreuz, Switzerland, 2Roche Diagnostics Belgium, Brussels, Belgium, 3London School of Economics, London, United Kingdom.
1Rotkreuz, Switzerland, 2Roche Diagnostics Belgium, Brussels, Belgium, 3London School of Economics, London, United Kingdom.
OBJECTIVES: Health systems continue to face mounting challenges for which digital health and AI technologies (DHAITs) can lend a helping hand. However, the lack of consensus on a taxonomy for digital health technologies along with the absence of appropriate value assessment frameworks, particularly for professional-facing solutions, inhibit their value to tackling health system challenges. In this study, we propose a comprehensive evidence-based taxonomy for professional-facing DHAITs, review existing evidence frameworks, highlight their shortcomings and present robust recommendations to evaluate these technologies.
METHODS: The study draws on scoping reviews and thematic analyses to develop a structured taxonomy that reflects the key characteristics of professional-facing DHAITs. It also examines evaluation frameworks put forward by six countries—UK, France, Germany, USA, South Korea, and Canada—to assess their current classification and evaluation proposals. A group of 9 experts were consulted to fine-tune the overall results of the study.
RESULTS: The proposed taxonomy includes seven core dimensions: interoperability, access platform, driving technology, data inputs, intended impact, intended use case, and intended beneficiary. The consolidated review results in eight policy recommendations stressing the need to align classification with evidence standards, expand HTA frameworks to include system-level impacts, and foster international regulatory cooperation. These recommendations target HTA agencies, notified bodies, international regulatory networks, payers, health ministries and developers, to facilitate remedies required to effectively evaluate these technologies and improve their impact in health systems.
CONCLUSIONS: The proposed taxonomy and review of existing evaluation frameworks contribute to the existing evidence gaps and ongoing work to define the best approach to evaluating DHAITs. Ultimately, properly evaluating DHAITs would ensure that they deliver on their promise to help tackle health system challenges.
METHODS: The study draws on scoping reviews and thematic analyses to develop a structured taxonomy that reflects the key characteristics of professional-facing DHAITs. It also examines evaluation frameworks put forward by six countries—UK, France, Germany, USA, South Korea, and Canada—to assess their current classification and evaluation proposals. A group of 9 experts were consulted to fine-tune the overall results of the study.
RESULTS: The proposed taxonomy includes seven core dimensions: interoperability, access platform, driving technology, data inputs, intended impact, intended use case, and intended beneficiary. The consolidated review results in eight policy recommendations stressing the need to align classification with evidence standards, expand HTA frameworks to include system-level impacts, and foster international regulatory cooperation. These recommendations target HTA agencies, notified bodies, international regulatory networks, payers, health ministries and developers, to facilitate remedies required to effectively evaluate these technologies and improve their impact in health systems.
CONCLUSIONS: The proposed taxonomy and review of existing evaluation frameworks contribute to the existing evidence gaps and ongoing work to define the best approach to evaluating DHAITs. Ultimately, properly evaluating DHAITs would ensure that they deliver on their promise to help tackle health system challenges.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
P58
Topic
Health Policy & Regulatory, Health Technology Assessment, Medical Technologies
Topic Subcategory
Value Frameworks & Dossier Format
Disease
No Additional Disease & Conditions/Specialized Treatment Areas