Tachkov, K., Zemplenyi, A., Kamusheva, M., Dimitrova, M., Siirtola, P., Pontén, J., Nemeth, B., Kalo, Z., & Petrova, G. (2022). Barriers to use artificial intelligence methodologies in health technology assessment in central and east european countries. Frontiers in Public Health, 10, 921226. https://doi.org/10.3389/fpubh.2022.921226
Barriers to use artificial intelligence methodologies in health technology assessment in central and East European countries
|Author:||Tachkov, Konstantin1; Zemplenyi, Antal2,3; Kamusheva, Maria1;|
1Faculty of Pharmacy, Medical University of Sofia, Sofia, Bulgaria
2Syreon Research Institute, Budapest, Hungary
3Center for Health Technology Assessment and Pharmacoeconomic Research, University of Pecs, Pecs, Hungary
4Biomimetics and Intelligent Systems Group, University of Oulu, Oulu, Finland
5Dental and Pharmaceutical Benefits Agency, Stockholm, Sweden
6Centre for Health Technology Assessment, Semmelweis University, Budapest, Hungary
|Online Access:||PDF Full Text (PDF, 0.4 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2023030830667
|Publish Date:|| 2023-03-08
The aim of this paper is to identify the barriers that are specifically relevant to the use of Artificial Intelligence (AI)-based evidence in Central and Eastern European (CEE) Health Technology Assessment (HTA) systems. The study relied on two main parallel sources to identify barriers to use AI methodologies in HTA in CEE, including a scoping literature review and iterative focus group meetings with HTx team members. Most of the other selected articles discussed AI from a clinical perspective (n = 25), and the rest are from regulatory perspective (n = 13), and transfer of knowledge point of view (n = 3). Clinical areas studied are quite diverse—from pediatric, diabetes, diagnostic radiology, gynecology, oncology, surgery, psychiatry, cardiology, infection diseases, and oncology. Out of all 38 articles, 25 (66%) describe the AI method and the rest are more focused on the utilization barriers of different health care services and programs. The potential barriers could be classified as data related, methodological, technological, regulatory and policy related, and human factor related. Some of the barriers are quite similar, especially concerning the technologies. Studies focusing on the AI usage for HTA decision making are scarce. AI and augmented decision making tools are a novel science, and we are in the process of adapting it to existing needs. HTA as a process requires multiple steps, multiple evaluations which rely on heterogenous data. Therefore, the observed range of barriers come as a no surprise, and experts in the field need to give their opinion on the most important barriers in order to develop recommendations to overcome them and to disseminate the practical application of these tools.
Frontiers in public health
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
113 Computer and information sciences
The HTx project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 825162. This dissemination reflects only the author's view and the Commission is not responsible for any use that may be made of the information it contains.
|EU Grant Number:||
(825162) HTx - Next Generation Health Technology Assessment to support patient-centred, societally oriented, real-time decision-making on access and reimbursement for health technologies throughout Europe
© 2022 Tachkov, Zemplenyi, Kamusheva, Dimitrova, Siirtola, Pontén, Nemeth, Kalo and Petrova. 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.