prikaz prve stranice dokumenta Transferability of new methods for health technology assessment in the field of diabetes between early and late adopters’ countries
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Scientific paper - Original scientific paper
Transferability of new methods for health technology assessment in the field of diabetes between early and late adopters’ countries
Biotechnology & Biotechnological Equipment, 38 (2024), 1; 2371354. https://doi.org/10.1080/13102818.2024.2371354
Tachkov, Konstantin; Somolinos-Simón, Francisco; Tapia-Galisteo, Jose; Hernando, Maria Elena; García-Sáez, Gema; Dimitrova, Maria; Kamusheva, Maria; Mitkova, Zornitsa; Petyko, Zsuzsanna; Nemeth, Bertalan; Kalo, Zoltan; Tesar, Tomas; Paveliu, Marian-Sorin; Piniazhko, Oresta; Lipska, Iga; Turcu-Stiolica, Adina; Savova, Alexandra; Manova, Manoela; Hren, Rok; Došenović Bonča, Petra; Knies, Saskia; Stanak, Michal; Doležal, Tomáš; Vitezić, Dinko; Petrova, Guenka More authors...

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Tachkov, K., Somolinos Simón, F., Tapia Galisteo, J., Hernando, M. E., García Sáez, G., Dimitrova, M. ... Petrova, G. (2024). Transferability of new methods for health technology assessment in the field of diabetes between early and late adopters’ countries. Biotechnology & Biotechnological Equipment, 38. (1). doi: 10.1080/13102818.2024.2371354

Tachkov, Konstantin, et al. "Transferability of new methods for health technology assessment in the field of diabetes between early and late adopters’ countries." Biotechnology & Biotechnological Equipment, vol. 38, no. 1, 2024. https://doi.org/10.1080/13102818.2024.2371354

Tachkov, Konstantin, Francisco Somolinos Simón, Jose Tapia Galisteo, Maria Elena Hernando, Gema García Sáez, Maria Dimitrova, Maria Kamusheva, et al. "Transferability of new methods for health technology assessment in the field of diabetes between early and late adopters’ countries." Biotechnology & Biotechnological Equipment 38, no. 1 (2024). https://doi.org/10.1080/13102818.2024.2371354

Tachkov, K., et al. (2024) 'Transferability of new methods for health technology assessment in the field of diabetes between early and late adopters’ countries', Biotechnology & Biotechnological Equipment, 38(1). doi: 10.1080/13102818.2024.2371354

Tachkov K, Somolinos Simón F, Tapia Galisteo J, Hernando ME, García Sáez G, Dimitrova M, and sur.. Transferability of new methods for health technology assessment in the field of diabetes between early and late adopters’ countries. Biotechnology & Biotechnological Equipment [Internet]. 2024 June 25 [cited 2025 January 15];38(1). doi: 10.1080/13102818.2024.2371354

K. Tachkov, et al., "Transferability of new methods for health technology assessment in the field of diabetes between early and late adopters’ countries", Biotechnology & Biotechnological Equipment, vol. 38, no. 1, June 2024. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:184:749876. [Accessed: 15 January 2025]

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Metadata
Title (english)Transferability of new methods for health technology assessment in the field of diabetes between early and late adopters’ countries
AuthorKonstantin Tachkov
AuthorFrancisco Somolinos-Simón
AuthorJose Tapia-Galisteo
AuthorMaria Elena Hernando
AuthorGema García-Sáez
AuthorMaria Dimitrova
AuthorMaria Kamusheva
AuthorZornitsa Mitkova
AuthorZsuzsanna Petyko
AuthorBertalan Nemeth
AuthorZoltan Kalo
AuthorTomas Tesar
AuthorMarian-Sorin Paveliu
AuthorOresta Piniazhko
AuthorIga Lipska
AuthorAdina Turcu-Stiolica
AuthorAlexandra Savova
AuthorManoela Manova
AuthorRok Hren
AuthorPetra Došenović Bonča
AuthorSaskia Knies
AuthorMichal Stanak
AuthorTomáš Doležal
AuthorDinko Vitezić
AuthorGuenka Petrova
Author's institutionUniversity of Rijeka
Faculty of Medicine
Scientific / art field,
discipline and subdiscipline		BIOMEDICINE AND HEALTHCARE
Clinical Medical Sciences
Clinical Pharmacology and Toxicology
Abstract (english)
This study aimed to investigate the transferability of novel artificial intelligence (AI) methods for prediction modelling of diabetes based on real-world data (RWD) between early and late adopters of emerging health technologies from the perspective of developers and health technology assessment (HTA) experts. A two-step approach was used. Developers of the new AI methods within HTx consortium completed a survey about the benefits, usability, barriers associated with implementing the new prediction models in routine HTA practices. Then, HTA experts from Central and Eastern European (CEE) countries participated in a focus group discussion. Developers generally expressed optimism regarding the transferability of the methods, while acknowledging potential disparities across CEE countries. Key benefits that were identified included enhanced understanding of diabetes, improved cost-effectiveness modelling, and refined patient stratification, all of which could contribute to clinical and reimbursement decisions across various jurisdictions. The focus group underscored the value of real-world data for diabetes prediction modelling, serving as a beneficial resource for both clinicians and HTA agencies. However, there was a recognized need to clarify the processes of integrating randomized clinical trial data with real-world data. For the other stakeholders, the advancement of the methodology will improve the diagnosis and therapy during the process of decision making. Experts from CEE countries recognized the potential of artificial intelligence-based methods employing real-world data for diabetes modelling. These methods are seen as instrumental in elucidating the heterogeneous nature of the disease, supporting clinician decision-making and holding promises for HTA purposes.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Journal titleBiotechnology & Biotechnological Equipment
Numberingvol. 38, no. 1, 2371354
p-ISSN1310-2818
e-ISSN1314-3530
DOIhttps://doi.org/10.1080/13102818.2024.2371354
URN:NBNurn:nbn:hr:184:749876
Publication2024-06-25
Document URLhttps://www.tandfonline.com/doi/full/10.1080/13102818.2024.2371354
Type of resourceText
Access conditionsRestricted access
Terms of useLicence In copyright icon
Created on2024-12-24 07:46:47