Aim: To provide insights into the capacity to conduct health technology assessment (HTA) in Central, Eastern, and South-Eastern Europe (CESEE), taking account of technical, financial, networking, and human resources.
Methods: An e-mail survey of 257 CESEE key informants involved in HTA was undertaken between March and April 2014. Contact e-mail addresses were identified from the internet. The survey questionnaire consisted of 3 sections: i) characteristics of the organization performing HTA, (ii) networking in HTA, and (iii) resources allocated for HTA.
Results: The survey was completed by 41 respondents representing a wide range of institutions from CESEE countries (response rate of 19.8%). Less than a quarter of respondents reported that their institutions had HTA-specific budgets, whereas the majority indicated that their institutions participated in HTA networks either at domestic or international levels. Although almost half of respondents indicated that their institutions offered HTA training, a shortage in skills training was suggested as the main barrier to HTA.
Conclusion: This is the first survey to thoroughly assess the state of HTA capacity in the CESEE region. To strengthen HTA capacity, CESEE countries should increase financial, technical, and training resources. To strengthen collaboration, the European Union and other international bodies should assist existing HTA networks in fulfilling their regional activities through leadership, advocacy to local policymakers, funding, and technical assistance.
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http://dx.doi.org/10.3325/cmj.2016.57.66 | DOI Listing |
Pharmacoepidemiol Drug Saf
January 2025
Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Purpose: Real-world evidence (RWE) is increasingly considered in regulatory and health technology assessment (HTA) decision-making, though perspectives on its relevance may vary. Expanding on a recent review regarding regulatory decisions, this study aimed to identify factors influencing the need for RWE in HTA decision-making, confirm and enrich factors with stakeholder views, and evaluate similarities and differences between regulatory and HTA needs.
Methods: Previous scoping review methodology was used to identify factors influencing the need for RWE in HTA decision-making.
BMJ Open
January 2025
Institute of Population Health, Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK.
Objectives: Platform trials were used successfully in adult populations during the COVID-19 pandemic. By testing multiple treatments within a single trial, platform trials can help identify the most effective treatments (and any interactions between treatments) for patients more quickly and with less burden for patients and their families. The aim of this qualitative research was to inform the design of the first adaptive platform trial for paediatric intensive care in the UK with young people, parents/carers and paediatric intensive care unit (PICU) staff.
View Article and Find Full Text PDFValue Health
October 2024
Health Intervention and Technology Assessment Program (HITAP), Ministry of Public Health, Nonthaburi, Thailand; Saw Swee Hock School of Public Health, National University of Singapore, Singapore.
Objectives: Health technology assessment (HTA) guidelines are intended to support successful implementation of HTA by enhancing consistency and transparency in concepts, methods, process, and use, thereby enhancing the legitimacy of the decision-making process. This report lays out good practices and practical recommendations for developing or updating HTA guidelines to ensure successful implementation.
Methods: The task force was established in 2022 and comprised experts and academics from various geographical regions, each with substantial experience in developing HTA guidelines for national health policymaking.
Int J Mol Sci
December 2024
Qingdao Institute of Software, College of Computer Science and Technology, China University of Petroleum (East China), Qingdao 266580, China.
Accurate protein secondary structure prediction (PSSP) plays a crucial role in biopharmaceutics and disease diagnosis. Current prediction methods are mainly based on multiple sequence alignment (MSA) encoding and collaborative operations of diverse networks. However, existing encoding approaches lead to poor feature space utilization, and encoding quality decreases with fewer homologous proteins.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!