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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.

IntroductionMeaningful patient involvement in health technology assessment (HTA) is essential in ensuring that the interests of the affected patient population, their families, and the general public are accurately reflected in coverage and reimbursement decisions. Central and Eastern European (CEE) countries are generally at less advanced stages of implementing HTA, which is particularly true for patient involvement activities. As part of the Horizon2020 HTx project, this research aimed to form recommendations for critical barriers to patient involvement in HTA in CEE countries.MethodsBuilt on previous research findings on potential barriers, a prioritisation survey was conducted online with CEE stakeholders. Recommendations for prioritised barriers were formed through a face-to-face workshop by CEE stakeholders and HTx experts.ResultsA total of 105 stakeholders from 13 CEE countries completed the prioritisation survey and identified 12 of the 22 potential barriers as highly important. The workshop had 36 participants representing 9 CEE countries, and 5 Western European countries coming together to discuss solutions in order to form recommendations based on best practices, real-life experience, and transferability aspects. Stakeholder groups involved in both phases included HTA organisation representatives, payers, patients, caregivers, patient organisation representatives, patient experts, health care providers, academic and non-academic researchers, health care consultants and health technology manufacturers/providers. As a result, 12 recommendations were formed specified to the CEE region’s context, but potentially useful for a broader geographic audience.ConclusionIn this paper, we present 12 recommendations for meaningful, systematic, and sustainable patient involvement in HTA in CEE countries. Our hope is that engaging more than a hundred CEE stakeholders in the study helped to spread awareness of the importance and potential of patient involvement and that the resulting recommendations provide tangible steps for the way forward. Future studies shall focus on country-specific case studies of the implemented recommendations.

BackgroundArtificial intelligence (AI) has attracted much attention because of its enormous potential in healthcare, but uptake has been slow. There are substantial barriers that challenge health technology assessment (HTA) professionals to use AI-generated evidence for decision-making from large real-world databases (e.g., based on claims data). As part of the European Commission-funded HTx H2020 (Next Generation Health Technology Assessment) project, we aimed to put forward recommendations to support healthcare decision-makers in integrating AI into the HTA processes. The barriers, addressed by the paper, are particularly focusing on Central and Eastern European (CEE) countries, where the implementation of HTA and access to health databases lag behind Western European countries.MethodsWe constructed a survey to rank the barriers to using AI for HTA purposes, completed by respondents from CEE jurisdictions with expertise in HTA. Using the results, two members of the HTx consortium from CEE developed recommendations on the most critical barriers. Then these recommendations were discussed in a workshop by a wider group of experts, including HTA and reimbursement decision-makers from both CEE countries and Western European countries, and summarized in a consensus report.ResultsRecommendations have been developed to address the top 15 barriers in areas of (1) human factor-related barriers, focusing on educating HTA doers and users, establishing collaborations and best practice sharing; (2) regulatory and policy-related barriers, proposing increasing awareness and political commitment and improving the management of sensitive information for AI use; (3) data-related barriers, suggesting enhancing standardization and collaboration with data networks, managing missing and unstructured data, using analytical and statistical approaches to address bias, using quality assessment tools and quality standards, improving reporting, and developing better conditions for the use of data; and (4) technological barriers, suggesting sustainable development of AI infrastructure.ConclusionIn the field of HTA, the great potential of AI to support evidence generation and evaluation has not yet been sufficiently explored and realized. Raising awareness of the intended and unintended consequences of AI-based methods and encouraging political commitment from policymakers is necessary to upgrade the regulatory and infrastructural environment and knowledge base required to integrate AI into HTA-based decision-making processes better.

Aim: Real-world data and real-world evidence (RWE) are becoming more important for healthcare decision making and health technology assessment. We aimed to propose solutions to overcome barriers preventing Central and Eastern European (CEE) countries from using RWE generated in Western Europe. Materials & methods: To achieve this, following a scoping review and a webinar, the most important barriers were selected through a survey. A workshop was held with CEE experts to discuss proposed solutions. Results: Based on survey results, we selected the nine most important barriers. Multiple solutions were proposed, for example, the need for a European consensus, and building trust in using RWE. Conclusion: Through collaborationwith regional stakeholders, we proposed a list of solutions to overcome barriers on transferring RWE from Western Europe to CEE countries.

Objectives: Methodological challenges in the evaluation of medical devices (MDs) may be different for early and late technology adopter countries, as well as the potential health technology assessment (HTA) solutions to tackle them. This study aims to provide guidance to Central and Eastern European (CEE) countries on how to address key challenges of HTA for MDs with special focus on the transferability of scientific evidence.Methods: As part of the COMED Horizon 2020 project, a comprehensive list of issues related to MD HTA were identified based on a targeted literature review. Health technology assessment issues which pose a greater challenge or require different solutions in late technology adopter countries were selected. Draught recommendations to address these issues were developed and discussed in a focus group. The recommendations were then validated with a wider group of experts, including HTA and reimbursement decision makers from CEE countries in May and June 2020.Results: A consolidated list of 11 recommendations were developed in 3 major areas: (1) clinical value assessment, focusing on the use of joint EU work, relying on real-world evidence, use of coverage with evidence development schemes, transferring evidence from foreign countries and addressing the challenges of learning curve and centre effect; (2) economic value assessment, covering cost calculation of complex medical devices and transferability of economic evaluations of MDs; (3) HTA processes, related to the frequent product modifications and various indications of MDs.Conclusions: Central and Eastern European countries with limited resources for conducting HTA, can benefit from HTA methods and evidence generated in early technology adopter countries. Considering the appropriate reuse of international HTA materials, late technology adopter countries can still implement HTA, even for MDs, which have a more limited evidence base compared with pharmaceuticals.

Background: Despite international initiatives on collaboration within the field of rare diseases, patient access to orphan medicinal products (OMPs) and healthcare services differ greatly between countries. This study aimed to create a comprehensive and in-depth overview of rare diseases policies and reimbursement of OMPs in a selection of 12 countries in the Western Eurasian region: Armenia, France, Germany, Kazakhstan, Latvia, The Netherlands, Poland, Romania, Russia, Turkey, Ukraine, and the United Kingdom.Methods: A systematic literature review was performed and an analysis of publicly available legislative and rare disease health policy data was undertaken in five focus areas: rare disease definition, newborn screening, registries, national plans, access to/reimbursement of OMPs.Results: Screening programs are broadly implemented but the number of screened diseases differs significantly (2–35 diseases), either between EU and non-EU countries, between EU member states and sometimes even within a single country. In most countries rare disease registries are operating with regional, national, European or worldwide coverage. The number of rare disease registries is growing, as a result of the National Plans (EU) and increased international scientific cooperation. France, Russia, and Poland have a centrally acting registry. National plans are present in all EU countries but implementation varies and is ongoing. The number of reimbursed OMPs in the selected countries ranges from nearly all available OMPs in the Netherlands, Germany, and France to zero in Armenia. Reimbursement rules differ considerably regionally and a trend is observed of reimbursement conditions getting stricter for expensive (orphan) drugs.Discussion: Inequality in patient access to new OMPs still exists due to variations in national policies, healthcare budgets, health insurance, and reimbursement systems. The observed differences are challenging for rare disease patients, health authorities and manufacturers alike. Progress can be seen, however, and international cooperation and harmonization is slowly but steadily expanding in the rare disease arena.