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The purpose of this article is to investigate the common facilitators and barriers associated with the implementation of hospital-based health technology assessment (HB-HTA) across diverse hospital settings in seven countries. Through a two-round Delphi study, insights were gathered from a panel of 15 HTA specialists from France, Hungary, Italy, Kazakhstan, Poland, Switzerland, and Ukraine. Experts initially conducted a comprehensive review of the HB-HTA implementation in their respective countries, identifying the barriers and facilitators through descriptive analysis. Subsequently, panel experts ranked these identified barriers and facilitators on a seven-point Likert scale. A median agreement score ≥ 6 and interquartile range (IQR) ≤ 1 was accepted as reaching a consensus. Out of the 12 statements categorized as external and internal barriers and facilitators, the expert panel reached consensus on six statements (two barriers and four facilitators). The external barrier, which achieved consensus, was the lack of the formal recognition of the role of HB-HTA in national or regional legislations. The internal barrier reaching consensus was the limited availability of human resources dedicated to HB-HTA. This qualitative study indicates that HB-HTA still has progress to make before being formally accepted and integrated across most countries, although by building on the facilitating factors we identified there may be an opportunity for the implementation of internationally developed strategies to strengthen HB-HTA practices. [ABSTRACT FROM AUTHOR]

The United States has begun assessing the value of pharmaceuticals to inform negotiated prices in the Medicare program. Given strong political objections in the United States to the use of QALYs, Medicare will need to adopt an alternative approach to measuring value. In this narrative review, we identified six alternative approaches to measuring value (equal value life-years, health years in total, generalized risk-adjusted cost-effectiveness, severity weighting based on absolute or proportional shortfall, comparative effectiveness based on conventional clinical endpoints, and comparative effectiveness based on both conventional endpoints and patient-centric value elements) and five criteria for assessing these approaches (responsiveness to concerns about discrimination, feasibility, transparency, flexibility, and the ability to incorporate factors beyond traditional value elements). Four of the alternatives are broadly aligned with the cost-effectiveness framework, but none fully addresses all aspects of the stated concerns that QALYs may be used to unintentionally implement discrimination. We note, however, that the extent to which these concerns lead to discrimination in practice is unknown. Finally, we recommend an approach for measuring value in terms of comparative effectiveness that combines quantitative ranking and weighting of distinct criteria (including patient-centric value elements) with deliberation. [ABSTRACT FROM AUTHOR]

Objectives: Economic evaluations (EEs) are commonly used by decision makers to understand the value of health interventions. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS 2022) provide reporting guidelines for EEs. Healthcare systems will increasingly see new interventions that use artificial intelligence (AI) to perform their function. We developed Consolidated Health Economic Evaluation Reporting Standards for Interventions that use AI (CHEERS-AI) to ensure EEs of AI-based health interventions are reported in a transparent and reproducible manner., Methods: Potential CHEERS-AI reporting items were informed by 2 published systematic literature reviews of EEs and a contemporary update. A Delphi study was conducted using 3 survey rounds to elicit multidisciplinary expert views on 26 potential items, through a 9-point Likert rating scale and qualitative comments. An online consensus meeting was held to finalize outstanding reporting items. A digital health patient group reviewed the final checklist from a patient perspective., Results: A total of 58 participants responded to survey round 1, 42, and 31 of whom responded to rounds 2 and 3, respectively. Nine participants joined the consensus meeting. Ultimately, 38 reporting items were included in CHEERS-AI. They comprised the 28 original CHEERS 2022 items, plus 10 new AI-specific reporting items. Additionally, 8 of the original CHEERS 2022 items were elaborated on to ensure AI-specific nuance is reported., Conclusions: CHEERS-AI should be used when reporting an EE of an intervention that uses AI to perform its function. CHEERS-AI will help decision makers and reviewers to understand important AI-specific details of an intervention, and any implications for the EE methods used and cost-effectiveness conclusions., Competing Interests: Author Disclosures Author disclosure forms can be accessed below in the Supplemental Material section., (Copyright © 2024. Published by Elsevier Inc.)

In early 2024, the Centers for Medicare & Medicaid Services (CMS) will send initial price offers to the manufacturers of the first 10 drugs selected for the Medicare Drug Price Negotiation Program, established under the Inflation Reduction Act. However, CMS has not specified exactly how it will adjust the starting point for an initial price offer based on assessment of a drug's clinical benefit. This article addresses unanswered questions relating to CMS' methods for assessing clinical benefit. Specifically, we address how CMS can weigh various measures of evidence, ensure transparency and consistency, meaningfully incorporate patient and other stakeholder perspectives, and support addressing evidence gaps. We propose a 2-step approach for assessing the overall clinical benefit of a selected drug compared with its therapeutic alternatives that builds on the framework outlined by CMS. In step 1, CMS would evaluate conventional clinical benefit, defined in terms of outcomes commonly used in clinical studies for the selected drug and indications. In step 2, CMS would evaluate other outcomes broadly related to patient experience that are not adequately represented in the clinical literature. Overall, our approach incorporates the advantages of both qualitative and quantitative approaches to value assessment and decision-making. We describe a set of loose decision rules to improve transparency and consistency, recommend incorporating ranks and weights to signal to researchers and manufacturers which elements of clinical benefit and sources of data are the most important, and center meaningful deliberation with clinical experts, patients, and caregivers.

Patients' perspectives are important to identify preferences, estimate values and appreciate unmet medical needs in the process of research and development and subsequent assessment of new health technologies. Patient and public involvement in health technology assessment (HTA) is essential in understanding and assessing wider implications of coverage and reimbursement decisions for patients, their relatives, caregivers, and the general population. There are two approaches to incorporating the patients' voice in HTA, preferably used in a mix. In the first one, patients, caregivers and/or their representatives directly participate at discussions in different stages of the HTA process, often at the same table with other stakeholders. Secondly, patient involvement activities can be supported by evidence on patient value and experience collected directly from patients, caregivers and/or their representatives often by patient groups Patient involvement practices, however, are limited in Central and Eastern European (CEE) countries without clear methodology or regulatory mechanisms to guide patient involvement in the HTA process. This poses the question of transferability of practices used in other countries, and might call for the development of new CEE-specific guidelines and methods. In this study we aim to map potential barriers of patient involvement in HTA in countries of the CEE region., Competing Interests: Authors IJ, AZ, BN, and ZK are employed by Syreon Research Institute. At the time of the study IJ was the President of the European Patients' Forum Youth Group and a Board of Trustees member at the EUPATI Foundation. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Dimitrova, Jakab, Mitkova, Kamusheva, Tachkov, Nemeth, Zemplenyi, Dawoud, Delnoij, Houýez and Kalo.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Tachkov, Zemplenyi, Kamusheva, Dimitrova, Siirtola, Pontén, Nemeth, Kalo and Petrova.)