Evidence-based medicine (EBM) is defined as a systematic approach to clinical problem solving by the integration of best research evidence with real-world clinical expertise and patient values. Since those early days, decision requirements expanded from patient-centric clinical decision making to a population-based view including regulatory health technology assessments (HTAs). Regulatory bodies mainly rely on the totality of research evidence, which includes preclinical and all available clinical data. HTA bodies primarily focus on clinical data with a strong preference for comparative data from randomized controlled clinical trials (RCTs). Conversely, bedside clinical decisions are largely driven by real-world clinical expertise, which takes into account the individual patients’ preferences, as well as the availability of supportive research evidence. While the focus on research evidence is a typical feature of the early part of the adoption curve for innovative technologies, HTA decision makers need to ensure that clinical expertise is also appropriately included in their decisions, in order to avoid beneficial medications from being not available to patients.
BackgroundHealth Technology Assessments (HTA) procedures differ substantially across the various European countries. We reviewed recent appraisals of a pharmaceutical manufacturer in three major European markets (France; Italy; Germany) and identified and categorized related decision drivers.MethodsNew marketing authorisation between January 2011 and August 2017, and Roche being the Marketing Authorization Holder, were included. Outcome of HTA appraisals by the Haute Autorité de Santé (HAS), Agenzia Italiana del Farmaco (AIFA), and Federal Joint Committee (Gemeinsamer Bundesausschuss, G-BA) were reviewed. Respective decision drivers were identified and commonalities and differences across the three countries were determined leveraging the EUnetHTA conceptual taxonomy (i.e. the 9 domains of the EUnetHTA core model).ResultsWithin that time period Roche received European marketing authorization for eight new molecular entities (10 indications, respectively). Outcome of HTA appraisals was heterogeneous across the three countries. However, the four clinical domains of the EUnetHTA core model were driving the national HTA appraisals, with the clinical effectiveness domain being of most importance. Important drivers related to the other three clinical domains included the target patient population (subgroups, Germany), the current management of the condition (unmet need, Italy), the regulatory status (Orphan Designation, Germany), as well as safety considerations (all three countries). Average time between EMA approval and full commercial availability of new medicines was 63 (Germany), 459 (Italy), and 557 days (France).ConclusionsThe clinical domains of the EUnetHTA framework are mainly driven by national HTA appraisals, providing a suitable starting point for further developing a joint European view on value and evidence. Underlying topics and issues still reveal considerable differences.
This paper provides an introduction to utilities for statisticians working mainly in clinical research who have not had experience of health technology assessment work. Utility is the numeric valuation applied to a health state based on the preference of being in that state relative to perfect health. Utilities are often combined with survival data in health economic modelling to obtain quality-adjusted life years. There are several methods available for deriving the preference weights and the health states to which they are applied, and combining them to estimate utilities, and the clinical statistician has valuable skills that can be applied in ensuring the robustness of the trial design, data collection and analyses to obtain and handle this data. In addition to raising awareness of the subject and providing source references, the paper outlines the concepts and approaches around utilities using examples, discusses some of the key issues, and proposes areas where statisticians can collaborate with health economic colleagues to improve the quality of this important element of health technology assessment.
ObjectivesEvidence requirements and assessment methods access differ between health technology assessment (HTA) agencies. The HTA Core Model® provides a standardized approach to HTA, targeting evidence sharing and collaboration between participating HTA bodies. It is fit for purpose from an industry perspective and was used by pharmaceutical company Roche to develop a framework for internal assessment of evidence required for market access and coverage/reimbursement (“access evidence”).MethodsTools were developed to systematically scope, assess, plan, and summarize access evidence generation. The tools were based mainly on the first four HTA Core Model® domains and rolled-out in selected development teams in 2017. Five months after full implementation, the impact of tools was assessed in an internal survey.ResultsSystematic access evidence generation started with the Access Evidence Questionnaire, to scope evidence requirements and identify evidence gaps. Findings were summarized in the Access Evidence Metric, which assessed the alignment of available/planned evidence against HTA bodies’ requirements and developed scope mitigation strategies. The Access Evidence Plan was then used to plan and document (additional) evidence generation. Once generated, evidence was summarized in the Access Evidence Dossier. A survey of twenty-seven Roche employees involved in evidence generation showed that the tools made discussions around access strategies and evidence more efficient and transparent.ConclusionsThe HTA Core Model® provided a useful framework around which to optimize internal evidence generation and assessment. The benefits of using a standardized HTA approach in industry mirror those expected from implementing the HTA Core Model® in HTA agencies.
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