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Using Real-World Data in Health Technology Assessment (HTA) Practice: A Comparative Study of Five HTA Agencies.

ABSTRACT: BACKGROUND:Reimbursement decisions are conventionally based on evidence from randomised controlled trials (RCTs), which often have high internal validity but low external validity. Real-world data (RWD) may provide complimentary evidence for relative effectiveness assessments (REAs) and cost-effectiveness assessments (CEAs). This study examines whether RWD is incorporated in health technology assessment (HTA) of melanoma drugs by European HTA agencies, as well as differences in RWD use between agencies and across time. METHODS:HTA reports published between 1 January 2011 and 31 December 2016 were retrieved from websites of agencies representing five jurisdictions: England [National Institute for Health and Care Excellence (NICE)], Scotland [Scottish Medicines Consortium (SMC)], France [Haute Autorité de santé (HAS)], Germany [Institute for Quality and Efficacy in Healthcare (IQWiG)] and The Netherlands [Zorginstituut Nederland (ZIN)]. A standardized data extraction form was used to extract information on RWD inclusion for both REAs and CEAs. RESULTS:Overall, 52 reports were retrieved, all of which contained REAs; CEAs were present in 25 of the reports. RWD was included in 28 of the 52 REAs (54%), mainly to estimate melanoma prevalence, and in 22 of the 25 (88%) CEAs, mainly to extrapolate long-term effectiveness and/or identify drug-related costs. Differences emerged between agencies regarding RWD use in REAs; the ZIN and IQWiG cited RWD for evidence on prevalence, whereas the NICE, SMC and HAS additionally cited RWD use for drug effectiveness. No visible trend for RWD use in REAs and CEAs over time was observed. CONCLUSION:In general, RWD inclusion was higher in CEAs than REAs, and was mostly used to estimate melanoma prevalence in REAs or to predict long-term effectiveness in CEAs. Differences emerged between agencies' use of RWD; however, no visible trends for RWD use over time were observed.

SUBMITTER: Makady A

PROVIDER: S-EPMC5834594 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Using Real-World Data in Health Technology Assessment (HTA) Practice: A Comparative Study of Five HTA Agencies.

Makady Amr A van Veelen Ard A Jonsson Páll P Moseley Owen O D'Andon Anne A de Boer Anthonius A Hillege Hans H Klungel Olaf O Goettsch Wim W

PharmacoEconomics 20180301 3

<h4>Background</h4>Reimbursement decisions are conventionally based on evidence from randomised controlled trials (RCTs), which often have high internal validity but low external validity. Real-world data (RWD) may provide complimentary evidence for relative effectiveness assessments (REAs) and cost-effectiveness assessments (CEAs). This study examines whether RWD is incorporated in health technology assessment (HTA) of melanoma drugs by European HTA agencies, as well as differences in RWD use b ...[more]

PMID: 29214389

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Project description:BackgroundThe number of Health Technology Assessment (HTA) agencies increases. One component of HTAs are economic aspects. To incorporate economic aspects commonly economic evaluations are performed. A convergence of recommendations for methods of health economic evaluations between international HTA agencies would facilitate the adaption of results to different settings and avoid unnecessary expense. A first step in this direction is a detailed analysis of existing similarities and differences in recommendations to identify potential for harmonization. The objective is to provide an overview and comparison of the methodological recommendations of international HTA agencies for economic evaluations.MethodsThe webpages of 127 international HTA agencies were searched for guidelines containing recommendations on methods for the preparation of economic evaluations. Additionally, the HTA agencies were requested information on methods for economic evaluations. Recommendations of the included guidelines were extracted in standardized tables according to 13 methodological aspects. All process steps were performed independently by two reviewers.ResultsFinally 25 publications of 14 HTA agencies were included in the analysis. Methods for economic evaluations vary widely. The greatest accordance could be found for the type of analysis and comparator. Cost-utility-analyses or cost-effectiveness-analyses are recommended. The comparator should continuously be usual care. Again the greatest differences were shown in the recommendations on the measurement/sources of effects, discounting and in the analysis of sensitivity. The main difference regarding effects is the focus either on efficacy or effectiveness. Recommended discounting rates range from 1.5%-5% for effects and 3%-5% for costs whereby it is mostly recommended to use the same rate for costs and effects. With respect to the analysis of sensitivity the main difference is that oftentimes the probabilistic or deterministic approach is recommended exclusively. Methods for modeling are only described vaguely and mainly with the rational that the "appropriate model" depends on the decision problem. Considering all other aspects a comparison is challenging as recommendations vary regarding detailedness and addressed issues.ConclusionThere is a considerable unexplainable variance in recommendations. Further effort is needed to harmonize methods for preparing economic evaluations.

Project description:BackgroundHealth technology assessment (HTA) agencies have an important role to play in managing the rising demands on health systems. However, creating and running such agencies potentially diverts resources from frontline services. A large number of studies address the question of 'what is the impact of HTA?'. Several points of heterogeneity in this literature include: purpose of the study, definition of HTA, definition of impact, and scope and rigour of evaluations. Our study seeks to address several limitations in this literature. This study aims to explore the mechanisms of impact of an HTA agency. In doing so, we consider HTA as an institution rather than a knowledge product to build an impact evaluation framework from an international, multi-stakeholder and multi-dimensional perspective.MethodsWe conducted 9 key informant interviews with experts from the international HTA community. We addressed several questions, informed by existing frameworks of impact within the literature, to understand their perspectives on the mechanisms of impact of an HTA agency. We analyse data using logic modelling and impact mapping, as tools to understand and visualise mechanisms of change.FindingsOur impact mapping highlights several distinct, but not necessarily mutually exclusive, mechanisms through which the overall impact of an HTA agency is achieved. These are: the effective conduct of HTA studies; effective use of HTA in agenda-setting and policy formulation processes; effective engagement and external communications; good institutional reputation and fit within the healthcare and policy-making system; effective use of HTA as a tool for the negotiation of health technology prices; and the effective implementation of policy change regarding health technologies. We also identify indicators of these effects.ConclusionsOur findings and resulting evaluation framework complement and add to existing literature by offering a new perspective on the mechanisms by which HTA agencies generate impact. This new perspective considers HTA as an institution rather than a knowledge product, is international, multi-dimensional, and includes multi-stakeholder views. We hope the analysis will be useful to countries interested in managing HTA performance.

Project description:Aim: Regulatory and health technology assessment (HTA) agencies have increasingly published frameworks, guidelines, and recommendations for the use of real-world evidence (RWE) in healthcare decision-making. Variations in the scope and content of these documents, with updates running in parallel, may create challenges for their implementation especially during the market authorization and reimbursement phases of a medicine's life cycle. This environmental scan aimed to comprehensively identify and summarize the guidance documents for RWE developed by most well-established regulatory and reimbursement agencies, as well as other organizations focused on healthcare decision-making, and present their similarities and differences. Methods: RWE guidance documents, including white papers from regulatory and HTA agencies, were reviewed in March 2024. Data on scope and recommendations from each body were extracted by two reviewers and similarities and differences were summarized across four topics: study planning, choosing fit-for-purpose data, study conduct, and reporting. Post-authorization or non-pharmacological guidance was excluded. Results: Forty-six documents were identified across multiple agencies; US FDA produced the most RWE-related guidance. All agencies addressed specific and often similar methodological issues related to study design, data fitness-for-purpose, reliability, and reproducibility, although inconsistency in terminologies on these topics was noted. Two HTA bodies (National Institute for Health and Care Excellence [NICE] and Canada's Drug Agency) each centralized all related RWE guidance under a unified framework. RWE quality tools and checklists were not consistently named and some differences in preferences were noted. European Medicines Agency, NICE, Haute Autorité de Santé, and the Institute for Quality and Efficiency in Health Care included specific recommendations on the use of analytical approaches to address RWE complexities and increase trust in its findings. Conclusion: Similarities in agencies' expectations on RWE studies design, quality elements, and reporting will facilitate evidence generation strategy and activities for manufacturers facing multiple, including global, regulatory and reimbursement submissions and re-submissions. A strong preference by decision-making bodies for local real-world data generation may hinder opportunities for data sharing and outputs from international federated data networks. Closer collaboration between decision-making agencies towards a harmonized RWE roadmap, which can be centrally preserved in a living mode, will provide manufacturers and researchers clarity on minimum acceptance requirements and expectations, especially as novel methodologies for RWE generation are rapidly emerging.

Project description:ObjectiveWe aim to develop a comprehensive checklist for evaluating Health Technology Assessment (HTA) studies commissioned in India. The primary objective of this work is to capture all vital aspects of an HTA study in terms of conduct, reporting and quality.MethodologyThe development of a quality appraisal checklist included 3 steps. First, a targeted review of the literature was done to gather information on existing HTA checklists. After reviewing these checklists, an initial draft of the HTA quality appraisal checklist (HTA-QAC) for India was prepared with discussion amongst the authors. Second, the draft checklist was reviewed by the members of the Technical Appraisal Committee (TAC) and their feedback was incorporated. Subsequently, the revised checklist was presented at a virtual meeting of the TAC. Finally, a pilot phase was undertaken to apply HTA-QAC for the approved HTA study reports. Three rounds of virtual discussions were held with the researchers who were involved in the conduct of these HTA studies to resolve any discordance in opinion or develop solutions for the problems in the use of the HTA-QAC followed by a further revision of the checklist.ResultsThe HTA-QAC is divided into two parts: a self-reporting section to be completed by the author, and the other to be completed by the reviewer. The reviewer checklist has two sections: one to review the report and the other to review the model. The author section is in a self-reporting format, which includes details of basic study information, the rationale for the study, policy relevance, study description, study methods, reporting of model parameters, and results. The reviewer section of the checklist focuses on the quality aspect of the conducted study. The domains included in the report review include details on study methodology, results, discussion, and conclusion. The second part of the reviewer section of HTA-QAC constitutes a review of the model in terms of model assumptions, functionality, model inputs, calculations, uncertainty analysis, model output, and model validation.ConclusionWe recommend a standardised process of quality appraisal to ensure the high quality of HTA evidence for policy use in the Indian context. The proposed HTA-QAC will help authors to ensure standardised reporting, as well as allow reviewers to assess the quality of analysis.

Project description:BackgroundDigital technologies are transforming the health care system. A large part of information is generated as real-world data (RWD). Data from electronic health records and digital biomarkers have the potential to reveal associations between the benefits and adverse events of medicines, establish new patient-stratification principles, expose unknown disease correlations, and inform on preventive measures. The impact for health care payers and providers, the biopharmaceutical industry, and governments is massive in terms of health outcomes, quality of care, and cost. However, a framework to assess the preliminary quality of RWD is missing, thus hindering the conduct of population-based observational studies to support regulatory decision-making and real-world evidence.ObjectiveTo address the need to qualify RWD, we aimed to build a web application as a tool to translate characterization of some quality parameters of RWD into a metric and propose a standard framework for evaluating the quality of the RWD.MethodsThe RWD-Cockpit systematically scores data sets based on proposed quality metrics and customizable variables chosen by the user. Sleep RWD generated de novo and publicly available data sets were used to validate the usability and applicability of the web application. The RWD quality score is based on the evaluation of 7 variables: manageability specifies access and publication status; complexity defines univariate, multivariate, and longitudinal data; sample size indicates the size of the sample or samples; privacy and liability stipulates privacy rules; accessibility specifies how the data set can be accessed and to what granularity; periodicity specifies how often the data set is updated; and standardization specifies whether the data set adheres to any specific technical or metadata standard. These variables are associated with several descriptors that define specific characteristics of the data set.ResultsTo address the need to qualify RWD, we built the RWD-Cockpit web application, which proposes a framework and applies a common standard for a preliminary evaluation of RWD quality across data sets-molecular, phenotypical, and social-and proposes a standard that can be further personalized by the community retaining an internal standard. Applied to 2 different case studies-de novo-generated sleep data and publicly available data sets-the RWD-Cockpit could identify and provide researchers with variables that might increase quality.ConclusionsThe results from the application of the framework of RWD metrics implemented in the RWD-Cockpit application suggests that multiple data sets can be preliminarily evaluated in terms of quality using the proposed metrics. The output scores-quality identifiers-provide a first quality assessment for the use of RWD. Although extensive challenges remain to be addressed to set RWD quality standards, our proposal can serve as an initial blueprint for community efforts in the characterization of RWD quality for regulated settings.

Project description:IntroductionIn this literature review we evaluated the real-world clinical effectiveness of switching Japanese diabetic patients from their current insulin regimen to insulin degludec (IDeg).MethodsStudies were identified from Japanese Diabetes Society (JDS) abstracts (2014-2015) and PubMed (2012 onwards). Inclusion criteria were: Japanese population, >15 participants, and studies switching patients from basal or basal-bolus insulin regimens to IDeg. Randomized controlled trials and case reports were excluded. Weighted mean changes in safety and effectiveness endpoints were calculated using the number of patients in each study.ResultsIn total, 81 JDS abstracts and seven manuscripts met the search criteria, representing 4238 patients [1028 with type 1 diabetes (T1D), 602 with type 2 diabetes (T2D), 2608 with unspecified or mixed diabetes]. Glycated hemoglobin (HbA1c) was reported in 93% of studies, with an improvement in 84% of these (51% significant, 33% numerical), no change in 12%, and worsening in 4% (3% numerical, 1% significant). Across all studies, the weighted mean absolute change in HbA1c was -0.3% (-2.7 mmol/mol). Basal insulin dose was reported in 58% of studies and was lower in 60% of these (30% significant, 30% numerical), numerically unchanged in 26%, and higher in 14% (2% significant, 12% numerical). The weighted mean change in basal insulin dose was -4.8% and -3.0% for all studies and for studies with only significant results, respectively. The weighted mean change in basal dose based on all studies was -8.9, -5.5, and -2.9% for the T1D, T2D, and unspecified patient populations, respectively. Hypoglycemia was recorded in 31% of the studies. After switching treatment to IDeg, 55% of studies reported decreased hypoglycemia, 29% no change, and 16% an increase. Quality of life (QoL) was measured in 11% of studies, of which 82% reported improved QoL after switching, and 18% reported no change in QoL.ConclusionSwitching from a conventional basal insulin to IDeg has the potential to improve HbA1c with a lower insulin dose. Switching to IDeg may also provide a reduced risk of hypoglycemia and improvement in QoL.FundingNovo Nordisk.

Dataset Information

Using Real-World Data in Health Technology Assessment (HTA) Practice: A Comparative Study of Five HTA Agencies.

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Using Real-World Data in Health Technology Assessment (HTA) Practice: A Comparative Study of Five HTA Agencies.

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