Using Real-World Data in the Health Technology Assessment of Pharmaceuticals: Strengths, Difficulties, and a Pragmatic Way Forward

Advancements in Electronic Medical Records for Clinical Trials: Enhancing Data Management and Research Efficiency

Recent advancements in electronic medical records (EMRs) have transformed clinical trials and healthcare systems by improving data accuracy, regulatory compliance, and integration with decision support tools. These innovations enhance trial efficiency, streamline patient recruitment, and enable large-scale data analysis while bridging clinical practice with research. Despite these benefits, challenges such as data standardization, privacy concerns, and usability issues persist. Overcoming these barriers through policy reforms, technological innovations, and robust methodologies is essential to maximizing the potential of EMRs. We examine current developments, challenges, and future directions for optimizing EMRs in clinical trials and healthcare delivery.

[Real-world data for comparative effectiveness research: Taking stock of available data sources in Germany with special regard to registries]

Using real-world data (RWD) for comparative effectiveness research has gained increasing attention. Real-world data is usually not collected with the primary aim of answering questions about the comparative effectiveness of medical interventions. Therefore, data collection is often not optimally designed for this purpose. For this reason, using it can be associated with several data-related or analysis-related problems. This article has two aims: First of all, we will outline the basic requirements for comparative non-randomized studies based on RWD. In addition, the advantages and disadvantages of potentially eligible RWD in Germany will be considered. In particular, the use of registry data will be discussed, as these currently appear to be the most suitable for comparing the effectiveness of interventions. There are now various databases in Germany that contain RWD and can potentially be used for comparative effectiveness research. If they contain all the necessary information and if the data are of sufficient quality, they could offer a timely and efficient way of determining the effectiveness of medical interventions. However, our analysis shows that the use of this data is sometimes associated with considerable limitations. RWD is often highly aggregated and thus may not be sufficiently detailed to select the subjects precisely or to emulate the intervention or control interventions satisfactorily. In addition, many data sources only encompass a limited set of variables and limited time horizons (e.g., only hospitalization) according to their intended purpose (e.g., billing). Therefore, it is often questionable whether this includes all endpoints on benefit and harm that are important for the assessment and whether sufficiently long observation horizons/follow-up periods are given. Similarly, it is often questionable whether all necessary data to avoid bias are included. Furthermore, it is often difficult to assess suitability in advance due to the lack of available information.

Real-world evidence to support health technology assessment and payer decision making: is it now or never?

OBJECTIVES

The aim of this policy article is twofold: (i) to provide a summary and update of recent important policy developments, in particular relevant guidance on the use of real-world data/real-world evidence (RWD/RWE) by health technology assessment (HTA) bodies and (ii) to set out our policy recommendations on how the different elements of an "RWE framework" we have previously developed could support, further enhance and facilitate the use of RWE for HTA purposes and by HTA bodies and payers.

METHODS

We undertook a targeted review and analysis of recent important policy developments. The aim was to build on our recommendations from previous work on the "RWE Framework," and consider how the relevant tools from our Framework can further enhance and facilitate the use of RWE for HTA purposes and by HTA bodies/payers.

RESULTS

We provide eight conditions that we argue would, in combination, constitute the optimal use and acceptance of RWD/RWE for HTA. We believe that, should the eight conditions hold, RWD/RWE would enable more efficient access to medicines and healthcare technologies for patients.

CONCLUSIONS

High-quality, fit-for-purpose RWD/RWE can and should be used more frequently in HTA. Multi-stakeholder and cross-geography collaborative partnerships are needed to align on best practices to optimize the evidence that needs to be generated to satisfy all stakeholders' needs.

NON-SMALL-CELL LUNG CANCER: Real-World Population-Based Cohorts' Study

INTRODUCTION

This retrospective follow-up study evaluates patient outcomes and treatment costs in two cohorts of incident NSCLC patients recorded in the population-based cancer registry of the Veneto Region in 2017 and 2019.

METHODS

This study examines two cohorts of incident NSCLC patients recorded by the Regional Veneto cancer registry in 2017 (493 patients) and 2019 (557 patients). Cancer patients were followed for three years after diagnosis to assess the disease's outcomes and analyze the overall treatment-related costs. Overall survival and cancer-specific mortality were evaluated using Cox regression models. The log-transformed overall treatment costs for the 3 years following diagnosis were analyzed using linear regression.

RESULTS

The overall mortality risk significantly lowered in the 2019 cohort (HR 0.84; 95% CI 0.72-0.98, p = 0.024). Stage III patients were not associated with a significant overall survival rate (HR 0.71; 95% CI 0.50-1.02; p = 0.065) but were associated with significantly higher cancer-specific survival (HR 0.61; 95% CI 0.41-0.91; p = 0.015). Overall, the 2019 cohort showed significantly higher costs (coefficient 0.16; 95% CI 0.02-0.30, p = 0.025), particularly as a result of increases in the costs of drug administration, outpatient services, and medical devices. However, during the same 3-year follow-up period, this cohort featured lower average costs for hospice care and hospitalizations.

CONCLUSIONS

These results revealed notable differences in clinical outcomes and patient-related costs in incident NSCLCs in 2017 and 2019. The study highlights the importance of monitoring clinical outcomes and management costs in real-world oncology practice.

A Comprehensive Framework for Evaluating the Value Created by Real-World Evidence for Diverse Stakeholders: The Case for Coordinated Registry Networks

OBJECTIVES

This manuscript presents a comprehensive framework for the assessment of the value of real-world evidence (RWE) in healthcare decision-making. While RWE has been proposed to overcome some limitations of traditional, one-off studies, no systematic framework exists to measure if RWE actually lowers the burden. This framework aims to fill that gap by providing conceptual approaches for evaluating the time and cost efficiencies of RWE, thus guiding strategic investments in RWE infrastructure.

METHODS

The framework consists of four components: (114th Congress. 21st Century Cures Act.; 2015. https://www.congress.gov/114/plaws/publ255/PLAW-114publ255.pdf .) identification of stakeholders using and producing RWE, (National Health Council. Glossary of Patient Engagement Terms. Published 2019. Accessed May 18. 2021. https://nationalhealthcouncil.org/glossary-of-patient-engagement-terms/ .) understanding value propositions on how RWE can benefit stakeholders, (Center for Drug Evaluation and Research. CDER Patient-Focused Drug Development. U.S. Food & Drug Administration.) defining key performance indicators (KPIs), and (U.S. Department of Health and Human Services - Food and Drug Administration: Center for Devices and Radiological Health and Center for Biologics Evaluation and Research. Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices - Guidance for Industry and Food and Drug Administration Staff. 2017. http://www.fda.gov/BiologicsBloodVaccines/GuidanceComplianceRegulatoryInformation/Guida .) establishing metrics and case studies to assess value. KPIs are categorized as 'better, faster, or cheaper" as an indicator of value: better focusing on high-quality actionable evidence; 'faster,' denoting time-saving in evidence generation, and 'cheaper,' emphasizing cost-efficiency decision compared to methodologies that do not involve data routinely collected in clinical practice. Metrics and relevant case studies are tailored based on stakeholder value propositions and selected KPIs that can be used to assess what value has been created by using RWE compared to traditional evidence-generation approaches and comparing different RWE sources.

RESULTS

Operationalized through metrics and case studies drawn from the literature, the value of RWE is documented as improving treatment effect heterogeneity evaluation, expanding medical product labels, and expediting post-market compliance. RWE is also shown to reduce the cost and time required to produce evidence compared to traditional one-off approaches. An original example of a metric that measures the time saved by RWE methods to detect a signal of a product failure was presented based on analysis of the National Cardiovascular Disease Registry.

CONCLUSIONS

The framework presented in this manuscript offers a comprehensive approach for evaluating the value of RWE, applicable to all stakeholders engaged in leveraging RWE for healthcare decision-making. Through the proposed metrics and illustrated case studies, valuable insights are provided into the heightened efficiency, cost-effectiveness, and improved decision-making within clinical and regulatory domains facilitated by RWE. While this framework is primarily focused on medical devices, it could potentially inform the determination of RWE value in other medical products. By discerning the variations in cost, time, and data utility among various evidence-generation methods, stakeholders are empowered to invest strategically in RWE infrastructure and shape future research endeavors.

Predicting the Population Health Economic Impact of Current and New Cancer Treatments for Colorectal Cancer: A Data-Driven Whole Disease Simulation Model for Predicting the Number of Patients with Colorectal Cancer by Stage and Treatment Line in Australia

OBJECTIVES

Effective healthcare planning, resource allocation, and budgeting require accurate predictions of the number of patients needing treatment at specific cancer stages and treatment lines. The Predicting the Population Health Economic Impact of Current and New Cancer Treatments (PRIMCAT) for Colorectal Cancer (CRC) simulation model (PRIMCAT-CRC) was developed to meet this requirement for all CRC stages and relevant molecular profiles in Australia.

METHODS

Real-world data were used to estimate treatment utilization and time-to-event distributions. This populated a discrete-event simulation, projecting the number of patients receiving treatment across all disease stages and treatment lines for CRC and forecasting the number of patients likely to utilize future treatments. Illustrative analyses were undertaken, estimating treatments across disease stages and treatment lines over a 5-year period (2022-2026). We demonstrated the model's applicability through a case study introducing pembrolizumab as a first-line treatment for mismatch-repair-deficient stage IV.

RESULTS

Clinical registry data from 7163 patients informed the model. The model forecasts 15 738 incident and 2821 prevalent cases requiring treatment in 2022, rising to 15 921 and 2871, respectively, by 2026. Projections show that over 2022 to 2026, there will be a total of 116 752 treatments initiated, with 43% intended for stage IV disease. The introduction of pembrolizumab is projected for 706 patients annually, totaling 3530 individuals starting treatment with pembrolizumab over the forecasted period, without significantly altering downstream utilization of subsequent treatments.

CONCLUSIONS

PRIMCAT-CRC is a versatile tool that can be used to estimate the eligible patient populations for novel cancer therapies, thereby reducing uncertainty for policymakers in decisions to publicly reimburse new treatments.

Paving the way for patient centricity in real-world evidence (RWE): Qualitative interviews to identify considerations for wider implementation of patient-reported outcomes in RWE generation

Objectives

Real-world evidence (RWE) generation can be enhanced by including patient-reported outcomes (PROs). Methods for collecting and using PRO data in the real-world setting are currently underdeveloped and there is no international guidance specific to its use in this context. This study explored stakeholders' perspectives and needs for using PROs in RWE generation. Barriers, facilitators, and opportunities for wider use of PROs in real-world studies were also investigated.

Methods

Online semi-structured interviews were conducted with international stakeholders: patients, patient advocates, regulators, payers, clinicians, academic researchers, and industry experts. Interviews were recorded, transcribed verbatim and analysed using NVivo 20. Thematic analysis was conducted based on the updated Consolidated Framework for Implementation Research (CFIR).

Results

Twenty-three interviews were conducted. Participants confirmed that the use of PROs in RWE generation is not yet well established. Participants expressed a mixed level of confidence in the value of PROs collected in a real-world setting. Operational challenges associated with collecting routine PRO data to inform care delivery at the individual level (e.g., setting up infrastructure) need to be addressed. Methodological and other challenges (e.g., financing research) associated with collecting prospective de novo data in a real-world setting should be considered to facilitate PRO utilisation in real-world studies.

Conclusions

Several opportunities and challenges were identified regarding the broader use of PROs in RWE research. Joint efforts from different stakeholders are needed to maximise PRO implementation, with consideration given to each stakeholders' specific needs (e.g., by developing good practices).

The Real-World Evidence Workstream in EUreccA 2025: How the Task Was Addressed

This is one of a series of articles that consider the barriers to optimal use of real-world evidence (RWE) in health technology assessment (HTA) as well as ways to overcome them. The work was carried out as part of EUreccA 2025 (European Initiative for New Reimbursement and Access Approaches 2025), in particular with the RWE workstream embodied within that collaboration. The starting premises of this workstream were as follows: (1) the acceptance of RWE by HTA agencies and payers in the assessment of drugs is suboptimal and variable between jurisdictions, and (2) if that were not the case, the path of new pharmaceuticals to patients could be quicker and less expensive. Elsewhere in this issue we set out the conclusions we had reached in the EUreccA RWE workstream. In this article, we set out the methodology used to conduct the totality of the EureccA 2025 RWE workstream effort, which led us to those conclusions. The main results, strengths, and limitations of the individual parts are discussed further in separate articles in this supplement. Through scoping work, we generated 4 key topics within which to identify and address the barriers to optimal RWE use in HTA. Through pragmatic literature searches, stakeholder engagement, and case studies, we suggest ways in which the problems identified may be addressed as a contribution to progress in this area.

Structure and Content of a Taxonomy to Support the Use of Real-World Evidence by Health Technology Assessment Practitioners and Healthcare Decision Makers

This is one of a series of articles that consider the barriers to optimal use of real-world evidence (RWE) in health technology assessment and how to overcome them. The work was performed as part of EUreccA 2025, in particular with the RWE workstream embodied within that collaboration. Elsewhere in this issue we described the reasoning and process that led us to develop practical tools to support RWE use, including this taxonomy and explained the methods used to do so. The taxonomy classifies questions that are typically addressed using real-world data in health technology assessment and the data sources typically used to address these questions. In this article, we describe the taxonomy itself. For as many of the pairings as possible, we have provided links to advice and methods on how to address the associated question using those data. We have also provided links to examples of RWE use in practical decision making to answer the questions posed. Our work is not complete, but we believe it is sufficient to demonstrate the value of such a taxonomy and information source if it is completed and curated as a "wiki" by the community that would use it.