A framework to guide the optimal development and use of real-world evidence for drug coverage and formulary decisions
Abstract
Aim: To provide a framework for optimizing the development and use of real-world evidence (RWE) in drug coverage decisions. Materials & methods: The Institute for Clinical and Economic Review convened a Policy Summit with representatives from 23 payer and life science companies that compose the Institute for Clinical and Economic Review membership. Results: Summit participants helped refine a new conceptual framework that emphasizes the central role of contextual considerations and the evidentiary argument that the RWE is intended to support in designing the process for the development and interpretation of RWE. Conclusion: This framework may provide a structured way for pharmaceutical manufacturers and payers to develop a shared understanding of the best way to develop RWE that will ultimately be useful in informing coverage and formulary decisions.
Supplementary Material
File (supplementary_table.docx)
- Download
- 47.67 KB
References
Papers of special note have been highlighted as: • of interest; •• of considerable interest
1.
Garrison L, Neumann P, Erickson P, Marshall D, Mullins D. Using real-world data for coverage and payment decisions: the ISPOR Real-World Data Task Force Report. Value Health 10(5), 326–335 (2007).
2.
Malone DC, Brown M, Hurwitz JT, Peters L, Graff JS. Real-world evidence: useful in the real world of US payer decision making? How? When? And what studies? Value Health 21(3), 326–333 (2018).
• Illustrates how certain payers are using real-world evidence (RWE), and discusses the limitations of relevance, timeliness and transparency.
3.
Massachusetts Institute of Technology. MIT NEWDIGS Hosts Design Lab on Efficacy to Effectiveness (E2E) data and decision-making. https://newdigs.mit.edu/news/mit-newdigs-hosts-design-lab-efficacy-effectiveness-e2e-data-and-decision-making.
4.
Patient-Centered Outcomes Research Institute. The Aspirin Study. http://theaspirinstudy.org/.
5.
Center for Medical Technology Policy. Real-World Evidence Initiative Report. www.cmtpnet.org/green-park-collaborative/published-recommendations/real-world-evidence.
6.
Duke-Margolis Center for Health Policy. Real-World Evidence Collaborative. https://healthpolicy.duke.edu/real-world-evidence-collaborative.
7.
Wang SV, Schneeweiss S, Berger ML et al. Reporting to improve reproducibility and facilitate validity assessment for healthcare database studies V1.0. Value Health 20(8), 1009–1022 (2017).
• Provides a catalog of parameters and items that should be adequately described to ensure transparency in the reporting of RWE studies.
8.
Berger ML, Sox H, Willke RJ et al. Good practices for real-world data studies of treatment and/or comparative effectiveness: recommendations from the joint ISPOR-ISPE Special Task Force on real-world evidence in health care decision making. Value Health 20(8), 1003–1008 (2017).
• Recommends best procedural practices to follow when developing RWE and complements the paper above by Wang and colleagues.
9.
Carrao G. Building reliable evidence from real-world data: methods, cautiousness and recommendations. Epidemiology, Biostatistics and Public Health 10(3), e8981:8981–e8981:8940 (2013).
10.
Hampson G, Towse A, Dreitlein B, Henshall C, Pearson S. Real-world evidence for coverage decisions: opportunities and challenges – a report from the 2017 ICER Membership Policy Summit. J. Comp. Eff. Res. (In Press) (2018).
11.
Hampson G, Towse A, Dreitlein B, Henshall C, Pearson S. Real-world evidence for coverage decisions: opportunities and challenges – a report from the 2017 ICER Membership Policy Summit. March (2018). https://icer-review.org/wp-content/uploads/2018/03/ICER-Real-World-Evidence-White-Paper-03282018.pdf.
•• Full description of the Institute for Clinical and Economic Review Policy Summit on RWE with deeper discussions of the challenges and opportunities of using RWE for coverage and formulary decisions.
12.
Matchar DB. Chapter 1: Introduction to the methods guide for medical test reviews. J. Gen. Intern. Med. 27(1), 4–10 (2012).
•• Describes in detail the PICOTS (Patients, Intervention, Comparators, Outcomes, Time horizon and Setting) approach to framing a research question.
13.
Peterson AM, Nau DP, Cramer JA, Benner J, Gwadry-Sridhar F, Nichol M. A checklist for medication compliance and persistence studies using retrospective databases. Value Health 10(1), 3–12 (2007).
14.
Cramer JA, Roy A, Burrell A et al. Medication compliance and persistence: terminology and definitions. Value Health 11(1), 44–47 (2008).
15.
Hess LM, Raebel MA, Conner DA, Malone DC. Measurement of adherence in pharmacy administrative databases: a proposal for standard definitions and preferred measures. Ann. Pharmacother. 40(7–8), 1280–1288 (2006).
16.
Pharmacy Quality Alliance. PQA performance measures. https://pqaalliance.org/measures/default.asp.
17.
International Society for Pharmacoeconomics and Outcomes Research. ISPOR tools for outcomes researchers. www.ispor.org/research/research_index.asp.
18.
Academy of Managed Care Pharmacy. www.amcp.org.
19.
United States Department of Health and Human Services. 42 CFR Parts 402 and 403 Medicare, Medicaid, Children's Health Insurance Programs; Transparency Reports and Reporting of Physician Ownership or Investment Interests; Final Rule. Federal Register 78(27), 9457–9528 (2013).
Information & Authors
Information
Published In
Copyright
© 2018 ICER & OHE.
History
Received: 28 June 2018
Accepted: 14 September 2018
Published online: 14 November 2018
Keywords:
Topics
Authors
Metrics & Citations
Metrics
Article Usage
Article usage data only available from February 2023. Historical article usage data, showing the number of article downloads, is available upon request.
Citations
How to Cite
A framework to guide the optimal development and use of real-world evidence for drug coverage and formulary decisions. (2018) Journal of Comparative Effectiveness Research. DOI: 10.2217/cer-2018-0059
Export citation
Select the citation format you wish to export for this article or chapter.
Citing Literature
- Katharine Cresswell, Ravinder Claire, Laila Issa, Luke Kubehl, Omnia Bilal, Rose Purcell, Amaya Clemente, Jakob Wested, Lotte Groth Jensen, Medha Sasane, Rita Peeters, Bethany Shinkins, Heather Colvin, Best Practices and Gaps in Current Regulatory and Health Technology Assessment Real‐World Evidence Policies for Medicines and Medical Devices: Current State of Play and Next Steps, Clinical and Translational Science, 10.1111/cts.70507, 19, 3, (2026).
- Lisa Masucci, Diedron Lewis, Jiahao Zhao, Caitlin Carter, Kelvin K.W. Chan, William W.L. Wong, The use of real-world evidence among healthcare payers: a scoping review, International Journal of Technology Assessment in Health Care, 10.1017/S0266462325100445, 41, 1, (2025).
- Sean Khozin, Nancy A. Dreyer, Dominic Galante, Raymond Liu, Peter Neumann, Nathan Nussbaum, Joyce O’Shaughnessy, Debra Patt, Mothaffar Rimawi, Hope Rugo, Sara M. Tolaney, Marisa Weiss, Adam Brufsky, Real-World Evidence Acceptability and Use in Breast Cancer Treatment Decision-Making in the United States: Call-to-Action from a Multidisciplinary Think Tank, Advances in Therapy, 10.1007/s12325-025-03201-y, 42, 7, (2973-2987), (2025).
- William H. Olson, Ibrahim Turkoz, Up-front matching: an ongoing recruitment method for prospective observational studies that mimics randomization for selected baseline covariates, Journal of Biopharmaceutical Statistics, 10.1080/10543406.2024.2373436, 35, 4, (697-710), (2024).
- Pavel Goriacko, Ari Moskowitz, Nadia Ferguson, Saira Khalique, Una Hopkins, Nicholas Quinn, Mark Sinnett, Eran Bellin, Medication use evaluation of tocilizumab implementation in COVID-19 treatment guidelines: A causal inference approach, American Journal of Health-System Pharmacy, 10.1093/ajhp/zxae161, 81, 21, (e700-e710), (2024).
- Konstantinos Zisis, Elpida Pavi, Mary Geitona, Kostas Athanasakis, Real-world data: a comprehensive literature review on the barriers, challenges, and opportunities associated with their inclusion in the health technology assessment process, Journal of Pharmacy & Pharmaceutical Sciences, 10.3389/jpps.2024.12302, 27, (2024).
- Linda A. Murphy, Ron Akehurst, Oriol Solà-Morales, David Cunningham, Jorge Mestre-Ferrandiz, Matthew Franklin, Gérard de Pouvourville, Structure and Content of a Taxonomy to Support the Use of Real-World Evidence by Health Technology Assessment Practitioners and Healthcare Decision Makers, Value in Health, 10.1016/j.jval.2023.01.007, 26, 4, (20-31), (2023).
- Leticia R Moczygemba, Carolyn Brown, Michael Johnsrud, “It’s Time to Represent”: shifting the paradigm to improve the quality of inputs into value assessment frameworks, Journal of Managed Care & Specialty Pharmacy, 10.18553/jmcp.2021.27.9-a.s19, 27, 9-a Suppl, (S19-S23), (2021).
- Leticia R Moczygemba, Carolyn Brown, Michael Johnsrud, “It’s Time to Represent”: shifting the paradigm to improve the quality of inputs into value assessment frameworks, Journal of Managed Care & Specialty Pharmacy, 10.18553/jmcp.2021.27.9-a.s17, 27, 9-a Suppl, (S17-S21), (2021).
- Karen M. Facey, Piia Rannanheimo, Laura Batchelor, Marine Borchardt, Jo de Cock, Real-world evidence to support Payer/HTA decisions about highly innovative technologies in the EU—actions for stakeholders, International Journal of Technology Assessment in Health Care, 10.1017/S026646232000063X, 36, 4, (459-468), (2020).
