The mission is to increase awareness, understanding, and implementation of real-world evidence (RWE) with all stakeholders, policy makers, regulators, payers, prescribers, patients and industry to improve decision making benefiting patients.


  • Promote dialogue on RWE, thereby increasing awareness and understanding of how RWE can be utilized to support healthcare decision making.
  • Help develop RWE-specific educational opportunities for ISPOR members.
  • Support ISPOR task force activities addressing RWE and aligned topics, particularly the development of new good practice guidelines; improving the quality of RWE generation has positive implications such as improving the quality of economic models that rely on RWE to inform various model parameters.
  • Encourage adherence to existing methodological good practices thereby increasing stakeholder trust in the RWE generated by ISPOR members; consequently, increasing trust in and acceptance of economic models relying on RWE tools: technology, core data models.


The use of real-world evidence (RWE) is not a new concept. For several decades, RWE has been used mainly by regulators to answer safety questions, and to some extent (comparative effectiveness) by HTA bodies and payers. However, there is growing interest in regulatory use of randomized pragmatic trials and non-interventional RWE studies of comparative effectiveness and safety. Other stakeholders also increasingly describe a growing interest in using real world data (RWD) sources to inform their decision-making, recognizing that RWE is a strong complement to RCTs. The analysis of RWD provides the opportunity to systematically evaluate the use, benefits and risks of medical products in more clinically diverse settings and patient groups, under conditions that reflect the use of treatments in actual clinical practice. Recognizing the advantages presented by RWE to evaluate longer-term outcomes, safety, and quality of care, large-scale investments in RWD infrastructure, such as Sentinel, PCORnet and IMI-EDHEN are under way. 

Despite the focus on and hopes for RWE, stakeholders remain cautious as they evaluate how much they can trust RWE, especially in effectiveness assessments. Historically, there have been concerns regarding discrepancies between RWE and randomized trial evidence, known as the “efficacy-effectiveness” gap [1]. This is also closely related to conflicting results that can be sometimes observed, coming from different studies, data sources, and methods. More specifically, one of the hurdles is linked to the lack of randomization and the risk of bias inherent to all observational (non-randomized) studies. That said, advances in methods such as high-dimensional propensity score adjustment have been shown to improved effect estimates compared [2]. Another critical hurdle is the quality of the RWD which are used to derive RWE; this includes data accuracy and completeness. Additionally, the generalizability of the results, also linked to the representativeness of the real-world population assessed, may be a hurdle. Lastly, transparency is a critical point to ensure robust RWE. 

Over the years, ISPOR members have taken on a leadership role in improving RWD methodologies, its relevance, and the uptake of RWE across the healthcare ecosystem [3]. For example, ISPOR established a joint task force with the International Society for Pharmacoepidemiology on RWE [4,5] and recently provided comments on the FDA’s framework [6].  Numerous Good Practices for Outcomes Research published by the society relate to RWD and RWE.


  1. Nordon C, Karcher H, Groenwold RHH, et al. The “Efficacy-Effectiveness Gap”: Historical Background and Current Conceptualization. Value Health. 2016;19(1):75-81. doi:10.1016/j.jval.2015.09.2938
  2. Schneeweiss S, Rassen JA, Glynn RJ, et al. High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology. 2009 Jul;20(4):512-22. doi: 10.1097/EDE.0b013e3181a663cc.
  3. Makady A, Ham RT, de Boer A, et al. Policies for Use of Real-World Data in Health Technology Assessment (HTA): A Comparative Study of Six HTA Agencies. Value Health. 2017;20(4):520-532. doi:10.1016/j.jval.2016.12.003
  4. 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. Pharmacoepidemiol Drug Saf. 2017;26(9):1033-1039. doi:10.1002/pds.4297
  5. Shirley V. Wang, SV, Schneeweiss, S, Berger, ML, et al. Reporting to Improve Reproducibility and Facilitate Validity Assessment for Healthcare Database Studies. Value Health 2017; 20:1009-22.
  6. Berg N. ISPOR Comment Letter on the Framework for the FDA’s Real-World Evidence Program (Docket No. FDA-018-N-4000). https://www.ispor.org/docs/default-source/strategic-initiatives/final-response-to-fda-rwe-framework-fda-2018-n-4000.pdf?sfvrsn=a8ddeffb_2. Accessed April 5, 2019.



    Leanne Larson, MHA, BS

    Principal, ZS Associates
    Wilmette, IL, United States


    Ashley Jaksa, BA, MPH

    Boston, MA, United States

    Past Chair

    Lucinda Orsini, MPH

    VP, Value and Outcomes Research, COMPASS Pathways
    Skillman, NJ, United States

    Working Groups:

    Member Engagement


    Sandipan Bhattacharjee, MS, PhD

    Director Real World Evidence (RWE) Leader Oncology, Bayer U.S. LLC
    Belle Mead, NJ, United States

    Kaustuv Bhattacharya, MS

    Assistant Professor, University of Mississippi, Department of Pharmacy Administration
    University, MS, United States

    Doug Foster

    Partner, Advanced Data Sciences LLC
    SAN FRANCISCO, CA, United States

    Kimberly Glenn

    Principal, Herspiegel
    Nolensville, PA, United States

    Phani Veeranki, DrPH, MD, MPH

    Director, Optum Life Sciences
    CYPRESS, TX, United States
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