Guest Column | September 19, 2019

Real-World Evidence In Clinical Research: We're Not In Kansas Anymore

By Alethea Wieland, founder and president, Clinical Research Strategies, LLC


This is the first article in a two-part series addressing real-world evidence (RWE) for life sciences leaders who may be struggling to make sense of the rules.

Part one of this series is intended to give readers a glimpse into what RWE is today, with its potential to utilize staggering volumes of data, digital health technologies,1 and mobile applications. Part two  will further describe the challenges and opportunities for life sciences companies, highlight recent examples of RWE, and discuss how this newer way of thinking will transform the way we design and conduct clinical research or evaluate value-based decisions for the better. However, this Cliff Notes-style version is no substitute for reading and becoming better versed in RWE methods and regulatory trends, and more importantly, the work that lies ahead for all of us. There will be, for certain, job security in policy and law, technology, regulatory affairs and strategy, quality assurance, market access, managed care, and data science careers for the long haul.

Over the past few years, it has been difficult to ignore the numerous articles published in medical and science journals and life sciences media channels and the position statements and guidance documents on the FDA website about the new world order in clinical research and value-based payment decision-making: real-world evidence.  For those of us in healthcare or clinical research professions, we have seen this coming, due to the rising costs of our healthcare and the countless inefficiencies we encounter in the work we do, including in conformance with process norms, complex regulations, and standards groups in multiple, decoupled federal agencies. Several consolidations of large contract research organizations (CROs) in the past five years were also obvious signs.

If your head has been spinning, trying to establish where we are with the U.S. regulatory framework, development, implementation, and acceptance of RWE programs, you are not alone. You have entered the discussion at a good time, without missing too much in the background. The “reset” button was pressed emphatically a few years ago, including with the passage of the 21st Century Cures Act in late 2016.2

Where Are We Now?

Real-world data (RWD) is data relating to patient health status or the delivery of healthcare routinely collected from a variety of sources (e.g., electronic health records or EHRs, claims and billing data, registries, and digital health apps on mobile devices). Technology has enabled the collection of RWD at an unbelievable rate.  RWE, on the other hand, is the clinical evidence regarding usage and potential benefits and risks of a medical product resulting from analysis of RWD that answers specific questions.3, 4, 5

In the wake of the well-documented reproducibility problems in science,6 taxpayer waste and diminished trust in our grants system,7 epic trial failures,8, 9 renewed calls for an end of the use of P values to claim statistical significance,10, 11 and astronomical costs and time to bring a drug to market,12, 13 it seems reasonable that our salvation will come from radical change.

Now imagine for a moment you are watching Dorothy in the Wizard of Oz, when she wakes up after the tornado hits her Kansas prairie family farmhouse depicted in the simplicity of black and white cinema and then we switch to the spectacle of technicolor. Except, you realize that you are taking a tour on the set, standing next to Judy Garland. She is in a rehearsal, still memorizing her lines and going over walkthroughs with a cast of hundreds, a seamstress is adjusting her blue and white gingham dress on a mannequin, the ruby red shoes are ordered but have not yet arrived, the producers are complaining about the budget, the director is nowhere to be found, agents are demanding special treatment for their movie stars, the script writers are handwriting revisions, timelines for editing and distribution are slipping, inspectors are looking over the studio’s scaffolding for hazards, and the construction crew is building the yellow brick road that leads to the Emerald City.

This is essentially where we are with RWE: a state of tactical development with more stakeholders than one could have ever imagined, after the decision for implementation has been legislated and our attention is transfixed by the dramatically new, never going back reality, and the saturation of noise and action. It is cautiously optimistic to think we have advanced beyond crawling to the standing stage, as eloquently supported in the aptly-timed August 2019 Bipartisan Policy Center (BPC) Report, Expanding the Use of Real-World Evidence in Regulatory and Value-Based Payment Decision-Making for Drugs and Biologics,  under the leadership of former Senator William Frist, M.D., and three former FDA commissioners, Robert Califf, M.D., Ph.D., Andrew von Eschenbach, M.D., and Mark McClellan, M.D., Ph.D.14  

The BPC report makes recommendations on “clearing barriers to the access and use of real-world data to provide an evidence base for regulatory evaluation and value-based payment programs, expanding opportunities to use new data sources and approaches, and advancing new models of collaboration among payers, manufacturers, regulators, clinicians, and –most importantly– patients.”14

A summary of the 12 key policy recommendations includes:

  1. Providing for Adequate Funding – Congress should approve $60 million for a Medical Data Enterprise to evaluate effectiveness and safety of drugs, biologics and devices.
  2. Improving Regulatory Clarity – The FDA should publish guidances for supporting new indications of an existing medical product and post-approval requirements with insights gained from pilot activities and stakeholder communication.
  3. Improving Access to Data – The Department of Health and Human Services (DHHS) should prioritize: i) adoption of The Office of National Coordinator for Health Information Technology’s (ONC) 2015 Health IT Certification criterion with patient privacy at the forefront for sharing and exportation; ii) adoption of ONC’s application programming interface (API)-enabled services for all data in the U.S. Core Data for Interoperability (USCDI) using the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR); iii) collaboration on the use of HL7 FHIR by the FDA, the Centers for Medicare and Medicaid Services (CMS) and ONC to access data and protect privacy; iv) creation of and access to reliable formats for CMS Medicare beneficiary data; and v) collaboration with multiple parties and states for accessing mortality data for research and adoption of mortality-related HL7 FHIR standards.
  4. Improving Reliability and Relevance of Data – The ONC should: i) replace the Common Clinical Data Set (CCDS) with the USCDI standard with new required data classes (e.g., patient demographics, clinical notes, data provenance) for certified health IT interoperable exchange; ii) align FDA standards with the USCDI; iii) adopt real-world interoperability testing and maintenance of certification (MOC); and iv) include patient email address in the list of demographic data elements and U.S. Postal Service standards for address reference in the USCDI standard.
  5. Leveraging Technology to Gain Input Directly From Patients – The FDA should develop more guidances on the use of digital tools to support data collection from patients (e.g., wearables, biosensors, mobile technology, etc.).
  6. Expanding Efforts to Leverage Artificial Intelligence – The FDA should address artificial intelligence (AI), natural language processing, and machine learning addressed in the Sentinel Initiative Five-Year Strategy15 and disseminate lessons learned, especially to facilitate medical product development life cycles.
  7. Accelerating Pilots and Demonstration Projects – The FDA should: i) explore new data sources through pilot projects that address needs of single molecule drugs, biologics, and regenerative cell therapies; and ii) launch a CMS Demonstration Project and publish methods, outcomes, and lessons learned.
  8. Assuring Privacy and Confidentiality – Public and private sectors should: i) come together to study, deliberate, and develop a set of privacy principles that could be used across multiple settings; and ii) advance a federal data privacy framework.
  9. Advancing Innovative, New Models of Drug Development – The FDA should continue to modernize and advance innovation and create a new Office of Drug Evaluation Science.
  10. Addressing Regulatory Barriers – The DHHS should modify and expand safe harbors i) to provide clarity related to the use of value-based payment arrangements for medical products; and ii) to enable donation or cost-sharing associated with software, hardware, and related training associated with patient-reported data and outcomes to support regulatory evaluation and value-based arrangements for medical products.
  11. Expanding the CMS Workforce – Congress should add scientific and value-based payment expertise within CMS to support coverage determinations and new payment models for drugs, biologics, and medical devices.
  12. Promoting Cooperation and Collaboration – The FDA and CMS should collaborate on ways to generate evidence, including transitioning pilot programs into permanent partnerships. This is especially true for new and complex therapies and patient-generated data because expertise is scarce.

I will let you catch your breath in anticipation of the follow-up article, which will explore challenges, opportunities, recent examples of RWE, and the involvement of multiple stakeholders to propel us forward.


  1. Forbes. Top Five Digital Health Technologies in 2019. February 4, 2019.
  2. 21st Century Cures Act
  3. Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices, Guidance of Industry and Food and Drug Administration Staff (issued August 31, 2017).
  4. Framework for FDA’s Real-World Evidence Program, December 2018.
  5. Submitting Documents Using Real-World Data and Real-World Evidence to the FDA for Drugs and Biologics, Guidance for Industry (Draft, May 2019).
  6. Begley, C. G., & Ellis, L. M. (2012). Drug development: Raise standards for preclinical cancer research. Nature, 483(7391), 531.
  7. Harris, Richard. Rigor mortis: how sloppy science creates worthless cures, crushes hope, and wastes billions. Basic Books, 2017.
  8. Cummings, J. L., Morstorf, T., & Zhong, K. (2014). Alzheimer’s disease drug-development pipeline: few candidates, frequent failures. Alzheimer's research & therapy6(4), 37.
  9. Wong, C. H., Siah, K. W., & Lo, A. W. (2019). Estimation of clinical trial success rates and related parameters. Biostatistics20(2), 273-286.
  10. Amrhein, V., Greenland, S., & McShane, B. (2019). Scientists rise up against statistical significance.
  11. Wasserstein, R. L., Schirm, A. L., & Lazar, N. A. (2019). Moving to a world beyond “p< 0.05”.
  12. Moore, T. J., Zhang, H., Anderson, G., & Alexander, G. C. (2018). Estimated costs of pivotal trials for novel therapeutic agents approved by the US Food and Drug Administration, 2015-2016. JAMA internal medicine, 178(11), 1451-1457.
  13. DiMasi, J. A., Grabowski, H. G., & Hansen, R. W. (2016). Innovation in the pharmaceutical industry: new estimates of R&D costs. Journal of health economics47, 20-33.
  14. Bipartisan Policy Center. Expanding the Use of Real-World Evidence in Regulatory and Value-Based Payment Decision-Making for Drugs and Biologics, August 2019.
  15. Sentinel Initiative Five-Year Strategy

About The Author:

Alethea Wieland is founder and president of Clinical Research Strategies, LLC, an executive-level management consulting firm and boutique, functional service provider for the life sciences industry. Her firm’s solutions include analyzing the intersection of healthcare innovation and policy; providing flexible clinical trial resourcing; developing sustainable corporate affairs programs and policies; training and managing resilient, high-performing clinical operations teams; mitigating risks of clinical trials; and facilitating transparent, accountable sponsor-CRO partnerships. Learn more by connecting with her on LinkedIn and by visiting her website.