top of page

The use of RWD and RWE: what do they mean for the management processes in healthcare systems?

Ana Paula Beck da Siva Etges, Eng, Ph.D

Carisi Anne Polanczyk, MD, ScD

With the increase access to technologies that allow following people's lifestyles and individual health care states, the term real-world data (RWD) started to incorporate the group of terminologies associated with the definition of populational health policies.

In the processes of health technologies assessment, the establishment of patient-centered reimbursement agreements based on outcomes and the continuous search for the adoption of RWD safely have grown globally. However, many questions are still open as it represents an innovative field, having just been the editorial theme of NEJM (1) in 2016 and, in 2017, of JAMA (2). Since its first conceptual definition, the dissemination of scientific advances and applications about the use of RWD and RWD in health care practices is happening fast worldwide give the relationship it has with advances in technologies that allow monitoring at the level of individuals, people habits and health outcomes. However, there is still difficulty understanding what the use of RWD represents and how its application to generating real-world evidence (RWE) can innovate or improve the health care system (3).

The literature converges in conceptualizing that RWD reports an individual's health state and can be generated or collected at any time along the care journey or life, whether from electronic health records, databases of administrative files, wearables, or digital applications, and any other digital source. (2) They are the primary source for generating RWE, which indicates the potential benefits or risks of health technologies (4).

With the acceleration of digital technologies availability, such as electronic records and populational databases from healthcare systems, access to RWD has become easier and cheaper, making it promising to generate evidence with agility based on the behavior of thousands of people. (3) This innovation from the use of data from multiple sources and with a granularity that demonstrates the routine of individuals is revolutionizing the accuracy of assessments, such as the pharmaceutical industry in submitting new technologies to regulatory agencies. Those processes start to have the opportunity to include data that represent the truth of the population habits and health outcomes, reducing limitations of controlled environments in developing technical reports that guide health policy decisions. Not only in the incorporation stage, but with greater intensity in the ability to monitor the real effect of technologies on the population's health status over time.

For regulatory agencies such as the Food and Drug Administration (FDA), this new era of knowledge represents an innovative and promising opportunity for the sustainability of health systems, which motivated the recent publication by the FDA of a framework to guide the use of RWD and RWE in the health technology decision-making process. (5) This document also aims to guide the regulation and control of RWD techniques in research and the management processes of health organizations.

The technologies that provide RWD generation also impact the informational access that the population has about their own health status and, consequently, their positioning in being proactive in their health care. (6) In the field of cardiovascular diseases, for example, Apple, together with Stanford University, developed the study with the highest inclusion of patients in a short period of time in history: in 9 months, 419,000 patients were part of the population of a research that aimed to assess whether the Apple Watch could be used as a technology for the identification of cardiac arrhythmia and atrial fibrillation and, consequently, be used as a tool for the early diagnosis of cardiovascular disease. (7) The results were promising: of the 0.5% of patients who received reports of heart rate irregularity, 84% confirmed a diagnosis of atrial fibrillation. When analyzing only individuals over 65 years, the percentage of irregularity notification was 3.2%. (8)

Considering the in-hospital initiatives, the concept is assessing how the implementation of digital technologies corroborates with the increment of value in health. Digital-care pathways, which include the simultaneous monitoring of patient-reported health outcomes (PROMs), which are RWD, are beginning to reach successful cases in the literature, especially in oncology and surgery. In the lung cancer care pathway, adopting a proactive monitoring routine of PROMs using digital instruments to establish a direct interaction between health professionals and patients resulted in lower mortality, emergency visits, and hospitalizations. The same study also demonstrated that physicians' perception of patients' health status differs considerably from how patients self-report. Results as these are triggers that begin to indicate the power of using RWD to execute more sustainable health policies focused on the real patients' needs. (8)

Although the positive effects reported about how the adoption of RWD and RWE affect the ability to innovate and manage health systems in a more efficient and patient-centered way, there are still several challenges to establishing RWD strategy be accepted worldwide. For a systemic and strategic transformation at a global level, it is necessary to build trust and transparency about how this evidence is being generated and what it represents in each context.

The agility and simplicity of data generation, while allowing to assess millions of people in a short period of time, can be dangerous if misused or infringing on fundamental ethical and regulatory aspects. Therefore, among the main points of challenge regarding the dissemination and acceptance of a culture of use of RWD and RWE, it is the relationship between trust, transparency, and methodological rigor. (4)

While the scientific community and the population find it difficult to trust due to the lack of methodological transparency in what is being reported , it is intrinsic to human beings to impose a barrier to the adoption of an innovation. Therefore, initiatives that support the primary awareness of the scientific community, health leaders and regulatory agencies, and, subsequently, the society, can serve as a strategic link for the establishment of a culture of RWD and RWE around global health care systems. For this purpose, the 'RWD Latam Initiative' is being launched and, throughout 2022, monthly content in written and Webinar format prepared with the purpose of translating to the context of Latin American health systems what the adoption of RWD and RWE represents to the management of health systems will be shared for free access to society.

This review marks the beginning of the program. The topics that will be addressed are listed below so that all interested parties can plan personal and team engagement in the initiative, collaborating with the innovative capacity and transformation of the local health system.

'RWD Latam Intiative'

May 2022 - The use of real-world data and real-world evidence: what do they mean for the management processes in healthcare systems?

June 2022 - Guidelines on the use of real-life data in health technology assessment

July 2022 - Existing databases in the Brazilian public (SUS) and private health care systems SUS

August 2022 - The use of wearables as an instrument for generating real-world data to manage the populational health

September 2022 - Technological and organizational challenges for adopting a culture of using real-world data in health care

October 2022 - The use of real-world evidence in the clinical practice

November 2022 - Applied project initiatives in progress in Brazil

Get involved:


An initiative promoted by Roche Produtos Farmacêuticos do Brasil.


  1. Sherman, R. E., Anderson, S. A., Dal Pan, G. J., Gray, G. W., Gross, T., Hunter, N. L., ... & Califf, R. M. (2016). Real-world evidence—what is it and what can it tell us?. New England Journal of Medicine, 375(23), 2293-2297.

  1. Jarow, J. P., LaVange, L., & Woodcock, J. (2017). Multidimensional evidence generation and FDA regulatory decision making: defining and using “real-world” data. Jama, 318(8), 703-704.

  1. Basch, E., & Schrag, D. (2019). The evolving uses of “real-world” data. Jama, 321(14), 1359-1360.

  1. Orsini, L. S., Berger, M., Crown, W., Daniel, G., Eichler, H. G., Goettsch, W., ... & Willke, R. J. (2020). Improving transparency to build trust in real-world secondary data studies for hypothesis testing—why, what, and how: recommendations and a road map from the real-world evidence transparency initiative. Value in Health, 23(9), 1128-1136.

  1. US Food & Drug Administration. Framework for FDA’s Real-World Evidence Program.

Published December 2018. Accessed March 20, 2019.

  1. Stern, A. D., Brönneke, J., Debatin, J. F., Hagen, J., Matthies, H., Patel, S., ... & Goldsack, J. C. (2022). Advancing digital health applications: priorities for innovation in real-world evidence generation. The Lancet Digital Health, 4(3), e200-e206.

  1. Turakhia, M. P., Desai, M., Hedlin, H., Rajmane, A., Talati, N., Ferris, T., ... & Perez, M. V. (2019). Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: The Apple Heart Study. American heart journal, 207, 66-75.

  1. Perez, M. V., Mahaffey, K. W., Hedlin, H., Rumsfeld, J. S., Garcia, A., Ferris, T., ... & Turakhia, M. P. (2019). Large-scale assessment of a smartwatch to identify atrial fibrillation. New England Journal of Medicine, 381(20), 1909-1917.

  1. Demedts, I., Himpe, U., Bossuyt, J., Anthoons, G., Bode, H., Bouckaert, B., ... & Verbeke, W. (2021). Clinical implementation of value based healthcare: Impact on outcomes for lung cancer patients. Lung Cancer, 162, 90-95.

69 visualizações0 comentário


bottom of page