The COVID-19 pandemic is the greatest public health crisis the U.S. has ever faced. The Duke-Margolis Center for Health Policy has marshalled its outstanding network of experts to respond to the crisis in real time, guiding Federal and state leaders through this extraordinarily difficult period. Interdisciplinary faculty and researchers from Duke University, Duke Health System and other leading health organizations are collaborating on vital, evidence-based strategies needed now to address the pandemic.

Duke-Margolis has put forward key policy steps leaders must take to respond comprehensively to the COVID-19 pandemic, to reopen the nation successfully, and create a more secure health care system. At the same time, the Center continues its vital mission to educate tomorrow’s health policy leaders, develop and analyze new data, provide timely thought leadership, and engage the greater public through outreach and education.

This is a 2-day event. You may register for Day 1 (Monday, July 13, 1:00 – 3:30 pm ET) on this page.

The Duke-Margolis Center for Health Policy, in partnership with the U.S. Food and Drug Administration, is organizing a public meeting to explore potential approaches to developing a high-quality, Real World Data (RWE) ecosystem. Discussion will consider technical challenges and cultural barriers to the scalability of data capture processes, as well as emerging practices being implemented among the stakeholder community.

The systematic collection of high-quality data is critically important to the function of health systems. While data regarding patient health status or the delivery of health care—referred to as real world data (RWD)—is primarily collected for the delivery and reimbursement of health care services, stakeholders want to use RWD for clinical research and biomedical innovation as well. This requires the collection of data that is trustworthy, consistently interpreted, and applied to support analyses for a range of evidentiary needs.

The development of the nation’s health information technology infrastructure provides new opportunities to capture diverse sources of data through routine health care delivery; however, challenges and questions regarding the reliability of this data remain. Challenges are particularly salient for the development of medical products in which data must meet fit-for-purpose requirements. Furthermore, existing RWD sources often do not adequately or consistently capture the types of health outcomes and endpoints important for research. Efforts to improve data quality presently focus on curation of datasets for real-world studies, but this is still largely a manual process that requires substantial time and resources.

Improving data capture practices at the point-of-care has the potential to improve the quality of RWD by reducing the need for data curation and permitting the collection of fit-for-purpose data that addresses key research questions. The capture of high-quality data will entail establishing an ecosystem including tools, standards, and workflows. For this ecosystem to scale, stakeholders must see the value in participation and align around common approaches for data collection. This effort might require not only enabling technical solutions, but also aligning stakeholders around a culture of high-quality data collection within and across institutions.

Funding for this meeting was made possible in part by a cooperative agreement from the U.S. Food and Drug Administration Center for Drug Evaluation and Research. The views expressed in written meeting materials or publications and by speakers and moderators do not necessarily reflect the official policies of the Department of Health and Human Services nor does mention of trade names, commercial practices, or organizations imply endorsements by the U.S. Government.

This is a 2-day event. You may register for Day 2 (Tuesday, July 14 from 1:00 – 4:30 pm ET) on this page.

The Duke-Margolis Center for Health Policy, in partnership with the U.S. Food and Drug Administration, is organizing a public meeting to explore potential approaches to developing a high-quality, Real World Data (RWE) ecosystem. Discussion will consider technical challenges and cultural barriers to the scalability of data capture processes, as well as emerging practices being implemented among the stakeholder community.

The systematic collection of high-quality data is critically important to the function of health systems. While data regarding patient health status or the delivery of health care—referred to as real world data (RWD)—is primarily collected for the delivery and reimbursement of health care services, stakeholders want to use RWD for clinical research and biomedical innovation as well. This requires the collection of data that is trustworthy, consistently interpreted, and applied to support analyses for a range of evidentiary needs.

The development of the nation’s health information technology infrastructure provides new opportunities to capture diverse sources of data through routine health care delivery; however, challenges and questions regarding the reliability of this data remain. Challenges are particularly salient for the development of medical products in which data must meet fit-for-purpose requirements. Furthermore, existing RWD sources often do not adequately or consistently capture the types of health outcomes and endpoints important for research. Efforts to improve data quality presently focus on curation of datasets for real-world studies, but this is still largely a manual process that requires substantial time and resources.

Improving data capture practices at the point-of-care has the potential to improve the quality of RWD by reducing the need for data curation and permitting the collection of fit-for-purpose data that addresses key research questions. The capture of high-quality data will entail establishing an ecosystem including tools, standards, and workflows. For this ecosystem to scale, stakeholders must see the value in participation and align around common approaches for data collection. This effort might require not only enabling technical solutions, but also aligning stakeholders around a culture of high-quality data collection within and across institutions.

Funding for this meeting was made possible in part by a cooperative agreement from the U.S. Food and Drug Administration Center for Drug Evaluation and Research. The views expressed in written meeting materials or publications and by speakers and moderators do not necessarily reflect the official policies of the Department of Health and Human Services nor does mention of trade names, commercial practices, or organizations imply endorsements by the U.S. Government.

Rachel Roiland, Mark Japinga, Elizabeth Singletary, Isha Sharma, Jonathan Gonzalez-Smith,
Gary Wang, Jeremy Jacobs, William Bleser, Robert Saunders, Mark McClellan