OSTP and ONC Seek Input on Optimizing Data Capture for Clinical Trials
By Micky Tripathi, National Coordinator, ONC, Jennifer Roberts, Assistant Director for Health Technologies, & Grail Sipes, Assistant Director for Biomedical Regulatory Policy, White House Office of Science and Technology Policy
Micky’s Twitter: @mickytripathi1
This blog post is co-authored with Jennifer Roberts, Assistant Director for Health Technologies, White House Office of Science and Technology Policy, and Grail Sipes, Assistant Director for Biomedical Regulatory Policy, White House Office of Science and Technology Policy.
The COVID-19 pandemic demonstrated the need for a coordinated clinical trials enterprise, one that can swiftly characterize emerging viral threats and evaluate the effectiveness of vaccines, therapeutics, and other countermeasures across a diversity of trial participants. In response, the Biden-Harris Administration released the National Biodefense Strategy, which calls for a U.S. clinical trials infrastructure “ready to administer candidate countermeasures to participants within 14 days after the identification of a viable countermeasure.” In support of this effort, the White House Office of Science & Technology Policy (OSTP), in coordination with the National Security Council, issued a Request for Information (RFI) on October 26 seeking input from the public about how a coordinated clinical research system can be deployed in the event of an emerging disease outbreak.
A key component in building U.S. capacity for clinical research – both during a public health threat and at other times – is ensuring that trial data can be captured as a set of consistent data elements across separate trial sites under a coordinated clinical trial protocol. Currently, researchers must analyze different datasets, developed under different research protocols, stored in different formats, in data repositories that are often not accessible to all participants. This delays the development of evidence. When time is of the essence, dataset incompatibility can become an unacceptable obstacle, inconsistent with our goal of rapid pandemic preparedness and biodefense.
On October 28, OSTP issued a second RFI related to the innovative clinical trials goal of the National Biodefense Strategy. This RFI was prepared in partnership with the Office of the National Coordinator for Health Information Technology (ONC) and is entitled “Data Collection for Emergency Clinical Trials and Interoperability Pilot.”
In this RFI, OSTP and ONC seek input on how best to operationalize clinical trial data capture and protocol distribution from a technical perspective within the current health care and research data ecosystem. We want to know what opportunities technology can offer to create the data infrastructure needed to support a coordinated clinical research enterprise that can be activated when a health threat arises. What are some of the technical solutions currently available? What technical solutions need to be developed for seamless, secure, and efficient data capture, so that we can respond as quickly as possible to the next virus?
The RFI lays out a multi-step use case, detailing the process for commenters to consider, from the creation of a clinical trial protocol through the transmission of data via common application programming interfaces (APIs). Specifically, we seek input on viable technical strategies to distribute clinical trial protocols and to capture clinical trial data using Health Level 7 (HL7®) Fast Healthcare Interoperability Resources (FHIR®)-based APIs, in both the pre-emergency phase and the emergency phase. The use of common APIs to distribute protocol requirements and to capture clinical trial data will allow health organizations across the country to communicate quickly and effectively. This will allow institutions to more rapidly understand a virus and to test new and repurposed vaccines and medicines, even when research is conducted across different kinds of healthcare and research settings with different electronic health record and research data systems.
We know that innovators have begun to develop technical strategies to improve data capture in clinical trials. One driver of this innovation has been ONC’s work to establish a regulatory and governance foundation for the interoperability of electronic health records (EHRs). Among other initiatives, ONC is currently supporting the development of the United States Core Data for Interoperability (USCDI) standard; FHIR APIs; and Substitutable Medical Applications and Reusable Technologies (SMART) platforms that are compatible with FHIR interfaces, giving rise to “SMART on FHIR” APIs.
The challenge now is to develop strategies for electronic capture of clinical trial data that can be used by unrelated institutions and study sites that participate in the same clinical trial. These strategies must be deployed in both the emergent and non-emergent settings.
We believe it is time for a demonstration project of such a system, with an emphasis on sites in underserved communities. This is part of a larger goal of strengthening the overall clinical trials infrastructure and making clinical research opportunities available to all Americans.
Key organizations, including in the private sector, have already made great strides towards adoption of ONC’s certification requirements. Certified health information technology (health IT) developers are working to meet various ONC certification criteria. For example, by December 31, certain developers of certified health IT are required to update and provide to their customers certified API technology capable of FHIR-based patient and population services.
This is in addition to ONC’s work in establishing the Trusted Exchange Framework and Common Agreement (TEFCA), with the goal of establishing a universal floor for the secure and responsible sharing of basic clinical information between health networks (see www.HealthIT.gov/TEFCA).
We hope that the feedback received on this RFI will uncover further opportunities for innovation, engagement, and action towards optimizing structured data capture for clinical research.
This article was originally published on the Health IT Buzz and is syndicated here with permission.