NOTE: This article is adapted from one appearing in the HL7 Quarterly Newsletter.
Getting radiation therapy information flowing throughout the healthcare system is crucial to effectively treating patients and ensuring coordinated, seamless care delivery. This is important because more than 50 percent of cancer patients receive radiation therapy during their treatment.
For the most part, a lack of standards has stymied efforts to easily move anything but the most rudimentary data for oncology patients.
But getting a wide range of information on radiation therapy to flow from radiation oncology information systems to those who need it is getting closer to reality thanks to the work group developing a use case supporting the exchange of radiation therapy treatment data by using mCODE™, short for the Minimal Common Oncology Data Elements, an initiative intended to assemble a core set of structured data elements for electronic health records.
The work is being pursued within CodeX, (Common Oncology Data Elements Extensions), a member-driven HL7 FHIR Accelerator, which is building a community to facilitate the development of interoperable data modeling and applications leading to improvements in cancer patient care and research.
Radiation therapy is one of the most technologically intensive treatments in medicine. Diagnosis and treatment are carried out with multiple databases and computer control in the design, analysis and delivery of safe radiation treatments. The collaboration of physicians and physicists – combining medical and technical domain knowledge – is a central element of clinical practice. That collaboration is exemplified by the partnership of the American Society for Radiation Oncology (ASTRO) and the American Association of Physicists in Medicine (AAPM) in developing clinically oriented standards supporting interoperable data exchange that is leveraged in the CodeX radiation therapy use cases.
Treatment data is often not easily transferred into EHR systems, and the use of FHIR-enabled exchange of mCODE standards could bring numerous benefits, such as enabling multi-purpose exchange of radiation treatment summary data for care coordination and data reuse. This can enhance patient care and better support data aggregation for research into oncology treatment.
Inclusion of radiation therapy information means increasing the number of standard data elements to support broader information exchange, said Jim Hayman, MD, director of the clinical division of radiation oncology for Michigan Medicine, and a clinical subject matter expert and terminologist for the CodeX work group.
Impetus for the project also came from ASTRO, the premier radiation oncology society, which led initial efforts to create a standard minimum data set for radiation therapy data; the effort was joined by other stakeholder groups.
The push for standardization of data elements is important because radiation therapy information resides in multiple information systems and historically in different formats and data structures, said Mary Feng, MD, vice chair for clinical research and professor in the Department of Radiation Oncology for the University of California – San Francisco, and co-chair for the Integrating the Health Care Enterprise-Radiation Oncology (IHE-RO) planning committee. “Exchange of information between electronic systems has been particularly challenging for our field, limiting big data efforts across oncology.”
The work on the use case for radiation therapy has required significant cross-professional communication and education, said Chuck Mayo, MD, director of radiation oncology informatics and analytics at University Hospital of Michigan Medicine and a member of the American Association of Physicists in Medicine, which is playing an important role in developing the use case.
“To actually make this work, you have to have a lot of detailed knowledge of where the data is stored, how people use them, what matters to the clinician and how to prioritize that,” Mayo said. “It’s tempting to think that all of this just happens automatically, but it takes a lot of coordinated effort.”
Standards are also vital to research, notes a recent blog by ASTRO on the radiation therapy use case. The importance of precision medicine using advanced computing, machine learning and artificial intelligence is dependent on better and easier aggregation of data, enabled by information exchange through standards-based exchange.
While the initial CodeX goal is to connect vendor information systems, the proposed interface also will eventually serve as a connection between radiation oncology information systems and other cancer data repositories, the ASTRO article notes. These improved connections “will create a pipeline of more accurate and comprehensive data summarizing a patient’s radiation treatment, increasing the power and value of these repositories.”
Larger sets from “real world” data will give researchers and clinicians better data to guide care for future patients. Experts believe that big data, the development of standard nomenclature and the ability to share data between cancer centers is important if AI is to play a role in improving the precision of treatment through radiation oncology.
In addition, mCODE-enabled data exchange can support better communication with cancer registries and payers, as well as with providers throughout the continuum of care and, importantly, back to the cancer patients themselves.
Work on the use case has progressed rapidly, primarily within the last six months, enabled by wide cooperation among large stakeholder organizations, including industry partners, Feng said. The work group already has defined and expanded the radiation therapy treatment concepts in mCode, in preparation for inclusion in the second version of mCODE Standard for Trial Use (STU2).
HL7 has been able to plug into existing work into oncology standardization, added Randi Kudner, senior manager of quality improvement for ASTRO.
The work group believes it is on track to have the standard able to generate an end-of-treatment summary that can be retrieved by another information system by year-end. In the spring of 2022, the standard is expected to be able to enable radiation oncology systems to generate radiation therapy in-progress treatment summaries that can be retrieved by another information system or health system. Eventually, the goal is to have these summaries displayed within an EHR.
The long-term goal is to have a FHIR-enabled standard that enables radiation oncology information systems to seamlessly generate and share patients' radiation therapy treatment summary information, both end-of-treatment and in-progress summary data, across health systems and providers. Clinicians then can use this readily available radiation therapy treatment summary information to make informed, impactful decisions related to a patient's health, with side benefits in supporting research and reporting requirements.
“Standardization is key to so much of what we want to do,” Mayo concluded. “Where we’ve been able to incorporate standardization in our clinical practice, we’re seeing the dividends of automation because we can make things more consistent. Standardization supports quality metrics, and where it can be applied, it becomes a real important enabling factor in improving care quality.”
“Short term our goal is better information sharing, having that information available more widely,” Hayman concurred. “Most of all, we want to learn from the data and see how we can improve what we’re doing. Without these basic standards, you can’t do any of that.”