mCODE: A lingua franca for cancer data
Whilst listening to this episode from the “DISH on Health IT” podcast, I first encountered mCODE (Minimal Common Oncology Data Elements). Having worked on the collection of oncology data in Ireland. From this work I was well aware of the significant challenges in having these data in a suitable format for ease of sharing and extraction. The development of mCODE and it’s HL7 FHIR extension Codex are incredible breakthroughs and well help immensely in providing a relevant and standardised oncology dataset.
The need for mCODE: Patient Safety & Research Quality Data
Like a lot of legacy of health data pre-mCODE a lot of the patient data was and sadly still is, paper based. In the video below clinicians cite some patients having 90 page PDF documents that they have to review when the patient first presents! Sub-optimal as one clinician describes it but this still understates it. There is a patient safety issue here where some patients oncology data can be mis-represented or under-represented.
So it is anticipated mCODE will become a lingua franca for cancer allowing the sharing of patient oncology data in a standard format. Importantly it includes the minimal data required to effectively care for an oncology patient.
Another spin-off from mCODE is research. The statistics regarding cancer are horrific: According to the National Cancer Institute, in the United States, 39.5% of men and women will be diagnosed with cancer at some point during their lifetimes. In 2020, an estimated 1,806,590 new cases of cancer will be diagnosed in the United States and 606,520 people will die from the disease. The response to this is to be able to learn as much as possible from these patients. Effective research data requires effective data technologies, capture and modelling. This is where mCODE will be leveraged to bridge the current gap in the quality of these data.
What is mCODE?
Put simply, the Minimal Common Oncology Data Elements (mCODE) project is a consensus data standard created to facilitate transmission of data of patients with cancer. mCODE is being developed by a multidisciplinary group of subject-matter experts, including oncology clinicians, informaticists, health services researchers, experts in data standards and interoperability, and others under the auspices of MITRE and the American Society of Clinical Oncology (ASCO).
Since data standardisation and interoperability are at the heart of mCODE, FHIR is used to implement it. To get started there is a HL7 FHIR implementation guide here.
For me the best starting point was to look through the current data dictionary available in Excel format and work from there.
The Future
The mCODE project has the potential to offer tremendous benefits to cancer care delivery and research by creating an infrastructure to better share patient data. But its success will hinge on its adoption in the health community. Potential use-case applications that use the standard or extend it to improve care and discovery, include matching patients to clinical trials, cancer registry reporting, and facilitating the use of oncology clinical pathways. However as already discussed better cancer data interoperability stands to benefit patients the most including those being treated now and in the future.
