By Joel Diamond, MD, FAAP
Few advances in recent decades have the potential to change health care practice as significantly as genomics and precision medicine. Not surprisingly, oncology is proving to be the standard bearer in the charge.
In recent years, and certainly since the human genome was mapped in the early 2000s, uptake and progress in clinical practice have been swift:
- Oncologists have greater insight into disease mechanisms, which supports targeted diagnosis and treatment.
- Rather than viewing cancer as a site-specific disease, physicians now can base clinical decision-making on molecular classifications.
- These considerations allow treatment to be individualized so therapeutic benefit is achieved faster.
- Cancer specialists are equipped to prospectively evaluate risk, and likewise can detect the disease and intervene earlier.
The picture is bright and promises to get only brighter as advances in the science of genomics accelerate.
Bringing Genomics Into Workflow
Yet the industry faces one significant barrier: Bringing the value of genomic data into the oncology workflow so physicians can access and use the information at the point of care. Forward-looking health care leaders are seeking an informatics strategy as the basis for ensuring both clinicians and patients are able to leverage the full value of genomic results.
Three factors contribute significantly to this obstacle:
1. Lack of standardized nomenclature. Despite tremendous inroads made by health care IT professionals and policy makers, the industry lacks standardized nomenclature to make information meaningful and useful. Oncology itself presents its own set of challenges. Naming conventions for specific cancers vary significantly. Cancer staging is not reflected consistently across clinical IT software. Other considerations such as toxicity and disease recurrence likewise are not integrated uniformly.
Efforts to standardize genomic nomenclature are even more immature—and vocabularies around molecular immunotherapy lag further still. This is due, in part, to the rapid pace of scientific discovery. The health care industry struggles to understand terms that are already in use, while emerging vocabularies around new concepts like proteomics have yet to be undefined. While it is never easy to "issue" a medical vocabulary (consider the lingering strain surrounding the move from ICD-9 to ICD-10), the task is nevertheless critical for oncology to fully exploit genomics and precision medicine at the point of care.
2. Too much paper and too little foresight. Integrating genomic information into the EHR, where it is readily available for the clinician, is critical if oncologists are to fully benefit from precision medicine.
Right now, precision medicine is in danger of taking a giant step backwards when it comes to electronic data sharing. Incredible amounts of genomic information continue to be communicated via paper, a practice that simply is not sustainable. Obvious inefficiencies aside, paper-based documents greatly limit how the information can be accessed and how it can be leveraged. Genomic information must be shared as discrete data so it can be mined and applied across treatment and research activities, and so it can be referenced and factored as physicians follow patients longitudinally.
Oncology thought leaders increasingly talk about the value of application platforms like SMART on FHIR—and they are, without a doubt, a necessary next step. But, alone, they are insufficient in propelling the industry where it needs to go. We have likewise learned from the past that waiting for government consensus on industry IT standards requires patience. The wheels of progress turn slowly.
Instead, oncology and other specialists can achieve "speed to value" by considering a different informatics strategy, including implementation of existing vendor-neutral solutions that consume genomic data from any knowledge base or source, and deliver it directly into any EHR.
3. Data silos. Health care is in danger of building another generation of data silos around genomics, repeating the mistake made when other clinical information systems emerged. Already, some health systems are exploring disease-specific precision medicine technologies, such as those available to oncology departments. This may prove to be a shortsighted strategy, however.
Consider the disadvantages a precision oncology data silo might represent. Optimal use of genomics in the care of cancer patients is not limited to somatic data. Some cancer susceptibility is tied to germline data—clinicians may benefit from insights contained in epigenetic information as well, for example. In addition, pharmacogenomics supports better clinical decision-making by revealing how a patient might respond to specific medications (e.g., pain or anti-nausea drugs), and whether or not toxicity might be an issue. It also reveals non-cancerous comorbidities and how they are being addressed, which might impact the oncologist's recommended course of treatment.
Adaptive Clinical Trials
Bringing genomic information to the point of care via an intentional informatics infrastructure will enable oncology to make strides in other key areas as well.
Precision medicine holds the promise of dramatically changing clinical trial matching, for instance. Industry leaders are considering the fact that genomics may accelerate a move away from certain randomized clinical trials towards greater reliance upon adaptive trials. Consider the benefit to the patient—and the researcher—if matching began with biology rather than the drug.
When a treatment is intended for patients with specific markers, perhaps only those individuals should be included in the trial. The oncologist, at the point of care, can access the genomic data and refer only those patients most likely to respond to therapy. Why waste clinical resources, as well as the patient's time and possibly quality of life, if the oncologist already knows that the treatment is ineffective, based on biology? This, of course, means patient cohorts would be smaller, and researchers may also eliminate the need for control groups receiving only placebos.
Disparity around which patients do or do not receive genetic testing is rapidly becoming a point of discussion and contention among industry thought leaders. EHRs, as an example, don't enable oncologists (or any physician) to identify at-risk patients easily or effectively. Critical information—like comprehensive family history—is often limited or incomplete and, even when present, typically not stored as discrete data integrated with the workflow and appropriate decision-support tools.
The result of this information gap was perhaps best articulated by Kevin S. Hughes, MD, FACS, Co-Director of the Avon Foundation for Comprehensive Breast Evaluation at Massachusetts General in Boston, in a recent article in the Journal of Clinical Oncology (2017;35:3789-3791): "Our problem, which desperately cries out for a solution, is that huge numbers of high-risk patients who could be identified by genetic testing are instead developing cancer and often dying of that disease."
Bringing access to genomic testing into the workflow would go a long way to save lives because "out of sight, out of mind" affects physicians just like all other segments of the population. If the opportunity to consider the option of genetic testing…and the functionality to order these tests…and the ability to review the results all presented themselves at the point of care, within the workflow, oncologists and all clinicians would constantly be reminded of their option to leverage genomics.
With access to genomics at the point of care, physicians could ensure every patient for whom testing is appropriate would have access.
Few doubt that genomics and precision medicine will soon be recognized as the standard of care in oncology and other specialties. To reap its full value, however, clinicians must have meaningful access to all genomic and clinical information that could impact testing, diagnostic, and therapeutic decisions. Moreover, it must be available within the workflow and in formats that empower oncologists to leverage it to its fullest potential. To do that, we must evaluate our informatics strategy, and build a precision care platform to meet today's needs and accommodate the discoveries just over the horizon.
JOEL DIAMOND, MD, FAAP, is Adjunct Associate Professor of Biomedical Informatics at the University of Pittsburgh. He is a diplomat of the American Board of Family Practice and a fellow in the American Academy of Family Physicians. He cares for patients at Handelsman Family Practice in Pittsburgh.