Almost 14 years ago today, researchers announced that the Human Genome Project had completed a high-quality sequence of essentially the entire human genome.
While the subsequent knowledge and technology has progressed at a rate previously unseen in science, many of the original challenges and opportunities still exist—many having to do with the complex ethical issues related to dealing with a potentially genetically-determined future coupled with incomplete policies regarding treatment, payment, privacy, and informed consent. Additionally, nothing has diminished the unstoppable force of consumer demand in this arena. Unfortunately, healthcare providers and policy-makers remain woefully ill-equipped to deal with the massive amounts of patient-driven and growing clinical data. There remain many obstacles to wide-spread adoption of genomics at the point of care. I would like to highlight a few of these, to show where challenges present opportunity, particularly in the field of healthcare information technology.
Cost of Genetic Testing
Despite increasing adoption of direct-to-consumer genetic testing, clinical cost of testing is often cited as a common barrier to entry, even as the prices for exome testing continue to fall dramatically. Return on investment seems quite clear in many instances, particularly in avoidance of genetically determined ineffective drugs or adverse reactions. Costs of the neonatal intensive care unit (NICU) can be significantly impacted by early diagnosis and treatment of newborn diseases. There is growing evidence that earlier detection of genetically-influenced illnesses will result in decreased morbidity and mortality (which translates to cost avoidance). An opportunity exists to develop analytic tools to accurately quantify cost-benefit. The diminishing cost of diagnostic testing will not prove, in my opinion, to be the rate-determining step in the adoption of this essential new technology.
Exchange of Genetic Information
Recapitulating an old theme in healthcare information technology; data must flow between systems in a meaningful way to be impactful. This is becoming even more evident with the emergence of this new kind of data. Consider genetic risk factors for bleeding tendency or certain anesthetic reactions found incidentally. These may only be relevant (even crucial) at the time of emergency surgery. Standards of interoperable use of genomic data is only the first step. The ability for electronic medical record systems to consume this data is a necessary first step, but much more needs to be done. A necessity to meaningfully display appropriate information where and when it is needed will create many new opportunities in the field of information technology.
Keeping Genomic Data Current
As diagnostics moves away from individual tests and panels to full exome or even full genome, providers will need to understand and deal with the huge number of incidental Variants of Unknown Significance (VUS). As science progresses and some of these variants become known, what are the technical and ethical issues involved in informing clinicians and patients of potential new risk factors? Cloud-based repositories of genomic data will be essential. Continual updates of these data sets along with tools to notify providers and patients will be crucial.
Knowledge Gaps in Genomics
Many highly competent physicians, who maintain their Continuing Medical Education requirements, continue to have knowledge gaps in the ever-expanding field of genomics. Interpretation of complicated and often ambiguous reports will require new ways of presenting and visualizing data. Clinical guidelines seem to lag behind other areas, and academic physicians are increasingly concerned by the growing use of genetic insights (particularly in pharmacogenomics) despite sufficient substantive double blind-studies. Clearly there is much to be done both in education and applied science.
Interpretation of Genetic Results
Traditionally, physicians have relied on highly trained genetic counselors to help them navigate complex reports, suggest follow-up studies and assist in communication to patients.
Unfortunately, there is a current paucity in genetic counselors, and the shortage of these specialists is increasing at a potentially alarming rate. This will place increasing demand on both primary care physicians and specialists to guide patients in interpreting genetic reports. They most certainly will demand point-of-care resources to help them order and assess genetic tests.
With an increasing burden on patient-facing clinicians, there is an opportunity to create both automated and virtual genetic counseling.
Uncovering Phenotypic Data
We will also need to contend with data derived from the much larger umbrella of omics. While well beyond the scope of this article, it includes the evolving fields of proteomics, epigenetics, viromics and the impact of the microbiome. In essence, there is much work to be done in describing phenotype as we compare it a patient's known genetic makeup. Phenotype is formally defined as the set of observable characteristics of an individual resulting from the interaction of its genotype with the environment. This will demand better tools for collecting and modeling other types of information such as family history, psychosocial factors, occupational and environmental exposures.
This an exciting time in medicine. Advances in immunotherapy and targeted genome editing such as CRISPR/Cas9 are racing forward in parallel with unprecedented commercial and consumer opportunities. The mapping of the human genome is now old news. It's time for clinicians and health care delivery systems to have the proper tools to utilize this knowledge. By defining the challenges and opportunities that exist in this evolving field of medicine, we can work together to overcome these barriers so genetic information can be integrated meaningfully into everyday practice.
Dr. Joel Diamond is the Chief Medical Officer of 2bPrecise, an EHR-agnostic, cloud-based precision medicine platform.
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