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Informatics Supports Adoption Of Genetics And Genomics Across Clinical Areas

Contributed Commentary By Joel Diamond

March 19, 2020 | Advances in genetic and genomic science have benefited cancer care for decades, both in pinpointing precise diagnoses and identifying effective targeted therapies.

Progress in precision oncology has come primarily in two specific areas. First has been the development of molecular tests for tumor tissue, which has a genetic profile all its own (distinct from the patient’s native genetic makeup). This has enabled researchers and clinicians to abandon the practice of focusing on the anatomical site where the cancer occurs and instead treating the molecular characteristics of the disease no matter where it manifests. Secondly, germline testing—the “normal” genetic profile—can identify whether or not a patient is at elevated risk for specific cancers. For instance, presence of BRCA1 or 2 mutations might indicate risk for breast and ovarian cancer, prompting early and aggressive prevention, screening and diagnostic activities.

As interest in and awareness of precision medicine sweeps the industry, healthcare leaders are applying the principals of precision oncology to other clinical areas—to great effect. For example, cardiologists treating patients for congestive heart failure (CHF) have the opportunity to improve care quality and outcomes by leveraging genetic testing to determine if the patient exhibits mutations associated with dilated cardiomyopathy. A more precise diagnosis such as this will have significant impact on clinical decision-making and treatment—and may spell the difference between life and death for the CHF patient. Similarly, physicians treating patients for high cholesterol can use genetic testing to identify variations associated with familial hypercholesterolemia (FH). This is especially critical in patients not responding to standard cholesterol medications, as a precise FH diagnosis would require a modified care plan.

Testing available for 2,000 conditions

According to the National Institutes of Health, genetic tests are available for more than 2,000 common and rare diseases. Increasingly, healthcare providers are leveraging genetics to screen and diagnose patients across clinical specialties—inclusive of all age groups, including prenatal and newborn testing. However, this rapid growth has illuminated a critical vulnerability for provider organizations.

  • Few health systems have created actionable clinical-genomic workflows that allow this critical data to be accessed at the point of care, within the EHR environment, for use in medical decision-making.
  • Because testing is happening in isolated pockets across organizations, resulting data is not being ingested, stored, or managed effectively. In fact, some healthcare leaders are not even aware of which departments and providers are doing genetic/genomic testing.
  • In the absence of an enterprise-wise precision medicine strategy, organizations are not getting the full value from results of tests performed. A patient’s germline information rarely changes over the course of his or her lifetime. That means that test results can be re-interrogated multiple times by multiple providers for years into the future. Unlike other lab data, such as a complete blood count (CBC), results from a single germline test serve as a long-term resource.

Healthcare organizations at the forefront of precision medicine have recognized the importance of an IT infrastructure to facilitate success. While instinct might cause leaders to assume their EHRs will serve this function, that calculation is faulty. EHRs were not developed to ingest genomic data discretely, nor translate the specialized vocabulary used by molecular labs into common clinical language. In addition, to optimize utilization of genetic and genomic information across an entire health system, EHRs would need to ingest data from, and subsequently make it available to, multiple software systems regardless of vendor. This is not currently possible, given lack of standardization and interoperability gaps across various EHRs.

Informatics layer enhances utilization of genomic insights

Instead, the most effective approach might be to add an informatics layer on top of existing clinical systems, so providers across specialties and care settings can have fingertip access to the data. If presented within the patient context, it then becomes a timely and insightful resource at the point of care.

Treatment of genetic and genomic data in this manner offers one additional advantage. There is no doubt that science will continue to advance at a dizzying pace, and new discoveries will need to be applied to the existing genetic/genomic data set. An agile informatics platform, preferably cloud-based, can deliver one-click access to the latest clinical evidence and guidelines. Further, scientists and clinical researchers anticipate that new categories of data (beyond what we today label as “genomics”) will be available soon, including transcriptomics, proteomics or metabolomics. Healthcare leaders instituting a precision medicine program today must ensure the infrastructure and processes they implement will serve as a foundation for future opportunities.

There is little doubt that precision medicine will soon become the new standard of care and will have a transformative impact on both diagnostic and therapeutic decisions. An enterprise approach will enable health care systems to ensure they are providing patients the best care possible, while equipping clinical teams with insights to make optimal decisions.

Joel Diamond, MD, FAAFP, is an 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 and serves as Chief Medical Officer for 2bPrecise. He can be reached at

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