Technology advances over the last decade have helped to reduce the cost of genetic testing from hundreds of thousands of dollars per exome (the protein-coding portion of genes) in 2006 to less than $1,000 today.
The lower pricing has spurred demand for new testing and today clinicians and researchers have access to more genetic test results and genomic data than ever before. Better data, along with growing interest in the potential of precision medicine and the need for insights into the health of patient populations, have set the stage for a new healthcare landscape that relies heavily on the promise of genomic medicine.
Physicians are already taking advantage of advances in genetic testing to improve the care process. For example, by identifying the presence of certain gene variants, clinicians can determine if an individual is at higher risk for certain types of cancer and if early intervention is warranted. In addition, if certain biomarkers are detected then physicians can more effectively target the use of specific medications or therapies.
While genomic medicine holds great promise for advancing healthcare, the industry must first address several barriers preventing the full integration of genomics and genetic testing into the care process. These include issues with existing healthcare IT infrastructure, the lack of interoperability, the complexity and amount of data, and concerns over privacy and data ownership.
Healthcare IT infrastructure
Healthcare's existing IT infrastructure is simply not ready to handle the science of genomics. For example, most enterprise hospital information systems lack a data field for "variant," which is the basic unit of analysis in genetics. Before providers can fully integrate the use of genomic medicine in healthcare, they must have IT infrastructures that incorporate genetic information and support communication between laboratories and EHRs.
In addition, genetic sequencing produces massively large data sets and the management of this data is well beyond the scope of existing back-end IT infrastructure. Organizations will need a new generation of systems in order to support these big data applications and provide the power to process immense volumes of data in a timely manner. They will also need sophisticated analytical tools and advanced reporting systems to disseminate information and identify the key details that impact individual patients. Advanced decision support tools are necessary to eliminate the need for physicians to filter through every variant to identify those that are pertinent to a specific patient versus variants that are non-disease causing. Adding to the challenge is our continuously evolving knowledge of variants: a variant that might have been of unknown significance yesterday could today be re-classified as disease-causing.
Interoperability
The current lack of interoperability between health IT systems hinders the full integration of patient-specific genetics data into EHRs. To maximize the potential of precision medicine, organizations must eliminate information silos and work to make patients' genetic profiles accessible at the point of care where diagnostic decisions are being made.
By incorporating genomic information into the diagnostic process, providers are able to diagnose, treat and predict disease more precisely. For example, the integration of genomic and pathology data into a single, integrated view helps physicians to narrow the cause of a patient's symptoms. Clinicians can better match patients with medications and clinical trials and avoid unnecessary, invasive and expensive testing. Treatments are better targeted and deliver care more rapidly and effectively. This can also reduce length of stays and minimize hospital admissions and re-admissions.
Privacy and data ownership
The expanded use of personal genetic information fuels new concerns and questions about who actually owns the data and who is responsible for its safekeeping. In 2013, HIPAA was amended by the Omnibus Final rule to address genetic information and offered several pathways for the use of data for research purposes. However, the rules are complicated and several exceptions apply. Most states also have genetic privacy laws that are often more stringent that federal regulations.
As more providers seek to incorporate genomics data into the care process, privacy and ownership concerns will continue to grow. At a minimum, any organization that intends to use genetic information for future research should comply with federal and state laws and obtain the informed consent of participating individuals.
Population health management: the next frontier
Healthcare's transition to value-based care models is fueling demand for better insights into the health of patient populations. Success in a value-based world requires an in-depth understanding of patients' care needs so that risk can be assessed and pro-active care strategies implemented.
The integration of genomics data with population health information would provide stakeholders with a clearer vision of the underlying health risks impacting outcomes. Populations could be more accurately stratified, allowing organizations to develop preventative care plans that are tailored to the needs of their populations. Healthcare disparities and waste would be minimized and outcomes optimized.
The healthcare industry still has work to do to ensure the full integration of genetic testing and genomic medicine into the care process and for the benefit of population health management. However, as stakeholders continue to address existing technical and operational challenges, genetic testing and genomics will, in time, become integral and essential components of the healthcare delivery process.
Matthew Hawkins is president at Sunquest Information Systems Inc., which provides laboratory information systems to more than 1700 laboratories and makes patients safer through diagnostic innovation. The company recently released Sunquest Laboratory 8.0, which features advanced functionality for integration with enterprise EHRs and blood banking administration.
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