There have been incredible advances in genomic testing over the past two decades, particularly the rapid development of next-generation sequencing (NGS). NGS is a well-established technology that relies on parallel sequencing of multiple small fragments of DNA, a process that dramatically reduces the time it takes to sequence an individual’s genome.
Genomic sequencing can identify genetic variants that may eventually lead to diseases such as cancer or Alzheimer’s or increase an individual’s risk of developing a specific disease. This valuable information can empower clinicians to take proactive measures to prevent the disease in individuals. In cases where a patient already has a disease or condition, NGS enables a precise diagnosis, thus giving clinicians better insights into the best treatment options.
NGS testing also reveals pharmacogenomic information that can tell clinicians whether a patient would have an adverse reaction to a specific drug. This not only helps avoid potentially dangerous or even fatal drug reactions, it reduces healthcare costs because patients can be put on the most appropriate and effective medication sooner.
Further, since its commercialization in 2005, the cost of NGS has followed Moore’s Law. Whereas sequencing a single human genome cost more than $10 million in 2007, the price had dropped below $600 by August 2021, making NGS viable for researchers and many individuals.
Given all the benefits of NGS for individual and population health – not to mention its potential for reducing healthcare costs associated with treating chronic diseases – one would expect NGS to be widely adopted by providers and supported by payers. Yet, due in part to lack of education and awareness, the clinical utility of genetic testing is grossly overlooked by both clinicians and the Centers for Medicare and Medicaid Services (CMS), the nation’s largest healthcare payer. Neither Medicare nor many clinicians know how to interpret and use genetic information.
This does a disservice to all healthcare disciplines in terms of exploring preventive medicine possibilities and developing clinical treatments for significantly ill patients, both of which would produce better outcomes while significantly lowering healthcare costs.
One major barrier to clinicians and payers using NGS to improve care and reduce costs is the complexity of genomic science. The underlying genetic pathways and the information around those pathways providing clues to both treatment modalities and the underlying issues are incredibly complicated. For example, researchers have identified mutations in 28 different biochemical pathways in schizophrenia patients. Some may be related to neurological development, while others may be traced to auto-immune conditions or viral attacks on the nervous system.
NGS can help clinicians solve these genetic mysteries for individual patients. Clinicians, however, want and need simple tools because they are under time constraints and pressure to treat what may be life-threatening conditions. Presented a choice between using something complicated and unfamiliar or working with the skill set for which they have invested a tremendous amount of time and effort, it’s not surprising that many clinicians will opt for the latter.
But there is real-world evidence that pharmacogenomic screening is improving health outcomes while reducing costs, both of which are essential to value-based care and beneficial to patients, providers and payers. The Kentucky Teachers Retirement Pension Fund (KTRPF) recruited members for a pharmacogenomic testing pilot to assess whether the prescription drugs they were taking were safe and appropriate to their conditions. More than 9,000 of the pension fund’s 36,315 members agreed to participate.
The screenings revealed that the pension fund’s health plan was wasting more than $1 million annually on drugs that weren’t working for members, $11 million on drugs that were prescribed in the wrong dosage and $7 million on drugs when there were better alternatives available. As a result of the NGS testing program, 64% of pension fund members tested had their medications changed to a safer or more effective drug or dosage. This led to an 11% reduction in prescription claims, a 22% reduction in hospitalizations and a 27% reduction in slips and falls (which can be caused by adverse reaction to medications).
Overall, spending by KTRPF’s health plan was down 14% over the 16 months of the pilot for members who had NGS testing. In that same period, health plan spending on members who didn’t undergo panel testing increased by 3%. Encouraged by the results, KTRPF is actively recruiting the remainder of its workforce for pharmacogenomic testing because its clinical and financial efficacy has been demonstrated.
Change comes slowly in healthcare, but the obvious and substantive benefits of NGS to patients, providers, payers and researchers should prompt vigorous efforts to educate medical school students as well as practicing clinicians about genetic testing. This includes a realistic understanding of the costs of genetic testing. A radiology test, of which thousands are ordered every day in the U.S., can cost thousands of dollars – more than the current cost of NGS testing (which continues to decline in price).
Medicare can accelerate the adoption of NGS testing by creating more codes for specific tests (such as for pulmonary disorders) that aren’t yet being covered. In January 2020, CMS announced it would cover NGS testing for types of cancer, particularly female breast and ovarian cancer. Given the huge cost to our healthcare system of non-cancer chronic illnesses such as diabetes, heart disease and Alzheimer’s, it’s clear that NGS testing that leads to prevention and early treatment could dramatically reduce healthcare spending while saving and improving lives.
Clinicians follow a set of best practices and deploy a common set of tools when treating patients. They’ll do a visual exam, check vital signs, and perhaps draw blood for some basic tests or order an image from a lab. Ideally, in the near future, genetic testing will become a regular part of a clinician’s diagnostic toolkit.
Dr. Jonathan Stein, PhD, received his doctorate in molecular and cancer genetics and holds a master’s degree in population and biomedical sciences from the University of Texas Health Science Center. He received a bachelor’s degree in biochemistry from the University of California, Santa Cruz.
This article first appeared on the website MedicalEconomics.com