The precision medicine learning curve
The concept of applying genomics and precision medicine is gaining momentum. Physicians are enthusiastic about the potential of personalized care plans to improve patient outcomes.
But several questions remain for physicians who must put precision medicine into practice, including:
1) Who should we test?
Physicians must be able to identify which patients might benefit from genetic testing. It is important to find them early enough for testing to have its full predictive value.
2) Which test should we order?
For any given condition, there are multiple versions of genetic testing that could range from $100 to several thousand dollars. The industry must apply more rigor to this unregulated area, but in the meantime, physicians need a way to determine which tests are most appropriate.
3) Who will pay for the test?
While costs of genetic tests are decreasing, payers don’t usually cover this expense. Patients, payers and providers must weigh the long-term value of testing against the cost.
4) How do we incorporate results into the patient record?
Test results are often returned on paper or as a .pdf document. It’s not discrete data that we can easily combine and view with other clinical information.
5) How do we interpret results?
Test results are returned in wording that has been developed for genetic counselors, which doesn’t help physicians. Also, these aren’t binary answers, but rather results that include many variants with unknown significance.
Example: Applying clinical-genomic solution to address hyperlipidemia
How does this work in practice? Let’s look at the potentially genetic disorder of hyperlipidemia as an example. Hyperlipidemia is an abnormally high concentration of fats or lipids, such as cholesterol and triglycerides, in the blood. These conditions double the risk for heart disease.
According to the Centers for Disease Control and Prevention, 73.5 million adults in the United States have high levels of low-density lipoprotein (LDL), or “bad” cholesterol. About 25% of adults over 40 are taking drugs to lower their LDL (high-dose statins). Unfortunately, patients who have the inherited version of the condition will not respond to this class of drugs.
Recently a new class of drugs, called PCSK9 inhibitors, have been found to be very effective to treat this condition in the familial form. They can be expensive, so it’s important to prescribe for patients that will respond best to them.
If physicians have a clinical-genomic solution within the electronic health record (EHR) workflow, treatment plans for this condition can be much more targeted. Doctors can identify patients that might benefit from this new class of drugs, such as patients with high cholesterol levels, or who have not responded to medication to date.
The solution can then facilitate the ordering process of a genetic test, using a knowledge base to identify which test is best for that condition. Results come back in a discrete form within the workflow and can show abnormal results, LDLR gene or other unexpected genes. The solution can provide details and recommendations for that condition, putting the power of combined information at the clinician’s fingertips.