Mayo Clinic uses EHRs, genetics to tailor patients’ antidepressants
Data and test results can help clinicians pick the most effective treatment, says Mark Frye, MD.
By combining an electronic health record system with genetic testing results, psychiatrists at the Mayo Clinic are able to personalize treatment for patients taking antidepressants.
The confluence of EHRs and precision medicine is proving to be a powerful tool for optimizing the prescriptions of antidepressant medication tailored to individual patients.
According to Mark Frye, MD, department chair of psychiatry and psychology at the Mayo Clinic in Rochester, Minn., there are more than 20 treatments approved by the Food and Drug Administration for depression. However, based on a patient’s genetic makeup and the way their body metabolizes medication, he contends that there can be different patient reactions to the drugs—both positive and negative.
“Clinically, some people do very well with these medicines, and sometimes they are not useful,” says Frye, a psychiatrist. “It would be a major clinical advance if we could better individualize treatments for depression and create an interface in the electronic health record that could do that efficiently.”
In particular, two major genetic tests are used to screen for pharmacokinetic metabolizing genes CYP2D6 and CYP2C19, which are enzymes that metabolize selective serotonin reuptake inhibitors (SSRI) such as Prozac. As Frye points out, there are differences in genetic variations for these two pathways, and knowing how a drug gets metabolized is very valuable information for clinicians. “We’re trying to be better and smarter about the type of antidepressants we use.”
Armed with the results of this genetic testing and an EHR, he believes physicians can now make more precise pharmacotherapy recommendations that are optimized for specific patients.
“The field of medicine is potentially changing quite significantly as it tries to accommodate new genomic research and how to interface that as best we can with electronic health records,” observes Frye. “We’ve been doing testing like this for some time now, and the other thing we’ve struggled with are EHRs, which have millions of data points, and how we can get this sort of information to the clinician where it might really be relevant—as in, they are looking to write a prescription for one of these antidepressants.”
As a physician is about to prescribe such medication, he argues that is the critical moment at which an alert could be issued through the EHR to flag in real time for the doctor the importance of genetic test results for the metabolizing genes. According to Frye, data in the hands of clinicians at the right time is crucial for helping them to make the right drug choice for their patients.
“Generating that information and having it readily available in an electronic health record interface can really facilitate decision support tools,” adds Frye. “It is currently available at Mayo in our Rochester campus. It is our own Mayo-based EHR, but we are going to Epic.”
The Mayo Clinic selected Epic to be its vendor in creating a single, integrated EHR-revenue cycle management system, replacing three EHR systems. “I would hope that this would be viewed as compatible and that we could do something similar with Epic,” he says.
Writing in the current issue of Mayo Clinic Proceeding, Frye and his colleagues discuss pharmacokinetic pharmacogenetic prescribing guidelines for antidepressants primarily metabolized by CYP2D6 and CYP2C19 as a template for psychiatric precision medicine.
“The purpose of the paper was to review the potential merits of such transformative care changes,” he concludes. “This is very early in the field, but there’s no question that genomic medicine has great potential for our practice. At the end of the day, there is not a clear set of antidepressants that have superior effectiveness for all patients, which means we need more tools to get more of a profile of the sort of person that might do well with antidepressant A versus antidepressant B.”
The confluence of EHRs and precision medicine is proving to be a powerful tool for optimizing the prescriptions of antidepressant medication tailored to individual patients.
According to Mark Frye, MD, department chair of psychiatry and psychology at the Mayo Clinic in Rochester, Minn., there are more than 20 treatments approved by the Food and Drug Administration for depression. However, based on a patient’s genetic makeup and the way their body metabolizes medication, he contends that there can be different patient reactions to the drugs—both positive and negative.
“Clinically, some people do very well with these medicines, and sometimes they are not useful,” says Frye, a psychiatrist. “It would be a major clinical advance if we could better individualize treatments for depression and create an interface in the electronic health record that could do that efficiently.” In particular, two major genetic tests are used to screen for pharmacokinetic metabolizing genes CYP2D6 and CYP2C19, which are enzymes that metabolize selective serotonin reuptake inhibitors (SSRI) such as Prozac. As Frye points out, there are differences in genetic variations for these two pathways, and knowing how a drug gets metabolized is very valuable information for clinicians. “We’re trying to be better and smarter about the type of antidepressants we use.”
Armed with the results of this genetic testing and an EHR, he believes physicians can now make more precise pharmacotherapy recommendations that are optimized for specific patients.
“The field of medicine is potentially changing quite significantly as it tries to accommodate new genomic research and how to interface that as best we can with electronic health records,” observes Frye. “We’ve been doing testing like this for some time now, and the other thing we’ve struggled with are EHRs, which have millions of data points, and how we can get this sort of information to the clinician where it might really be relevant—as in, they are looking to write a prescription for one of these antidepressants.”
As a physician is about to prescribe such medication, he argues that is the critical moment at which an alert could be issued through the EHR to flag in real time for the doctor the importance of genetic test results for the metabolizing genes. According to Frye, data in the hands of clinicians at the right time is crucial for helping them to make the right drug choice for their patients.
“Generating that information and having it readily available in an electronic health record interface can really facilitate decision support tools,” adds Frye. “It is currently available at Mayo in our Rochester campus. It is our own Mayo-based EHR, but we are going to Epic.”
The Mayo Clinic selected Epic to be its vendor in creating a single, integrated EHR-revenue cycle management system, replacing three EHR systems. “I would hope that this would be viewed as compatible and that we could do something similar with Epic,” he says.
Writing in the current issue of Mayo Clinic Proceeding, Frye and his colleagues discuss pharmacokinetic pharmacogenetic prescribing guidelines for antidepressants primarily metabolized by CYP2D6 and CYP2C19 as a template for psychiatric precision medicine.
“The purpose of the paper was to review the potential merits of such transformative care changes,” he concludes. “This is very early in the field, but there’s no question that genomic medicine has great potential for our practice. At the end of the day, there is not a clear set of antidepressants that have superior effectiveness for all patients, which means we need more tools to get more of a profile of the sort of person that might do well with antidepressant A versus antidepressant B.”
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