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This study is being done to better understand how genetic information related to drug dosing and use can affect medical care of patients. By doing this study, the investigators are developing and improving ways to incorporate information about drug related genetic variants into the medical record.
The purpose of this research is to initiate a test of the concept that sequence information can be coupled to electronic medical records (EMRs) for use in healthcare.The focus of this study is on pharmacogenomics, given the role of adverse drug reactions (ADRs) as major causes of morbidity and mortality, the increasing number of recognized variants included in FDA labels as mediators of both efficacy and toxicity, and the relative lack of stigma attached to carriers of variants in "pharmacogenes". Preemptive sequencing of patients interrogates large numbers of PGx variants and integrates clinically actionable results in a patient's electronic health record (EHR) for use by clinicians at the point-of-care. It is unknown, however, whether integration of preemptive PGx data into the EHR will significantly improve patient outcomes and reduce healthcare costs. Therefore, the Right Drug, Right Dose, Right Time Using Genomic Data to Individualize Treatment Protocol (RIGHT Protocol) study was designed to recruit a large group of patients for preemptive PGx testing, to develop the EHR infrastructure to deliver clinical decision support in real time, and to study the effects of integrating preemptive PGx testing into clinical practice on patient outcomes.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Primary cohort | Other | All eligible Biobank participants that receive the majority of their care at Mayo Clinic based on EHR length and depth had pharmacogenomic testing done. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Pharmacogenomic testing | Diagnostic Test | A comprehensive PGx interpretive report created by OneOme (www.oneome.com) provides information on how an individual patient's genes may affect medication response. OneOme utilizes algorithms and curated clinical PGx knowledge to generate a highly intuitive personalized report based on a patient's genomic results. |
| Measure | Description | Time Frame |
|---|---|---|
| Study Participants - Total number of subjects identified with high risk for being prescribed a PGx drug | Total number of subjects identified with high risk for being prescribed a PGx drug | Baseline |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Suzette Bielinski, PhD | Mayo Clinic | Principal Investigator |
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| Label | URL |
|---|---|
| Mayo Clinic Clinical Trials | View source |
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| ID | Term |
|---|---|
| D000071185 | Pharmacogenomic Testing |
| ID | Term |
|---|---|
| D005820 | Genetic Testing |
| D019411 | Clinical Laboratory Techniques |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
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The Mayo Clinic Biobank is an institutional resource comprised of adult community volunteers who donated biological specimens, provided risk factor data, access to EHR data, and consented to participate in additional studies. Subjects in the Mayo Clinic Biobank are the cohort that was recruited to participate in the RIGHT study.
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|
| D008919 | Investigative Techniques |
| D005821 | Genetic Techniques |
| D033142 | Genetic Services |
| D006296 | Health Services |
| D005159 | Health Care Facilities Workforce and Services |
| D003954 | Diagnostic Services |
| D011314 | Preventive Health Services |