We wish to develop and test a decision support tool, TreatGx. Using genetic information (single nucleotide polymorphisms - SNPs) and patient biophysical characteristics this tool creates drug and dose recommendations.
Each year in Canada, there are approximately 200,000 severe adverse drug events, claiming 10,000 to 22,000 lives, and costing $13.7 to $17.7 billion. Physicians cannot predict whether a patient will gain the desired benefit from a prescribed medication or whether they will experience harmful side effects. Genetic tests may reduce this potential harm for many medications; however there is currently no way of incorporating genetic information into routine prescribing processes.
We see a need to pilot test a, genetic based, prescribing decision support (TreatGx) for feasibility and usability.
Five Family Physicians and one pharmacy will be invited to participate. They will be requested to identify a total of 250 adults with chronic diseases to participate in the study.
Each participant will be invited to give a saliva sample for the SNP test. This sample will be sent to the laboratory for genetic testing; whole genome testing is not being undertaken. We have identified from published evidence a small panel of SNPs that will give information to guide prescribing. A genetic report will be fed back into the family physician's or pharmacist's electronic health record. The electronic health record will be linked to TreatGx; the next time the participant is seen by the family physician/pharmacist prescribing recommendations will be available for use. The family physician will be able to use TreatGx to give the participant a prescription that is personalized.
We will track how many times the system is used, gain feedback on usability, record timing between receiving samples, time to the laboratory, time to analysis, and time to electronic record.