Canadian Medication Cost Savings Associated with Combinatorial Pharmacogenomic Guidance for Psychiatric Medications
Bibliographic record
Abstract
Julie-Anne Tanner,1,2 Lisa C Brown,3 Kunbo Yu,3 James Li,3 Bryan M Dechairo4 1Neurogenetics Section, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Department of Psychiatry, Toronto, ON, Canada; 2Assurex Health Ltd., Toronto, ON, Canada; 3Assurex Health, Inc., Mason, OH, USA; 4Myriad Genetics, Inc., Salt Lake City, UT, USACorrespondence: Julie-Anne TannerNeurogenetics Section, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Department of Psychiatry, Assurex Health, Ltd., 250 College, Room R38, Toronto, ON M5T 1L8, CanadaTel +1 416 813-2745Email julie-anne.tanner@myriad.comObjective: To estimate Canadian pharmacy cost savings associated with psychiatric medication prescribing that is guided by combinatorial pharmacogenomic testing in patients switching or augmenting their psychiatric medication.Methods: Pharmacy claims data from a United States (US) pharmacy benefit manager were analyzed for 1662 patients who recently augmented or switched to a different antidepressant or antipsychotic medication and underwent combinatorial pharmacogenomic testing. Costs of prescription medications were translated to the Canadian healthcare system by matching drug names and doses using the Ontario Drug Benefit Formulary. One-year costs (2017 CAD) were compared between patients whose clinician prescribed antidepressants or antipsychotics that were consistent (congruent) or inconsistent (incongruent) with the combinatorial pharmacogenomic test recommendations.Results: Patients whose psychiatric medication treatment was congruent with the combinatorial pharmacogenomic test report saved $1061 CAD per member per year (PMPY) on prescription medication costs relative to patients whose medications were incongruent with their test report (p<0.0001). For patients ages 99% matched at the therapeutic chapter.Conclusions: Antidepressant and antipsychotic prescribing that was congruent with combinatorial pharmacogenomic test guidance was associated with significant cost savings on Canadian prescription medications according to the Ontario Drug Benefit Formulary.Keywords: pharmacogenomics, genetic test, genesight, psychiatry, mental health, prescription, pharmacy spend
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".