Prescribing: Reducing costs through in-class therapeutic interchange

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Abstract

Introduction: Spending on pharmaceuticals in the US reached $373.9 billion in 2014. Therapeutic interchange offers potential medication cost savings by replacing a prescribed drug for an equally efficacious therapeutic alternative. Methods: Hard-stop therapeutic interchange recommendation alerts were developed for four medication classes (HMG-CoA reductase inhibitors, serotonin receptor agonists, intranasal steroid sprays, and proton-pump inhibitors) in an electronic prescription-writing tool for outpatient prescriptions. Using prescription data from January 2012 to June 2015, the Compliance Ratio (CR) was calculated by dividing the number of prescriptions with recommended therapeutic interchange medications by the number of prescriptions with non-recommended medications to measure effectiveness. To explore potential cost savings, prescription data and medication costs were analyzed for the 45,000 Vanderbilt Employee Health Plan members. Results: For all medication classes, significant improvements were demonstrated-the CR improved (proton-pump inhibitors 2.8 to 5.32, nasal steroids 2.44 to 8.16, statins 2.06 to 5.51, and serotonin receptor agonists 0.8 to 1.52). Quarterly savings through the four therapeutic interchange interventions combined exceeded $200,000 with an estimated annual savings for the health plan of $800,000, or more than $17 per member. Conclusion: A therapeutic interchange clinical decision support tool at the point of prescribing resulted in increased compliance with recommendations for outpatient prescriptions while producing substantial cost savings to the Vanderbilt Employee Health Plan-$17.77 per member per year. Therapeutic interchange rules require rational targeting, appropriate governance, and vigilant content updates.

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APA

Stenner, S. P., Chakravarthy, R., Johnson, K. B., Miller, W. L., Olson, J., Wickizer, M., … Lehmann, C. U. (2016). Prescribing: Reducing costs through in-class therapeutic interchange. Applied Clinical Informatics, 7(4), 1168–1181. https://doi.org/10.4338/ACI-2016-09-RA-0160

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