This med, not that.
Make better, safer prescription
decisions with your patients.
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Precise Prescribing Informed by Genetics, Lab Testing and Life
DecisionRx combines Medication Therapy Management (MTM), PharmacoGenomics (PGx), clinical lab data, and integrated engagement and monitoring workflows in a single platform. Integrated lab and patient data enables an optimal medication plan tailored specifically for the patient, improving clinical outcomes and lowering the overall cost of care.
Manage Medication Risk Across Your Entire Population
DecisionRx assigns Medication Risk Scores to each patient using a real-time knowledgebase of drug interactions, FDA warnings, and pharmacogenomic markers.
Improve Risk And Quantify Waste
Risk Scoring ensures that the patients most likely to benefit from a comprehensive pharmacist review are prioritized, and quantifies wasted spending associated with suboptimal medication therapy.
Real-time modeling helps pharmacists and providers tailor medication therapy plans for each patient, reducing risk of failures due to contraindications with each patient’s genetics, medical profile, and lifestyle.
Improved Medication
Adherence
Individualized prescribing increases efficacy and reduces unwanted side-effects, improving patient satisfaction and medication adherence.
Reduced Health Risk
Among the Population
The right medication at the right dose the first time reduces the risk of adverse drug reactions while improving short-and long-term patient outcomes.
Overviews and
Executive Insights
Gain real-time insights into healthcare savings through longitudinal patient risk scoring and continuous monitoring of claims.
TechPoint Product of the Year
DecisionRx was chosen as Tech Product of the Year during TechPoint’s 21st annual Mira Awards, an awards gala to honor the “Best of Tech” in Indiana.
This award recognizes the novelty of our application of data science to improve healthcare delivery at scale.
The Latest Resources
Can Pharmocogenomic Testing Improve Medication Adherence?
Poor medication adherence is a well-documented problem…