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MSIDE Accelarmed: Adaptive patient-centered outcome-driven coverage and benefit design for patients with complex conditions

In this post we discuss the AccelarMed analytics platform and MSIDE Smart Decisions Рproducts of MSIDE Solutions.

What others say about us

Market leaders have recognized our new AI-enabled market approach for value-based contracting in precision medicine and specialty drug market access. As an example, an article in Pharma Boardroom  outlining how AI can be leveraged to enable new drug marketing models for specialty drugs as well as to identify qualifying populations and measure cost savings and outcomes Рhas referenced our platform AccelarMed.

Outcome-driven coverage and pricing enabled by AI on combination of real world clinical and claims data and medical literature research.

“The FDA concedes that the health care community uses real-world data to support expanded coverage decisions and to develop guidelines and decision support tools for use in clinical practice.”
2021, Understanding real-world data in the real world | BioPharma Dive

To find cost, pricing, and prior authorization strategies for complex medical conditions, new approaches are needed. Static value-based models are insufficient and cannot accommodate the necessary decisions for ever-changing disease progression.

Enabled by new technologies – such as Machine Learning and generative AI companies now can find answers quickly and reliably and provide adaptive coverage throughout the patient journey, improve patient outcomes and satisfaction while preserving sustainable ROI.

Leveraging the power of AI – a combination of RWD financial analysis paired with outcome research from medical literature: 47% cost savings over 36 months for the most efficient treatment pathway discovered in real world data (RWD) accompanied by evidence for pathway effectiveness from medical literature.

As an example, MSIDE Smart Decisions AI mines real-world data from approximately 750,000 patients with rheumatoid arthritis to understand the effectiveness and efficiency of drug therapy pathways. It found that a treatment pathway involving a combination of methotrexate and sulfasalazine followed by methotrexate and etanercept had a 47% lower cost than the least cost-efficient pathway and a 34% lower cost than the most common pathway. Upon request the generative AI also found evidence from studies and articles supporting the superior effectiveness and patient outcomes of the discovered pathway, with links to supporting articles listed on PubMed.

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