Improving Oncology Outcomes by Using Artificial Intelligence to Help HCP's Identify More Brand-Eligible Patients
See how OptimizeRx drove a 28% increase in patient starts using an AI-driven approach to HCP engagement.
CLIENT GOAL
An oncology brand had a significant positive impact on outcomes and quality of life for patients, but a limited window for initiation, and needed to increase patient starts on therapy.
THE CHALLENGE
- Very limited window to initiate treatment due to step therapy requirements.
- HCPs often became aware of treatment options after the eligibility window had ended.
- No defined test or trigger to indicate the patient was qualified for brand therapy.
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Earlier Patient Identification
Proprietary AI model detected qualified patients just before they become brand-eligible, allowing oncologists to initiate therapy before missing the treatment window.
Data-Driven Qualification
Algorithm visibility across multiple longitudinal patient datasets, including specific care settings and milestones, allowed the predictive model to identify brand-qualified patients in the absence of a single clear eligibility criteria.
Physician List Validation
Targeted approach focused brand communications on oncologists with qualified patients, allowing for more efficient messaging deployment and field teams to better prioritize HCP calls.
Point-of-Care Integration
Program introduced directly in the EHR workflow, raising awareness of patient qualification when and where providers were making treatment decisions.