Case Study

OptimizeRx Financial Messaging Case Study: Driving Copay Card Program Adoption

Client

Specialty Therapy

Key Results

4.4x Increased Copay Card Program Adoption

The challenge

Challenge

A leading pharmaceutical company sought to ensure eligible patients initiated therapy and improve first-fill rates for a new or access-sensitive specialty brand. The market presented significant challenges, as patients often struggled with medication affordability, leading to low utilization of existing assistance programs. Specifically for this specialty brand, the goal was to address high out-of-pocket costs and/or formulary or access challenges that could hinder patient access and adherence. A precise strategy was required to deliver financial reassurance and streamline access to support programs at critical decision points for healthcare professionals (HCPs).
High Out-of-Pocket Costs Hindered Patient Access

The solution

PLD-Targeted Financial Messaging

Delivering Prescriber-Level Data (PLD) targeted financial messages to the right prescribers. Providing copay-access specific information directly within the prescribing process. Aiming to raise awareness of patient support and reinforce prescribing decisions.

In-Workflow EHR Integration

Leveraged a robust network of Electronic Health Records (EHRs) and ePrescribing partners. Delivered targeted, brand-specific cost and coverage support information directly within HCPs' clinical workflows. Ensured messages were delivered in real-time, supporting prescribing behavior at the point of care.

Pharmacy Integration & Patient Support

Appended copay information directly to the prescription. Sent this information to the pharmacy alongside the prescription. Aimed to make pharmacists aware of copay availability at the point of purchase, intending to reduce abandonment or generic switching.

The results

Results

The OptimizeRx Financial Messaging campaign, active from February to April 2025, delivered significant positive outcomes. It successfully drove new patient acquisition into the copay program and demonstrated superior quality of engagement and more efficient conversion to new starts among exposed HCPs.

Key results

Copay Penetration Rate among new users for exposed HCPs.

9.60%

Higher Effectiveness for exposed HCPs at initiating new patients into the copay program compared to their non-exposed peers.

4.4x

New Patients among the 139 copay card users identified from exposed HCPs.

99%

Results that speak for themselves.

From rare disease to mass markets, our clients move faster, waste less, and turn coordinated marketing into measurable script lift.

Data Driven Decision-Making Drove 10:1 Return on TV Ad Spend

Learn how data-driven decision making in pharma delivered a 10:1 ROI on TV ad spend through precise targeting and omnichannel engagement.

The ad ranked in the top 25% for impressions per new prescriptions (NRx) generated.

25%

Return on Advertising Spend (ROAS) Digital Display

10:1

Audience segments ranked in the top one-third for impressions per NRx generated.

3/4

AI-Powered EHR Messaging Drives Significant Referrals for Rare Disease Treatment Referral

Discover how AI in HCP engagement improved rare disease referrals by delivering timely, EHR-based education to pediatricians and specialists.

Higher Overall Referral Rate in the test group compared to the control group.

23x

Increase in Pediatric Endocrinology Referrals in the test group versus the control group.

110x

Increase in Pediatric Genetics Referrals in the test group

~6x

Improving Audience Quality for CTV with Clinical Connected Datasets

See how OptimizeRx drove ROI in pharma CTV advertising by using clinical data and Micro-Neighborhood® targeting to improve audience quality.

OptimizeRx targeting had the best performance of all partners in both audience quality and cost per diagnosed patient

#1

Our Micro-Neighborhood® targeting platform produced higher audience quality than the national benchmark

2x

Higher audience quality rate than the next performing partner

60%

Healthcare marketing is evolving.

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