Data is the Cure: Why Specialty Pharmacies Need Analytics to Thrive in 2024
To meet the rising demand for drugs to treat rare and chronic conditions, the industry’s largest players (e.g., CVS Health, Cigna, and UnitedHealth Group) have moved quickly to derive two-thirds of their prescription revenues from specialty dispensing. Health systems are following suit, rapidly launching entity-owned specialty pharmacies that enable these providers to strengthen the continuity ... Read More


To meet the rising demand for drugs to treat rare and chronic conditions, the industry’s largest players (e.g., CVS Health, Cigna, and UnitedHealth Group) have moved quickly to derive two-thirds of their prescription revenues from specialty dispensing. Health systems are following suit, rapidly launching entity-owned specialty pharmacies that enable these providers to strengthen the continuity of care they deliver to patients. As providers stake out claim in the competitive $68.3 billion specialty drug market, strategic application of data analytics to provide key fulfillment insights could be the differentiator that ensures success.
Challenges Associated with Entity-Owned Specialty Pharmacies
A fully optimized, entity-owned specialty pharmacy is a key way for health systems to improve patient care by increasing access to specialty medications and reducing the turnaround time for prescription fulfillment while at the same time generating revenue via increased script capture. However, challenges in key operational areas prevent health systems from realizing these benefits, including:
- Interoperability: As seamless data exchange remains the modern healthcare standard. Pharmacies with connectivity gaps suffer hits to patient experience and care coordination due to not having the most up-to-date information to influence patient onboarding, prescribing decisions, and patient communications.
- Claims Review: Inconsistent, or even, nonexistent claims review processes leave health systems without insight into the percentage of specialty pharmacy prescriptions filled outside of the health system and impede efforts to optimize in-network fulfillment.
- 340B Management: Inefficient 340B workflows may hinder program compliance resulting in missed discounts and increased risk of error for complex orders. Further, limited program automation inhibits auto-accumulation and real-time reporting to optimize savings capture.
Data Sources to Pinpoint Uncaptured Revenue
To create a seamless patient care experience and capture potential lost revenue stemming from the above operational challenges, claims and 340B-related data are valuable tools to highlight specialty pharmacy program pain points. While a singular claim may reveal one patient’s or physician’s preference for out-of-network dispensing, in aggregate, several hundred or even thousands of data points can highlight a trend indicating that the health systems’ specialty pharmacy resources are grossly underutilized.
Indeed, reviewing key claims metrics such as top prescribers and prescribing locations is often the first step toward quantifying prescription capture and identifying program leakage associated with lost revenue. Further, analysis of top drug volumes and value, as well as current 340B drug prices, enable health systems to identify manufacturer pricing discrepancies and excess drug expenses ensuring that 340B programs reap the most value and maximize savings.
Leveraging Data Insights for Program Optimization
With targeted data insights pinpointing program gaps and areas of weakness, health systems now have a roadmap to inform specialty pharmacy program improvement. This guidance is critical given the finite financial and talent resources most healthcare organizations have at their disposal. With a plan, health systems can prioritize the most high-reward opportunities, namely, developing intervention plans to engage specialties, physicians, and even patients whose prescriptions are consistently filled out-of-network.
For instance, investigation into the top out-of-network prescriptions may reveal that the entity-owned specialty pharmacy stocks in-demand prescriptions at lower volumes, resulting in increased time to fill. This pain point can be remedied by leveraging claims data combined with predictive analytics to better track medication inventory and forecast prescription needs, ensuring that patients can have their specialty drug needs met in-network. Additionally, analysis of prescribing locations may help determine if 340B eligible prescriptions originate from non-registered locations. In this case, immediate action includes ensuring that prescribers are charting visits from the correct location to maintain 340B eligibility requirements and recoup program savings.
Integrating Service-Based Adherence Strategies
In the long-term, the advantage of utilizing key data assets for specialty pharmacy program optimization is the opportunity to positively impact business, clinical, and patient outcomes. For example, during the intervention process to drive in-network fulfillment, analysis of claims data may reveal individual physician propensities to send prescriptions to specific out-of-network pharmacies. The reasons for these habits can then be identified and strategies enacted to shift these writing tendencies in favor of the in-house specialty pharmacy.
Claims data can also reveal changes in patient circumstances such as income, access to transportation, or family status. This knowledge enables pharmacy teams to personalize treatment plans based on each patients’ unique circumstances with the goal of maximizing medication adherence. Direct outreach and patient education initiatives can be developed to prevent medication lapses associated with increased costs of care, ultimately bolstering health system bottom line.
Future Trends: The AI Advantage
In healthcare, use cases for AI-driven models to automate manual processes, augment decision making, and predict outcomes are ever-increasing. As clinical leaders explore rules-based AI to streamline administrative tasks such as refill and inventory management for improved pharmacy outcomes overall, immediate applications for specialty pharmacy include optimizing processing for complex claims and identifying missed opportunities for 340B value and savings.
Further down the line, generative AI, which learns from historical data to generate new patterns and content, has the potential to accelerate today’s predictive analytics capabilities with advanced forecasting, such as anticipating patients’ future specialty drug needs based on their medical history and disease profiles. This capability supports proactive intervention to begin treatment regimens early on before conditions advance, ultimately reducing the patient’s need for hospitalization and lowering risk of adverse events.
Health systems that embark on an entity-owned specialty pharmacy journey garner key benefits from meeting patient needs for high-cost, high-touch medications in-network. These advantages include opportunities for more streamlined care coordination and less risk of medical error stemming from communication silos. However, to maintain these competitive advantages, health systems must tackle operational pain points within entity-owned specialty pharmacy programs that chip away at revenues and negatively impact financial sustainability.
Investment in technologies that support deep analysis of claims and 340B-related data is one key strategic measure that empowers health systems to understand how each patient interaction, prescription written, or medication dispensed contributes to overall specialty pharmacy program success and ultimately, the organization’s long-term financial and operational wellbeing.
About Matt Manning
Matt Manning is Senior Director of Operations for Health Systems at Omnicell. Matt is a seasoned leader with a proven track record in managing customer engagements, project teams, and P&L responsibilities.