From Fee-for-Service Waste to Value-Based Efficiency: Rethinking Pharmacy in the VBC Era

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The shift to Value-Based Care (VBC) models represents healthcare's most significant economic transformation in decades. Yet one critical aspect remains stubbornly anchored in fee-for-service thinking: pharmacy operations.

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This blind spot creates a painful contradiction for healthcare systems and provider groups that operate under both fee-for-service and value-based payment models. The same decision that maximizes revenue under fee-for-service could significantly increase medical loss ratios under risk-based contracts.

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The Value-Based Pharmacy Paradigm Shift

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Traditional pharmacy operations focus on inventory management, dispensing efficiency, and maximizing reimbursement. Value-based pharmacy demands an entirely different approach:

• Cost optimization vs. revenue maximization: Selecting the lowest-cost, therapeutically equivalent treatment option for at-risk patients
• Site-of-service optimization: Evaluating home infusion vs. outpatient settings, based on total cost of care
• Medication adherence: Prioritizing interventions that improve adherence and reduce downstream costs
• Risk-stratified approaches: Applying different pharmacy protocols based on patient risk status
• Integrated decision support: Embedding these insights at the point of care

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One health system embracing this shift implemented a Bookend AI pharmacy operations solution that could distinguish between fee-for-service and value-based patients at the point of care, applying different optimization criteria based on risk status.

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Case Study: Same Patient, Different Economics

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Consider an actual case from this health system involving a Medicare patient requiring trastuzumab (Herceptin) treatment:

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Before Bookend AI:

• Prescribed: Ogivri (a biosimilar)
• Cost: $2,500 per treatment
• Approach: Standard treatment protocol for all patients, regardless of risk arrangement

After Bookend AI:

• Prescribed: Trazimera (a Herceptin biosimilar in the same drug class)
• Cost: $1,300 per treatment
• Approach: Bookend AI identified that the patient was attributed to a full-risk contract and recommended the clinically equivalent, lowest-cost treatment option
• Result: 48% cost reduction ($1,200 savings per infusion)

Multiplied across thousands of high-cost medication decisions annually, this type of optimization yielded projected savings of $5 million annually – with no reduction in clinical outcomes.

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Aligning with Value-Based Care Quality Metrics

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Beyond pure cost considerations, the value-based pharmacy approach directly supports key quality metrics driving VBC performance:

1. Medication adherence metrics: By selecting medications with favorable cost-sharing for patients, adherence improved 5-8%
2. Patient satisfaction scores: Reduced authorization delays and coverage issues improved patient experience measures
3. Total cost of care: Lower medication costs directly impact the most significant component of medical cost ratios
4. Hospital utilization: Fewer medication discontinuations led to reduced adverse events and hospitalizations

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Bridging the Fee-for-Service and VBC Worlds

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The optimization challenges for healthcare providers operating under both reimbursement models are especially acute. The Bookend AI solution deployed by this health system solves multiple problems at once:

• Identify patient risk status and insurance plan in real-time
• Apply tailored optimization based on full-risk or other contract status
• Display cost impact for at-risk patients, or margin impact for fee-for-service patients
• Recommend the optimal choice for each scenario

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Pharmacy as a Strategic Value-Based Care Asset

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As VBC continues to expand, pharmacy operations must quickly evolve from a tactical function to a strategic decision support role. Organizations leading in this Value-Based Pharmacy transformation are taking several key steps:

1. Data integration: Combining clinical, claims, and pharmacy data for comprehensive decision support
2. Proactive cost prediction: Flagging high-cost medication opportunities before prescribing
3. Real-time guidance: Embedding insights at the moment of prescribing
4. Learning systems: Continuously updating recommendations based on payer outcomes and changing economics
5. Patient engagement: Involving patients in shared decision making on the rationale for specific medication choices

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The Future of Value-Based Pharmacy

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This health system's experience provides a glimpse into the future of pharmacy operations in a value-based world – one where medication decisions incorporate not just clinical factors, but also economic considerations aligned with the total cost of care.

For healthcare organizations navigating the transition to value-based care, reimagining pharmacy operations represents one of the most immediate, high-impact opportunities to align clinical practice with financial incentives – and AI-powered decision support at the point of care is proving to be the key enabler of this transformation.