Drug Pricing Aggregation System for Multi-PBM Transparency
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Solution Overview
Problem
The existing system for managing pharmacy benefits does not efficiently provide consumers with transparent and comparative pricing information from multiple Pharmacy Benefit Managers (PBMs), leading to unawareness of varying drug costs and potential savings opportunities.
Innovation Solution
A system and method that aggregates drug pricing information from multiple PBMs, allowing users to compare prices across different pharmacies and generate discount coupons for lower-cost options, utilizing APIs and pricing rules to determine and display the best available prices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a system aggregates and displays drug pricing information from multiple PBMs, then consumers gain transparent pricing information and can make informed decisions, but the system complexity increases due to needing to integrate data from multiple PBMs and generate discount coupons
Solution Approach 1:
The patent merges pricing information from multiple PBMs into a single unified interface. The system aggregates data from different PBM sources and presents it in one consolidated view, allowing consumers to compare prices across PBMs without needing to navigate multiple separate systems. This combining approach resolves the contradiction by providing comprehensive pricing transparency while managing system complexity through centralized integration.
Solution Approach 2:
The system acts as an intermediary between consumers and multiple PBMs. It receives pricing data from various PBM sources, processes and standardizes the information, and presents it in a user-friendly format. This intermediary function allows the system to handle the complexity of multiple data sources while providing simple, transparent pricing information to consumers.
2Productivity
If the system provides detailed pricing information from multiple PBMs, then consumers can compare and find lower costs, but the user interface and data processing requirements become more complex
Solution Approach 1:
The system performs preliminary processing of pricing data from multiple PBMs before presenting it to consumers. It pre-aggregates, standardizes, and organizes the pricing information so that when consumers query the system, the data is already prepared and ready for comparison. This preliminary action enables efficient cost savings discovery while reducing the apparent complexity of data processing during user interaction.
Solution Approach 2:
The system automatically processes and compares pricing information from multiple PBMs without requiring manual intervention. It self-manages the data aggregation, comparison, and presentation functions, allowing consumers to simply query for pricing information and receive processed results. This self-service approach maximizes cost savings efficiency while hiding the underlying data processing complexity from users.
Data Source
AI summary
A system according to certain aspects of the disclosure provides drug pricing information from multiple PBMs to users. For example, the system may obtain, calculate, and/or estimate drug prices that are available under contracts or agreements between PBMs and various pharmacies. These prices may be prices of drugs for purchase at the various pharmacies. In response to requests for prices of particular drugs, the system can display relevant prices. For example, the system displays a price for each pharmacy chain and/or displays prices for a particular geographical area. The users can compare the prices for a particular drug and determine which pharmacy they would like to purchase the drug from. The system can provide a discount coupon that allows the users to purchase the drug at the price listed by the system at the selected pharmacy.