Prescription Pricing Cache for Real-Time Cost Estimates
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Solution Overview
Problem
Physicians and other prescribers often lack accurate information on prescription costs, leading to difficulties in selecting cost-efficient medication options for patients, and existing systems require extensive processing and network resources to determine pricing.
Innovation Solution
A system that provides real-time pricing information to prescribers by storing prescription transactions and special prices, allowing for immediate determination of medication costs at preferred pharmacies, and reducing the need for multiple network transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing systems route numerous electronic requests to various computing entities to determine prescription pricing, then pricing information can be obtained, but processing resources, memory resources, and network resources are excessively expended
Solution Approach 1:
The system pre-calculates and stores pricing information in a cache memory before it is actually requested. When a prescriber computer requests pricing, the system checks the cache first and returns pre-computed results, avoiding the need to route numerous electronic requests to multiple computing entities in real-time. This preliminary action significantly reduces processing, memory, and network resource expenditure while maintaining pricing accuracy.
2Adaptability or versatility
If multiple transactions are routed to different entities for pricing determination, then comprehensive pricing options are evaluated, but the system complexity and resource requirements increase significantly
Solution Approach 1:
The patent combines multiple pricing determination functions into a single service provider computer that maintains a cache of pre-calculated pricing information. Instead of routing transactions to multiple separate computing entities (claims processor computers, cash discount system computers), the system consolidates these functions and provides comprehensive pricing options through one centralized cache-based solution, thereby reducing system complexity while maintaining adaptability.
Solution Approach 2:
The system creates cached copies of pricing information that can be quickly retrieved and returned to prescribers. These cached copies contain comprehensive pricing data from multiple sources (benefit plans, cash discount systems, manufacturer incentives) that are pre-computed and stored, allowing the system to provide versatile pricing options without the complexity of real-time multi-entity transactions.
3Loss of information
If real-time pricing information is provided to prescribers, then medication cost transparency is improved, but extensive network transactions and processing are required
Solution Approach 1:
The system performs preliminary calculations and stores pricing information in a cache before it is needed. When a prescriber requests pricing information, the system retrieves pre-computed data from the cache rather than performing real-time calculations across multiple entities. This allows real-time cost transparency for patients while minimizing actual processing time and network transactions at the moment of inquiry.
Data Source
AI summary
A method, apparatus and computer program product are provided for providing real-time or near real-time pricing information with improved efficiency. A special price may be returned in response to a prescription inquiry, and/or an alternative price obtained from stored prescription transactions. The prescription inquiry may be transmitted to a claims processor computer and/cash discount system in certain scenarios. If a response is not received within a time threshold, an estimated cost range may be determined. The real-time or near real-time pricing information is provided to a prescriber computer and may improve the efficiency of related systems, as well as prescription adherence by patients.