Drug Alternative Ranking System with Clinical Filtering
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Solution Overview
Problem
The complexity of determining costs for prescription drugs makes it difficult for patients and physicians to make sound economic choices without sacrificing therapeutic efficacy, as they lack access to comprehensive cost and efficacy information for drug alternatives.
Innovation Solution
A system and method that processes drug alternatives by receiving a selection, generating a list with price data, ranking options by price, suppressing non-clinically effective alternatives, and filtering by parameters, providing improved formulary and benefit information to prescribers and payers, including real-time prescription benefit checks and patient-specific copay information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive cost and efficacy information for multiple drug alternatives is provided, then patients and physicians can make better economic choices, but the system complexity and data processing requirements increase significantly
Solution Approach 1:
The system segments drug alternatives into hierarchical groups (therapeutic classes, subclasses, and individual drugs) to manage complexity. This segmentation allows comprehensive information to be organized in manageable sections, making it accessible without overwhelming the system or users.
Solution Approach 2:
The system introduces an intermediary processing layer that automatically collects, standardizes, and processes cost and efficacy data from multiple sources before presenting it to users. This intermediary handles the complexity of data integration, allowing comprehensive information delivery without exposing system complexity to end users.
2Measurement precision
If real-time prescription benefit verification is implemented, then accurate patient-specific copay information is provided, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing benefit verification data and copay information before prescriptions are written. This allows real-time queries to retrieve pre-processed information quickly, maintaining accuracy while reducing processing time at the point of care.
Solution Approach 2:
The system implements feedback mechanisms where prescription benefit verification results are immediately returned to prescribers and patients, enabling instant decision-making. This feedback loop provides accurate copay information in real-time without significant delay by optimizing data retrieval and presentation.
3Productivity
If drug alternatives are ranked by price, then cost-effective options are highlighted, but clinically superior but more expensive options may be obscured
Solution Approach 1:
The system applies different sorting criteria to different sections or contexts within the same interface. Drug alternatives can be sorted by price in one view while maintaining clinical efficacy ratings and coverage status visible in all views, allowing users to prioritize cost-effectiveness without losing sight of clinical quality.
Solution Approach 2:
The system provides multiple sorting and filtering functions that work simultaneously on the same drug alternative data set. Users can sort by price, clinical efficacy, or coverage status, and the system maintains all these attributes visible, allowing comprehensive evaluation regardless of the primary sort criterion used.
4Adaptability or versatility
If filtering options for route and form are added, then drug alternatives are more precisely matched to patient needs, but the interface complexity increases
Solution Approach 1:
The system implements dynamic filtering where available filter options adapt based on the selected therapeutic class or drug. Only relevant route and form filters are displayed for each drug type, reducing interface complexity while maintaining precise matching capability when needed.
Data Source
AI summary
A method of processing drug alternatives for a selected drug. The method includes receiving a selection of the selected drug and generating a drug alternatives list from source data, the drug alternative list including a plurality of drug alternatives. The method includes gaining access to a price model and at least one price data source. The method includes determining respective prices for the plurality of drug alternatives according to the price model and the at least one price data source and ranking the plurality of drug alternatives in the drug alternatives list according to respective ordinality and respective prices. The method includes suppressing ones of the plurality of drug alternatives lacking a desired clinical outcome from the drug alternatives list. The method includes filtering resultant drug alternatives by at least one parameter. The method includes transmitting the drug alternatives list to a user computing system for display.