Outcome-Based Medical Referral System with Risk-Adjusted Data
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Solution Overview
Problem
Current healthcare provider search services lack access to reliable and accurate quality data, failing to facilitate informed purchasing decisions based on clinically relevant outcome measures and risk-adjusted comparisons, leading to suboptimal healthcare quality and increased costs.
Innovation Solution
A system and method that collects and disseminates accurate healthcare outcome data by linking user health status questions to a clinically useful outcomes database, using algorithms to provide tailored provider recommendations, integrating risk-adjustment procedures, and ensuring data accuracy and security through Hippocratic principles and fraud protection measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional find a doctor services are used, then provider listings are made accessible, but quality data is not available for informed decision-making
Solution Approach 1:
The system segments the healthcare provider search function into distinct components: outcome data collection, risk-adjustment processing, and referral generation. Each component handles a specific aspect of the problem, allowing comprehensive quality information to be provided without overwhelming system complexity.
Solution Approach 2:
The patent introduces an intermediary system that collects outcome data from multiple sources, applies risk-adjustment algorithms, and presents processed quality information to consumers. This intermediary layer transforms raw data into actionable insights without requiring consumers to directly manage the complexity of data collection and analysis.
2Ease of operation
If referrals are based on personal connections and prestige, then provider selection is simplified, but quality accuracy deteriorates
Solution Approach 1:
The system implements feedback loops where patient outcomes are continuously collected and used to update provider quality ratings. This creates an evidence-based referral system that maintains ease of use through automated rankings while improving measurement accuracy through continuous outcome data collection and risk-adjustment analysis.
3Reliability
If outcome data is collected and disseminated, then informed purchasing decisions are enabled, but data accuracy and reliability challenges arise
Solution Approach 1:
The system performs preliminary risk-adjustment processing and data validation before outcomes are disseminated. By pre-processing the data through standardized algorithms and validation protocols, the system ensures reliability while managing complexity through automated procedures rather than manual intervention.
Solution Approach 2:
The patent applies risk-adjustment parameters to normalize outcome data across different providers and patient populations. By changing the parameters through which outcomes are measured and compared, the system accounts for varying case mix and patient characteristics, thereby improving reliability without requiring complex manual adjustments.
4Reliability
If comprehensive outcome data is made accessible, then healthcare quality improves, but data security and fraud protection requirements increase
Solution Approach 1:
The system implements preliminary anti-actions by incorporating fraud detection algorithms and security protocols before data is collected and processed. These preventive measures address security risks upfront rather than reacting to breaches, allowing comprehensive outcome data to be accessed while maintaining protection against fraud and unauthorized access.
Data Source
AI summary
A method and system is described to provide outcome data to the healthcare industry allowing for fair and accurate quality based purchasing decisions. The system deploys methods to facilitate the accurate and unbiased collection of patient outcome data. From this data warehouse of outcome data, purchasers can access aggregate outcome data identifying those providers or health plans that have achieved the best outcomes for specific criteria. Similarly, individual patient referrals can be made to providers with the best track record of helping comparable patients. Based upon outcome assessment data these searches can automatically be made based on specific patient characteristics and needs.