Coverage Outcome Algorithms for Health Policy Determination
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Solution Overview
Problem
The healthcare system faces inefficiencies and increased costs due to variability in how health plans structure medical policies, leading to challenges in determining coverage for medical services and products, including genetic testing, which can result in fraud, waste, and abuse.
Innovation Solution
Implementing coverage outcome algorithms (COAs) that utilize triggers and coverage criteria associated with medical services or products, including identifiers determined by trainable machine learning models, to automate the process of determining coverage outcomes and streamline the ordering of tests within a provider's workflow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If health plans structure medical policies with high variability to accommodate different market needs, then adaptability to market variability is improved, but complexity in determining coverage increases
Solution Approach 1:
The patent segments health plan policies into standardized coverage categories and uses decision trees to break down the complex coverage determination process into manageable steps. This allows the system to handle market variability through standardized segments while simplifying the determination process through structured decision pathways.
Solution Approach 2:
The patent introduces coverage outcome algorithms (COAs) as intermediary computational models that mediate between the variability in health plan policies and the need for consistent coverage determinations. These algorithms process policy variations and transform them into standardized coverage outcomes, reducing complexity while maintaining adaptability.
2Measurement precision
If manual review processes are used to determine coverage for each unique policy structure, then accuracy in coverage determination is improved, but loss of time increases
Solution Approach 1:
The patent implements self-service coverage determination through automated decision trees and coverage outcome algorithms that independently evaluate coverage eligibility without requiring manual review. The system automatically processes claims, matches them against policy criteria, and determines coverage outcomes, eliminating time-consuming manual intervention while maintaining accuracy through structured algorithmic logic.
Solution Approach 2:
The patent performs preliminary actions by pre-processing and structuring health plan policies into standardized formats and decision trees before actual coverage determination occurs. This preparation allows rapid automated decision-making during claim processing, reducing the time needed for coverage determination while ensuring accurate application of policy criteria.
3Ease of operation
If standardized coverage categories are implemented to simplify policy review, then ease of operation is improved, but adaptability to specific policy variations decreases
Solution Approach 1:
The patent implements dynamic coverage determination through decision trees that can adapt to different policy variations while maintaining a standardized review process. The algorithms dynamically adjust their evaluation based on the specific policy structure encountered, allowing the system to handle policy variations without sacrificing ease of operation through rigid categorization.
Solution Approach 2:
The patent creates universal coverage outcome algorithms that can handle multiple policy variations and structures through a single standardized framework. These algorithms are designed to be multi-functional, accommodating different health plan policies while maintaining consistent operation, thus achieving both ease of operation and adaptability to policy variations.
4Reliability
If comprehensive coverage criteria are applied to ensure thorough policy compliance, then reliability of coverage determination is improved, but device complexity increases
Solution Approach 1:
The patent segments comprehensive coverage criteria into standardized policy categories and decision tree nodes, making the complex reliability requirements manageable through structured breakdown. This segmentation allows thorough compliance checking while reducing processing complexity by organizing criteria into hierarchical, standardized segments that can be systematically evaluated.
Solution Approach 2:
The patent replaces complex mechanical review processes with automated coverage outcome algorithms that systematically apply comprehensive coverage criteria. These algorithms use computational logic to ensure thorough policy compliance while reducing the complexity of manual processing, achieving both reliability and simplified execution through algorithmic automation.
Data Source
AI summary
The present disclosure, in one aspect, relates to implementing coverage outcome algorithms (COAs) to determine a coverage outcome indicating whether a medical service or product is covered by a health policy, and outputting the coverage outcome. In some embodiments, the COAs each utilize triggers associated with the medical service or product and/or coverage criteria associated with the health policy.