Healthcare Estimate Accuracy Scoring Engine
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Solution Overview
Problem
Current healthcare estimation models lack a quantitative method to score variables impacting accuracy, leading to inaccurate estimates and a lack of comparison between different revenue cycle vendors, which strains the healthcare system and affects patient and provider relationships.
Innovation Solution
A system and method for providing quantitative estimate accuracy scoring, utilizing an estimate scoring engine to measure and compare estimate accuracy across vendors and payers, identifying sources of inaccuracies and improving model accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If estimation models are used to determine out-of-pocket responsibility, then billing efficiency is improved, but estimate accuracy deteriorates due to lack of quantitative scoring methods
Solution Approach 1:
The patent implements a feedback mechanism by comparing estimated amounts against actual adjudicated amounts and using this feedback to score and refine estimation models. The system calculates accuracy scores based on the difference between estimated and actual patient responsibilities, enabling continuous improvement of estimation accuracy while maintaining billing efficiency.
Solution Approach 2:
The patent replaces manual assessment of estimation accuracy with an automated quantitative scoring system. Instead of subjective evaluation, the system uses computational algorithms to objectively score estimation accuracy based on mathematical comparisons between estimated and actual amounts, thereby improving measurement precision without sacrificing billing efficiency.
2Measurement precision
If multiple variables are considered in estimation models, then estimate accuracy should improve, but device complexity increases due to lack of standardized scoring
Solution Approach 1:
The patent segments the complex estimation accuracy assessment into distinct scoreable elements. It breaks down the overall accuracy measurement into component scores for different variables and factors, allowing systematic evaluation of each variable's impact on estimation accuracy while managing model complexity through structured organization.
Solution Approach 2:
The patent transforms the complexity of multi-variable estimation into manageable parameter changes by establishing standardized scoring criteria for each variable. Instead of dealing with complex interactions, the system assigns specific score ranges and weightings to each parameter, simplifying the assessment process while maintaining comprehensive accuracy measurement.
3Device complexity
If no quantitative scoring method is used, then device complexity is reduced, but loss of information occurs regarding sources of inaccuracy
Solution Approach 1:
The patent uses feedback mechanisms to capture and analyze information about the sources of estimation inaccuracy. By comparing estimated versus actual amounts and tracking which variables contribute most to discrepancies, the system recovers lost information about inaccuracy sources, enabling targeted improvements without requiring overly complex scoring infrastructure.
4Ease of operation
If standardized accuracy comparison is not provided, then ease of operation is improved, but loss of information occurs regarding vendor performance comparison
Solution Approach 1:
The patent creates a universal scoring framework that can be applied across different revenue cycle vendors and payment types. This multi-functional scoring system enables standardized comparison of vendor performance while maintaining ease of operation through consistent criteria and automated calculations, thereby recovering lost vendor performance information.
Data Source
AI summary
Quantitative estimate accuracy scoring is provided. An estimate scoring engine uses estimate scoring model logic to quantitatively measure the accuracy of an estimate for healthcare services relative to actual values associated with an adjudication of a claim for the services. Scores are determined for various factors that impact estimate accuracy, and a total estimate accuracy score may be determined. A report may be generated and displayed in a user interface including information received and/or determined by the estimate scoring engine. A plurality of estimates may be evaluated, and the report may include a summary and details associated with the accuracy of a range of estimates. An accuracy rate associated with the range of estimates may be measured against the accuracy rate of other healthcare services providers, payers, and/or estimation models in an ‘apples-to-apples’ comparison. Accordingly, issues associated with estimate inaccuracies may be identified and addressed to improve estimate accuracy.