Automated Healthcare Quality Reporting System Using Rules Engine
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Solution Overview
Problem
Current reporting systems for healthcare providers are complex and time-consuming due to the need to manually navigate extensive sets of rules and criteria for calculating quality measures, which are required by government regulations such as those set by the Centers for Medicare and Medicaid Services, involving numerous codes and exclusion criteria.
Innovation Solution
An automated system utilizing a rules engine that traverses hierarchical trees of denominator and numerator questions using structured descriptive data items like SNOMED, ICD9, ICD10, RxNorm, and CPT codes to determine patient eligibility and generate quality measure reports, reducing the need for manual data entry and simplifying the reporting process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual reporting methods are used to calculate quality measures, then providers can report quality data, but the process becomes extremely time-consuming and complex
Solution Approach 1:
The patent replaces manual mechanical processes with an automated computer-based system. The system automatically calculates quality measures by retrieving patient data from electronic health records, applying quality measure specifications, and generating reports without manual intervention. This substitution of manual mechanical operations with automated computational processes directly resolves the contradiction by maintaining reporting accuracy while dramatically reducing the time required.
Solution Approach 2:
The system enables self-service automation where the computer automatically performs data retrieval, calculation, and report generation. The automated system serves itself by autonomously navigating quality measure specifications, selecting appropriate patient populations, calculating numerators and denominators, and producing final reports without requiring provider intervention at each step, thus eliminating time loss while preserving reliability.
2Reliability
If comprehensive quality measure specifications with extensive rules are implemented, then reporting completeness is improved, but the complexity of the reporting system increases
Solution Approach 1:
The patent segments the complex quality measure reporting process into distinct automated components: data retrieval from electronic health records, application of quality measure specifications, calculation of quality measures, and report generation. By dividing the comprehensive reporting requirements into manageable automated segments, the system maintains complete and accurate reporting while reducing the perceived complexity for providers who no longer need to manually navigate the entire process.
Solution Approach 2:
The computer-based system acts as an intermediary between the complex quality measure specifications and the provider. It automatically interprets and applies the extensive rules and criteria embedded in the specifications, serving as a mediator that translates complex regulatory requirements into automated calculations and clear report outputs, thereby maintaining reporting completeness while shielding providers from system complexity.
3Productivity
If automated calculation systems are implemented, then reporting efficiency is improved, but the initial setup and data structure requirements become more complex
Solution Approach 1:
The patent implements preliminary action by pre-structuring the electronic health record data and pre-configuring the quality measure specifications in the system before reporting is needed. Patient data is organized in advance with appropriate coding and metadata, and quality measure criteria are pre-loaded and validated. This preliminary preparation enables highly efficient automated calculation during the actual reporting period, as the system simply needs to retrieve and process pre-structured data rather than organizing it from scratch.
Data Source
AI summary
An automated system for making quality measure submissions. In one embodiment, the system includes: a data input system; a data output system; a database of descriptive data items; a processor in communication with the data input system, the data output system and the database, and comprising a rules engine to traverse a hierarchical tree of denominator and numerator questions, using patient input and data items from the database of descriptive data items. In one embodiment, the invention relates to an automated review system for providing a multiple measure review of care including: a provider input device for inputting patient data; a patient database; a rules engine in communication with the patient database and traversing a plurality of denominator and numerator rules, using provider input patient data and patient data from the database to generate, from multiple encounters and multiple measures, the review of care subsequent to each visit.