Exception Record Batch Validation for Cross-Record Conflict Resolution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Healthcare providers face inefficiencies and errors in manual intra-record validation processes for exception records, which can lead to cross-record inconsistencies and conflicts, particularly in specialized fields like anesthesia, due to the time-consuming and error-prone nature of reviewing and correcting these records.
Innovation Solution
An automated batch processing system with a graphical user interface that includes a batch explorer, artifact components for displaying and editing exception records, and automated inter-record validations to detect and resolve time concurrency and modifier processing errors, facilitating efficient intra-record and inter-record validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual intra-record validation is performed for exception records, then individual record accuracy is improved, but cross-record inconsistencies and time conflicts arise due to the error-prone nature of manual processes
Solution Approach 1:
The patent introduces an automated validation system as an intermediary between manual record review and final record approval. This system includes a validation module that automatically checks exception records for both intra-record errors and inter-record conflicts, such as time concurrency issues and provider availability conflicts. The automated system acts as a mediator that identifies and flags issues before manual processing, thereby improving both record accuracy and cross-record consistency simultaneously.
Solution Approach 2:
The patent replaces the mechanical manual validation process with an automated computational system. Instead of relying on human reviewers to manually check each exception record for errors and conflicts, the system uses automated algorithms to perform intra-record validation and inter-record conflict detection. This substitution eliminates human errors in manual processing while maintaining high accuracy standards, and efficiently identifies cross-record inconsistencies that would be difficult to detect manually.
2Measurement precision
If manual review and correction of exception records is performed, then data accuracy is improved, but the process becomes time-consuming and reduces productivity
Solution Approach 1:
The patent implements preliminary automated validation of exception records before they are submitted for final approval. The system proactively identifies intra-record errors and inter-record conflicts using automated validation rules and algorithms. By performing this validation action in advance, the system prevents erroneous records from proceeding to manual review, thereby maintaining high data accuracy while significantly reducing the time required for manual correction and revalidation cycles.
Solution Approach 2:
The patent replaces the time-consuming manual review and correction process with automated computational validation. The system uses algorithms to rapidly check exception records for errors and conflicts, processing multiple records simultaneously. This mechanical substitution maintains rigorous data accuracy standards while increasing processing speed and productivity, as the automated system can evaluate records much faster than human reviewers without sacrificing thoroughness.
3Measurement precision
If intra-record validation is performed to ensure individual record accuracy, then record-level errors are reduced, but broader cross-record effects and conflicts are not mitigated
Solution Approach 1:
The patent introduces an inter-record validation module as an intermediary that specifically addresses cross-record conflicts. This module analyzes relationships between multiple exception records to detect time concurrency issues, provider availability conflicts, and scheduling overlaps that arise from intra-record corrections. By adding this intermediary validation layer, the system ensures that fixing errors in individual records does not create or propagate conflicts across related records, thereby mitigating cross-record harmful effects while maintaining intra-record accuracy.
Solution Approach 2:
The patent implements a feedback mechanism where the validation system continuously monitors and adjusts exception record processing based on detected inter-record conflicts. When intra-record validation identifies errors that need correction, the system performs automated checks to ensure these corrections do not create new conflicts with related records. The feedback loop includes automated revalidation steps that verify cross-record consistency after corrections are applied, preventing the propagation of harmful effects across the record set while maintaining high intra-record accuracy standards.
Data Source
AI summary
In some embodiments, a method for automated batch processing of a plurality of exception records includes displaying an automated batch processing graphical user interface comprising: a batch explorer user interface container that includes a hierarchical view of a plurality of exception record batches, a first artifact user interface component that is configured to display a plurality of top-level exception records associated with an exception record batch selected in the batch explorer user interface element, a second artifact user interface component that is configured to display a plurality of sub-level exception records subordinate to a top-level exception record selected in the first artifact user interface component, and a plurality of editable user interface fields that are configured to receive input for modifying a plurality of attributes associated with a sub-level exception record selected in the second artifact user interface component.