Medical Coding System Using NLU Engine and Codebook Interface
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Solution Overview
Problem
Manual medical coding is time-consuming and prone to errors, as it requires human professionals to interpret clinical documentation to assign standardized codes, which can vary from the language used in the documents.
Innovation Solution
A system employing a natural language understanding engine to automatically derive medical billing codes from free-form clinical text, with a user interface allowing human coders to review and correct the generated codes, and providing access to government-authorized codebooks for accurate coding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual medical coding is performed by human professionals, then coding accuracy can be maintained, but time consumption increases and productivity decreases
Solution Approach 1:
The system enables self-service coding by allowing the NLU engine to automatically interpret clinical documentation and generate codes without requiring human professionals to manually interpret and code each document, thereby maintaining accuracy while significantly improving productivity
Solution Approach 2:
The patent replaces the mechanical manual coding process with an automated NLU-based system that uses natural language processing to interpret clinical text and generate codes, eliminating the time-consuming manual interpretation while maintaining coding accuracy through automated algorithms
2Ease of manufacture
If manual medical coding is performed by human professionals, then coding can be performed with current technology, but the process is prone to human errors
Solution Approach 1:
The system substitutes the human-based coding process with an automated NLU engine that processes clinical documentation through natural language understanding algorithms, eliminating human errors such as misinterpretation and transcription mistakes while maintaining feasibility through structured code generation
Solution Approach 2:
The system incorporates feedback mechanisms where the NLU engine continuously processes and validates clinical documentation against coding guidelines and standards, automatically correcting potential errors and ensuring coding accuracy through iterative verification before final code generation
3Productivity
If automated code generation is implemented, then productivity increases, but system complexity increases
Solution Approach 1:
The patent introduces an NLU engine as an intermediary component that bridges the gap between raw clinical documentation and standardized codes, simplifying the overall system architecture by using a dedicated natural language processing layer that handles the complexity of text interpretation and code mapping separately
Solution Approach 2:
The system achieves multi-functionality by having the NLU engine perform multiple tasks including clinical text interpretation, code generation, error detection, and validation against coding guidelines, thereby reducing the need for multiple separate systems and simplifying the overall architecture while maintaining high productivity
4Reliability
If human professionals perform manual coding, then coding can be reviewed and corrected, but time consumption increases
Solution Approach 1:
The system implements feedback loops where the NLU engine automatically generates codes that can be immediately reviewed and corrected by human professionals with minimal time investment, as the automated generation eliminates the need for reviewing entire manual coding processes from scratch
Solution Approach 2:
The system performs preliminary action by having the NLU engine pre-generate and pre-verify codes before human review is needed, so that when humans do review, they are only correcting minor errors rather than building codes from scratch, significantly reducing review time while maintaining reliability
Data Source
AI summary
Techniques for use in medical coding include applying a natural language understanding engine to a free-form text documenting at least one clinical patient encounter to generate a set of one or more medical billing codes for the patient encounter. A user interface may be provided, configured to allow one or more human users to review and correct the generated set of medical billing codes. Within the user interface, in response to user selection of a first medical billing code of the generated set of medical billing codes, at least a portion of a government-authorized codebook for the first medical billing code may be displayed, and a position of the first medical billing code may be indicated in the displayed portion of the codebook.