Automatic Medical Coding System Using Natural Language Processing
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Solution Overview
Problem
Manual medical coding is time-consuming and prone to errors, often delaying reimbursement processes and requiring specialized personnel, as it typically occurs after patient encounters, leading to inefficiencies in pre-claim communications and potential reimbursement issues.
Innovation Solution
An automatic medical coding system that includes a parser, mapper, and optional scorer to translate natural language diagnosis or procedure descriptions into standardized medical codes, utilizing databases for normalization and semantic analysis to enhance accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual medical coding is performed by specialized personnel, then coding accuracy is improved, but processing time and operational complexity increase
Solution Approach 1:
The system performs preliminary medical coding during patient intake or scheduling, before the actual patient encounter or procedure occurs. This allows codes to be prepared in advance, reducing post-encounter processing time while maintaining accuracy through automated analysis of available information.
Solution Approach 2:
The patent replaces the manual mechanical process of coded review and selection with an automated computer-based system that uses natural language processing, pattern recognition, and algorithmic mapping to convert clinical documentation into medical codes automatically, eliminating the need for specialized human coders.
2Loss of information
If medical coding is performed after patient encounters, then complete information is available, but reimbursement processes are delayed
Solution Approach 1:
The system performs preliminary medical coding during patient intake or scheduling, before the actual patient encounter or procedure occurs. This allows codes to be prepared in advance, reducing post-encounter processing time while maintaining accuracy through automated analysis of available information.
Solution Approach 2:
The patent enables continuous medical coding operations by processing documentation in real-time or near-real-time as it becomes available, rather than batching all coding tasks after encounters end. This continuous processing maintains information quality while eliminating delays in reimbursement submissions.
3Ease of operation
If non-specialized personnel perform medical coding, then operational complexity is reduced, but coding accuracy decreases
Solution Approach 1:
The patent replaces the manual mechanical process of coded review and selection with an automated computer-based system that uses natural language processing, pattern recognition, and algorithmic mapping to convert clinical documentation into medical codes automatically, eliminating the need for specialized human coders.
Solution Approach 2:
The system enables self-service medical coding where the computer automatically performs the coding function without requiring specialized human operators. The automated system serves itself by processing documentation, generating codes, and submitting them for reimbursement, making the process accessible to non-specialized personnel.
4Adaptability or versatility
If narrative descriptions are used instead of standardized codes, then documentation flexibility is improved, but reimbursement processing efficiency decreases
Solution Approach 1:
The patent replaces the manual mechanical process of coded review and selection with an automated computer-based system that uses natural language processing, pattern recognition, and algorithmic mapping to convert clinical documentation into medical codes automatically, eliminating the need for specialized human coders.
Solution Approach 2:
The system dynamically changes the parameter of code representation by automatically converting flexible narrative descriptions into standardized medical codes through automated processing. This transformation maintains the adaptability of narrative input while achieving the processing efficiency of standardized codes through algorithmic conversion.
Data Source
AI summary
An automatic medical coding system is provided. The system parses features of natural language diagnosis and procedure information. The features are compared to elements of a medical coding system. Medical codes corresponding to medical coding system elements that match features of the diagnosis and procedure information are mapped to the received diagnosis and procedure information. The mapped medical code is assigned a score reflecting the estimated reliability of the mapped medical code based on the amount of manipulation of the received diagnosis and procedure information leading to the match. The scored medical code may be submitted to a workflow making use of medical codes. The scored medical code may optionally be presented to a user for review prior to further utilization of the scored medical code.