Document Subset Extraction for Medical Coding Accuracy
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Solution Overview
Problem
Medical coders spend a significant amount of time reviewing and navigating through unformatted, often handwritten or scanned, medical documents to identify billable aspects for coding, which is cumbersome and time-consuming, typically requiring up to 70% of their time.
Innovation Solution
A computer-implemented method and system that receives electronic documents associated with a patient's encounter, applies predefined rules to extract relevant portions, and generates a user interface displaying subsets of documents, allowing coders to focus on key information, thereby reducing the time spent on document review and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If medical coders review all electronic documents to identify billable aspects, then coding accuracy is maintained, but time consumption increases significantly (up to 70% of coder's time)
Solution Approach 1:
The system extracts and displays only the relevant portions of electronic documents that contain billable aspects, rather than requiring coders to review entire documents. This extraction of essential information maintains coding accuracy while significantly reducing the time coders need to spend on document review.
Solution Approach 2:
The system segments large volumes of electronic documents into smaller, manageable subsets based on relevance to coding tasks. By dividing the document set into targeted portions, coders can efficiently review only the necessary segments, preserving accuracy while reducing overall time consumption.
2Reliability
If medical coders review numerous unformatted documents, then comprehensive billable aspects are identified, but ease of operation deteriorates due to document navigation complexity
Solution Approach 1:
The system extracts and presents only the relevant portions of unformatted documents in a standardized, easily navigable format. This extraction eliminates the need for coders to manually navigate through complex document structures while ensuring comprehensive identification of billable aspects is maintained.
3Loss of information
If all portions of electronic documents are displayed to coders, then complete information is available, but productivity decreases due to information overload
Solution Approach 1:
The system extracts and displays only the essential portions of electronic documents that contain billable information, eliminating redundant content. This selective extraction maintains information completeness for coding purposes while significantly improving productivity by reducing information overload.
Solution Approach 2:
The system segments document information into relevant and irrelevant portions, presenting only the relevant segments to coders. This segmentation maintains complete access to necessary information while improving productivity by eliminating distracting or unnecessary content.
Data Source
AI summary
Systems and methods for displaying subsets of electronic documents generated in association with a patient's encounter with a healthcare organization.