Standardized DRG Coding System for Healthcare Data
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Solution Overview
Problem
Current healthcare systems face challenges in accurately assigning and updating Diagnosis Related Grouping (DRG) codes, leading to potential under or over-reimbursement for hospital services, due to inconsistencies in medical record formats across different healthcare facilities and the need for precise diagnosis coding to reflect resource intensity and patient conditions.
Innovation Solution
A method and system for entering and analyzing patient diagnoses, including primary, secondary, complication, and comorbidity diagnoses, using a hardware data processor to calculate DRG codes and generate working diagnoses, which are then stored and displayed in a standardized format within electronic medical records, allowing for real-time updates and notifications across healthcare providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If medical records are maintained in specialized local formats at each hospital facility, then each facility can maintain consistent internal formatting, but data inconsistency and lack of standardization occur across different healthcare providers
Solution Approach 1:
The patent implements a universal data exchange standard that enables medical records to be consistently formatted and exchanged across different healthcare facilities while maintaining each facility's internal formatting requirements. The standardized data structure acts as a common interface that multiple systems can use, allowing the same data to serve both local consistency and cross-facility interoperability needs.
2Loss of time
If DRG codes are assigned based on initial patient diagnoses, then reimbursement can be determined quickly, but inaccurate coding may result in under or over-reimbursement
Solution Approach 1:
The system performs preliminary DRG code assignment based on initial diagnoses to enable quick reimbursement determination, while simultaneously preparing for subsequent updates. This preliminary action allows the process to move forward efficiently without waiting for final diagnosis confirmation, reducing time loss while maintaining the ability to correct inaccuracies later.
Solution Approach 2:
The patent implements a feedback mechanism where DRG codes are initially assigned based on presenting diagnoses, then updated as additional information becomes available during hospitalization. This feedback loop ensures that coding accuracy improves over time as more diagnostic information is confirmed, while the initial assignment prevents reimbursement delays.
3Measurement precision
If diagnosis codes are updated throughout hospitalization to reflect resource intensity, then reimbursement accuracy improves, but additional data entry and processing time is required
Solution Approach 1:
The system implements automated updates to DRG codes based on changes in patient diagnosis and condition information. Rather than requiring manual data entry at each update stage, the system automatically processes diagnosis information and adjusts coding accordingly, reducing the time burden on healthcare providers while maintaining accurate reimbursement coding.
4Manufacturing precision
If accurate diagnosis coding is required to reflect complications and comorbidities, then resource allocation improves, but coding complexity increases
Solution Approach 1:
The patent segments the diagnosis coding process into distinct components: primary diagnosis, secondary diagnoses, complications, and comorbidities. Each segment is coded and processed separately, then integrated to determine the final DRG assignment. This segmentation reduces overall complexity by breaking down the complex coding task into manageable parts while ensuring accurate resource allocation reflects all relevant patient factors.
Data Source
AI summary
A hardware processor-based patient system and method having an indexing and referential storage that collects, converts and consolidates patient diagnosis information into a standardized format, including converting input diagnosis information provided by different sources and different formats into that standardized format, as well as specialized diagnosis entry subprograms to analyze patient diagnosis information, calculate diagnosis specific data and generate a working diagnosis, and display and store the diagnosis specific data and generate a working.