Healthcare Data Alignment System for Billing Accuracy

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Solution Overview

Problem

Healthcare facilities face challenges in accurately and efficiently transferring clinical charge data from Order Entry Systems (OES) to Charge Description Master (CDM) databases, leading to incorrect billing and reimbursement issues due to discrepancies in procedure descriptions, unit of measure, and active flags, which are often manually reviewed and prone to errors.

Innovation Solution

A computer-implemented method that imports and analyzes data from OES and CDM files, creates a linked data items file, and compares descriptors and unit measures to identify similarities and differences, using artificial intelligence to flag errors and automatically communicate corrections to ensure accurate billing by aligning OES data items with CDM data items.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual review methods are used to transfer clinical charge data from OES to CDM, then flexibility and adaptability are maintained, but accuracy and efficiency deteriorate due to human errors and time-consuming processes

Engineering Contradiction:

Improveaccuracy of charge data transferVSAvoidtime required for data review and correction

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces the manual mechanical review process with an automated computer-based system that uses algorithms to compare OES data items with CDM data items, eliminating human error and significantly reducing the time required for charge data verification

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service by automatically performing the comparison and identification of discrepancies between OES and CDM data without requiring manual intervention, allowing the system to correct its own errors through automated flagging and notification mechanisms

Inventive Principle:

Principle #25Self-service

2Productivity

If automated data transfer is implemented from OES to CDM, then efficiency and productivity are improved, but reliability deteriorates due to discrepancies in procedure descriptions, unit of measure, and active flags

Engineering Contradiction:

Improveefficiency of charge data transferVSAvoidaccuracy of billing and reimbursement

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system implements feedback mechanisms by automatically flagging discrepancies between OES and CDM data items and notifying relevant personnel, allowing for continuous improvement and verification of data accuracy while maintaining high productivity

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary actions by proactively identifying and flagging potential billing errors before they affect reimbursement, allowing corrections to be made in advance and ensuring reliable billing without sacrificing efficiency

Inventive Principle:

Principle #10Preliminary action

3Reliability

If comprehensive manual verification of all data items is performed, then reliability of billing is improved, but productivity and ease of operation worsen due to the complex and time-consuming process

Engineering Contradiction:

Improveaccuracy of billing codesVSAvoidcomplexity of data verification process

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system applies partial action by focusing verification efforts only on specific critical data items such as procedure descriptions, unit of measure, and active flags that have the greatest impact on billing accuracy, rather than requiring comprehensive manual verification of all data elements

Inventive Principle:

Principle #16Partial or excessive action

4Productivity

If automated comparison algorithms are used to match OES and CDM data items, then productivity is improved, but measurement precision may worsen due to difficulty in detecting subtle discrepancies

Engineering Contradiction:

Improvespeed of data alignmentVSAvoiddetection of subtle data differences

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system applies local quality by using different comparison strategies for different data item types, applying more rigorous verification methods to critical fields such as procedure descriptions and unit of measure while using faster comparison methods for less critical data elements

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11923055B1Computer-based tools and techniques for analyzing health care data in connection with medical procedures

Publication Date: 2024.03.05 MEDCOM SOLUTIONS

AI summary

Tools and techniques are provided for analyzing health care procedure related transactions of a health care entity. The method can include creating a linked data items file, by a transaction analysis computer system, derived from a combination of a charge description master (CDM) file containing CDM data items, an order entry system (OES) file containing OES data items, and a CDM-to-OES cross-reference data file. The linked data items file can be analyzed by reading linked line items, analyzing its CDM data portion, analyzing its OES data portion, and/or comparing the linked CDM data portion to the linked OES data portion for determining similarities or differences between the CDM and OES data portions.