Revenue Cycle Workforce Allocation Using Disruption Diagnostics
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Solution Overview
Problem
Current revenue cycle management systems require costly human intervention for disruptions, leading to delayed or lost reimbursements and workforce overload, as they struggle to collect all potential revenue.
Innovation Solution
A system that utilizes diagnostic data to automatically identify, rank, and recommend corrections for disruptions in revenue cycles, optimizing inventory and workforce management by assigning tasks based on impact and required time, leveraging inventory and workforce inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human intervention is used to address disruptions in revenue cycle management, then disruptions can be corrected, but costs become prohibitive and workforce becomes overwhelmed
Solution Approach 1:
The system enables self-service by automatically identifying disruptions, ranking them by impact and correction time, and providing correction recommendations without requiring human intervention for each disruption. The system serves itself by using diagnostic data to detect and analyze its own operational issues.
Solution Approach 2:
The patent replaces the mechanical system of manual human intervention with an automated computational system that uses diagnostic data analysis, automatic disruption identification, and algorithmic ranking to identify and recommend corrections for revenue cycle disruptions.
2Productivity
If more workforce is allocated to address disruptions, then revenue collection improves, but costs increase and existing workforce becomes overwhelmed
Solution Approach 1:
The system uses feedback from diagnostic data to continuously monitor revenue cycle operations, automatically identify disruptions as they occur, and provide real-time correction recommendations. This closed-loop feedback mechanism enables the system to adapt and respond to disruptions without requiring manual workforce reallocation.
Solution Approach 2:
The system changes the parameter of disruption management from manual human effort to automated computational analysis. By transforming the management approach and using algorithmic processing instead of human labor, the system improves revenue collection efficiency without adding workforce complexity.
3Reliability
If manual processes are used to identify and correct disruptions, then corrections can be made, but time is lost and reimbursements are delayed
Solution Approach 1:
The system performs preliminary action by automatically identifying disruptions and providing correction recommendations in real-time, before disruptions can cause significant delays or losses. The system proactively detects issues and prepares correction guidance, enabling faster response compared to manual post-disruption analysis.
Solution Approach 2:
The patent replaces manual mechanical processes of disruption identification and analysis with automated computational mechanisms that process diagnostic data instantly, enabling real-time detection and immediate correction recommendations that eliminate the time delays inherent in manual processes.
Data Source
AI summary
Methods, computer systems, and computer storage media are provided for utilizing system diagnostics focused in areas of disruption to improve inventory and workforce management in a revenue cycle management system. Inventory input is received from a revenue cycle management system. The inventory input includes inventory in the revenue cycle management system, types of claims in the inventory, pair agreements of the claims, and a length of time the claims have been in the inventory. Workforce input is also received from the revenue cycle management system. The workforce input includes experience, type of education or technical training, specialty, and outcomes corresponding to a workforce of the client. A portion of the inventory is automatically assigned to an associate of the workforce. The portion of the inventory tailored to the associate based on the inventory input and the workforce input.