Healthcare Financial Data Segmentation for Cost Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Hospitals face challenges in optimally managing financial performance while improving patient care outcomes due to existing technologies' inability to accurately identify and manage costs and revenue opportunities at a patient, contract, and physician level, and fail to provide real-time allocation of total provider cost of care and profitability.
Innovation Solution
A system that aggregates data from various sources, generates statistical models, and applies analytics to identify cost savings and revenue enhancement opportunities, enabling timely and accurate reporting and automated corrections to hospital information systems, thereby improving clinical and financial outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing technologies are used to manage healthcare financial performance, then general financial tracking is maintained, but accurate identification and management of costs and revenue opportunities at patient, contract, and physician levels is not achieved
Solution Approach 1:
The system segments healthcare financial data by multiple dimensions including patient, contract, physician, service line, and payer. This segmentation enables precise cost identification and revenue opportunity management at granular levels while maintaining an integrated view through the common data model.
Solution Approach 2:
The patent introduces a intermediary computing system that acts as a mediator between existing healthcare information systems and financial analysis tools. This intermediary layer integrates data from multiple sources without requiring changes to existing systems, thereby improving measurement precision without proportionally increasing overall system complexity.
2Loss of time
If real-time allocation of total provider cost of care and profitability is implemented, then financial performance visibility is improved, but data processing complexity and computational resources increase
Solution Approach 1:
The system performs preliminary data aggregation and normalization continuously in the background, maintaining pre-processed financial data ready for rapid analysis. This preliminary action enables real-time profitability allocation without requiring intensive computational resources at the moment of reporting.
Solution Approach 2:
The patent employs parameter changes by dynamically adjusting the granularity and scope of financial analysis based on user needs. The system can shift between aggregated views and detailed analyses, optimizing computational resource usage while maintaining real-time capabilities for critical metrics.
3Loss of information
If data from multiple disparate systems is integrated, then data continuity and completeness are enhanced, but system integration complexity increases
Solution Approach 1:
The system implements a universal data model that can represent multiple types of healthcare data from different sources in a unified structure. This multi-functional framework enables seamless integration of clinical, financial, and operational data without requiring separate integration pathways for each data type.
Solution Approach 2:
The patent uses an intermediary integration layer that standardizes data from disparate systems before analysis. This intermediary component handles the complexity of data mapping and transformation, ensuring data continuity while isolating the core analytical functions from integration complexity.
4Productivity
If actionable insights for improving operating margins are provided, then financial performance is enhanced, but the complexity of analysis and model generation increases
Solution Approach 1:
The system implements feedback loops that continuously monitor financial performance metrics and automatically generate actionable insights. The statistical models learn from historical data and provide real-time recommendations for improving operating margins, reducing the complexity of manual analysis while enhancing productivity.
Solution Approach 2:
The patent enables self-service analytical capabilities where the system automatically generates insights and recommendations without requiring complex manual intervention. The automated statistical modeling and insight generation reduce analysis complexity while improving operating margin outcomes through consistent, data-driven recommendations.
Data Source
AI summary
Example embodiments of a system, apparatus, computer readable media, and method are disclosed for improving clinical and financial outcomes for a healthcare provider The example embodiments may be used for aggregating data corresponding to care for a group of patients by at least one healthcare provider, generating a statistical model based on the aggregated data, periodically determining a current value for the treatment parameter associated with care of a patient provided by a healthcare provider, and causing treatment to be administered to the patient in response to applying the statistical model to determine that the current value for the treatment parameter is associated with an adverse outcome.