On-Demand Patient Data Analysis Platform
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Solution Overview
Problem
Inefficient medical diagnostics and redundant testing occur due to disparate healthcare data sources that do not communicate effectively, making it difficult for healthcare providers to assess patient care quality and compliance with regulatory standards in real-time, especially in complex and costly healthcare environments.
Innovation Solution
A computing platform that enables on-demand real-time analysis of patient-specific data from multiple internal and third-party databases, allowing clinicians to order and receive pertinent analytics through existing interfaces, aggregating and mining data to support high-quality and cost-effective care.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is aggregated and analyzed from multiple sources to create a comprehensive patient view, then healthcare quality is maximized, but the complexity of data integration and analysis becomes untenable for individual providers
Solution Approach 1:
The patent introduces an intermediary computing platform that sits between multiple healthcare data sources and individual providers. This platform automatically aggregates, standardizes, and analyzes data from EHRs, claims databases, and other sources, then delivers synthesized insights to providers through existing interfaces. The intermediary handles the complexity of data integration, allowing providers to access comprehensive patient information without directly managing the integration complexity.
2Loss of substance
If real-time analysis of patient data is performed during clinical encounters, then unnecessary tests are reduced, but the time required to process and analyze voluminous data becomes a constraint
Solution Approach 1:
The system performs preliminary actions by pre-processing and organizing patient data from multiple sources before the clinical encounter occurs. Data is aggregated, standardized, and made queryable in advance, so when a provider needs information during a patient visit, the analysis can be quickly retrieved and presented without requiring time-consuming data collection and processing during the encounter itself.
Solution Approach 2:
The patent replaces manual data collection and analysis mechanisms with automated computing systems. Instead of providers manually gathering data from multiple sources and analyzing it, an automated platform performs data aggregation, standardization, and analysis through electronic interfaces, dramatically reducing the time required while enabling real-time decision support during clinical encounters.
3Measurement precision
If comprehensive patient data is collected from disparate sources, then quality of care assessment is improved, but the ability to make real-time assessments is compromised due to data volume and dispersion
Solution Approach 1:
The system replaces manual data collection and assessment processes with automated electronic data retrieval and analysis. The computing platform automatically queries and aggregates data from EHRs, claims databases, and other sources, then performs real-time analysis to assess quality of care metrics, enabling providers to obtain comprehensive assessments instantly without manual intervention.
Solution Approach 2:
The patent creates a universal data access platform that can retrieve and analyze multiple types of patient data from diverse sources through standardized interfaces. This multi-functional system handles clinical data, administrative data, and quality metrics simultaneously, allowing comprehensive quality assessment to be performed in real-time across all data types through a single integrated system.
Data Source
AI summary
A computing platform configured to receive and process an on-demand real-time patient-specific data analysis order is provided. The computing platform can receive an order, determine the viability of the order, and then perform the desired analysis based on parameters provided within the order. As part of the analysis, the computing platform can mine one or more data sources to collect data relevant to the ordered diagnostic. Once the data is collected, the computing platform can analyze the data according to one or more pre-programmed algorithms. The selection of which algorithms to apply to the data set can be determined by the type of on-demand real-time patient-specific data analysis ordered. The on-demand real-time patient-specific data analysis in some examples can be ordered using an external ordering user interface.