Multi-Site Sepsis Detection via Intermediary Data Aggregation
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Solution Overview
Problem
Current clinical decision support systems are limited by the lack of interoperability between different medical organizations, leading to incomplete patient information sharing and inconsistent monitoring of conditions like sepsis, which can result in delayed treatment due to disparate reference ranges used by healthcare providers.
Innovation Solution
A multi-site clinical decision support system that aggregates patient information from disparate medical organizations using a risk assessment array, allowing for near real-time notification of clinicians when actionable criteria for conditions such as sepsis are met, enabling timely intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If patient information is shared across multiple medical organizations, then detection accuracy and completeness of patient conditions is improved, but system complexity and interoperability requirements increase
Solution Approach 1:
The patent introduces a centralized monitoring system that acts as an intermediary between multiple medical organizations' electronic medical record systems. This monitoring system receives, aggregates, and standardizes patient information from disparate sources, enabling comprehensive detection without requiring direct integration between all participating organizations. The intermediary handles the complexity of interoperability centrally while maintaining relative simplicity at individual organization levels.
2Adaptability or versatility
If diverse reference ranges from different healthcare providers are used, then adaptability to various clinical practices is improved, but measurement consistency and reliability of condition detection deteriorate
Solution Approach 1:
The patent allows each medical organization to maintain its own local reference ranges and clinical standards in its electronic medical record system, preserving local quality and adaptability. Meanwhile, the centralized monitoring system applies standardized detection criteria and reference ranges when analyzing aggregated patient data, ensuring measurement consistency and reliability across all organizations. This dual approach enables both local customization and global standardization.
3Loss of time
If real-time monitoring of patient information is implemented, then response time for condition detection is improved, but information processing requirements and system resource consumption increase
Solution Approach 1:
The patent implements preliminary action by having medical organizations continuously populate and update patient information in electronic medical record systems in advance of any specific detection query. The monitoring system periodically queries and aggregates this pre-prepared data, rather than requiring complex real-time streaming processing. This approach enables timely detection while reducing instantaneous processing requirements compared to true real-time continuous analysis.
Data Source
AI summary
Methods are provided for validating theoretical improvements in the decision-support processes facilitating surveillance and monitoring of a patient's risk for developing a particular disease or condition and detecting the disease or condition. Patient information is received from a source and populated into an active risk assessment that monitors the patient's risk for developing Sepsis. At least a first and second set of actionable criteria for determining a patient's risk for developing sepsis are received. For each set of actionable criteria, it is determined that actionable criteria have been met. In some embodiments, software agents, operating in a multi-agent computing platform, perform each determination of whether actionable criteria are met. In some embodiments, in response to actionable criteria being met, a notification or alert is provided, and in some embodiments the results of the determinations of each set of actionable criteria are provided to facilitate validation of theoretical improvements.