Clinical Decision Support Orchestrator Module
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Solution Overview
Problem
Current clinical decision support systems in ICU environments face challenges due to the complexity of managing multiple AI monitoring algorithms and clinical protocols, which can lead to workflow disruptions, cognitive burden on healthcare providers, and potential errors in patient care.
Innovation Solution
A clinical decision support system that includes an orchestrator module to coordinate the interaction between AI monitoring algorithms and clinical protocols, ensuring that only relevant algorithms and protocols are activated based on real-time patient data and predefined conditions, thereby reducing cognitive burden on healthcare providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple AI monitoring algorithms and clinical protocols are deployed to improve patient care, then the quality and comprehensiveness of patient monitoring is improved, but the cognitive burden on healthcare providers and workflow disruption increase
Solution Approach 1:
The patent introduces an orchestrator module as an intermediary between multiple AI algorithms/protocols and healthcare providers. This orchestrator centrally manages algorithm selection, configuration, and execution, shielding providers from the complexity of individual algorithms while maintaining comprehensive monitoring. The orchestrator handles parameter coordination and conflict resolution, allowing multiple algorithms to run without directly burdening the provider with their individual complexities.
Solution Approach 2:
The orchestrator module serves multiple functions: it selects appropriate algorithms based on patient conditions, configures their parameters, coordinates their execution, and manages their interactions. This single multi-functional component replaces what would otherwise require multiple separate management systems, reducing overall system complexity while maintaining the ability to deploy comprehensive monitoring.
2Reliability
If multiple AI monitoring algorithms and clinical protocols are deployed to improve patient care, then the comprehensiveness of monitoring is improved, but the cognitive burden on healthcare providers increases
Solution Approach 1:
The orchestrator acts as a central intermediary that manages the complexity of multiple algorithms and protocols. It provides a unified interface for algorithm selection and management, hiding the individual complexities of each algorithm from the provider. The orchestrator handles parameter coordination, conflict resolution, and execution management, effectively containing system complexity within a single managing component rather than distributing it across multiple independent systems.
3Measurement precision
If AI algorithms require comprehensive input data including laboratory results, ventilation information and patient demographics, then the accuracy of risk prediction is improved, but the staff time and resource needed to provide all necessary inputs increases
Solution Approach 1:
The system enables self-service by automatically collecting and integrating required input data from multiple sources including electronic health records, laboratory systems, and ventilation equipment. The orchestrator identifies which data are needed for selected algorithms and automatically retrieves them, eliminating the need for staff to manually gather comprehensive patient information. This automated data aggregation maintains high prediction accuracy while removing the time burden of data collection.
4Measurement precision
If comprehensive input data including laboratory results, ventilation information and patient demographics are collected to improve risk prediction accuracy, then the sophistication of risk prediction is improved, but the staff time and resources needed outweigh the benefits
Solution Approach 1:
The system performs self-service by automatically identifying, collecting, and integrating all necessary input data for sophisticated risk prediction algorithms. The orchestrator manages the entire data aggregation process without requiring staff intervention, allowing the system to maintain high prediction sophistication while preserving clinical efficiency. Staff focus remains on patient care rather than data collection.
Solution Approach 2:
The orchestrator serves as an intermediary that manages the complex interaction between data collection requirements and algorithm execution. It automatically coordinates with various data sources (laboratory systems, ventilation equipment, EHR) and integrates the data streams, maintaining sophisticated prediction capabilities while eliminating the productivity loss that would result from manual data gathering.
Data Source
AI summary
A clinical decision support system including an orchestrator module adapted to co-ordinate the triggering of inference algorithms and the execution of clinical protocols. The system further includes modules for checking input requirements for inference algorithms are met before an algorithm is released for use.