Composite Acuity Score Generator for ICU Data Integration
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Solution Overview
Problem
In intensive care units, the abundance of patient data from various sources leads to information overload, making it time-consuming and inefficient to integrate and interpret, which can result in neglect of relevant data and errors in patient care, especially in predicting patient deterioration such as single-organ system failure or multi-organ system failure.
Innovation Solution
A patient monitoring system that senses shorter interval physiological parameters, collects longer interval data, and generates a composite acuity score to provide real-time updates and alerts to healthcare professionals, enabling faster presentation of critical information and prediction of patient instability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive patient data from multiple sources is collected, then the completeness of patient information is improved, but the complexity of data integration and interpretation increases
Solution Approach 1:
The system segments patient data into distinct categories (vital signs, laboratory results, imaging studies, clinical observations) and processes each category through dedicated modules. The acuity score is segmented into multiple parameters (hemodynamic stability, respiratory function, renal function, etc.) that are calculated separately and then integrated, making the complex integration process more manageable and systematic.
Solution Approach 2:
The patent introduces an intermediary processing layer that automatically integrates and interprets data from multiple sources. This intermediary system uses predefined algorithms and clinical decision support rules to synthesize raw data into meaningful acuity scores and alerts, reducing the burden on clinicians to manually integrate information while maintaining completeness.
2Measurement precision
If detailed patient data is collected and analyzed, then the accuracy of patient condition assessment is improved, but the time required for data processing increases
Solution Approach 1:
The system performs preliminary processing of patient data by continuously collecting and pre-analyzing information from multiple sources in the background. Acuity scores are calculated in advance and updated in real-time as new data becomes available, so that when clinicians need the information, it is already prepared and ready for immediate review, reducing processing time while maintaining accuracy.
Solution Approach 2:
The patent replaces manual data integration and interpretation (mechanical human effort) with automated computer-based algorithms and artificial intelligence. The system automatically calculates acuity scores, generates alerts, and provides clinical decision support, dramatically reducing the time required for data processing while improving assessment accuracy through consistent application of clinical criteria.
3Reliability
If continuous monitoring of physiological parameters is implemented, then the ability to detect patient deterioration is improved, but the amount of information to be monitored increases
Solution Approach 1:
The system extracts only the most critical and clinically relevant information from the continuous stream of monitored physiological parameters. By focusing on key indicators that are most predictive of patient deterioration (such as changes in heart rate, blood pressure, oxygen saturation, and laboratory values), the system reduces the information burden on clinicians while maintaining high reliability in detecting deterioration through targeted monitoring of essential parameters.
Solution Approach 2:
The patent uses visual alerting mechanisms that change the appearance (color, intensity) of displayed information based on the level of concern. Normal parameters are displayed in neutral colors, while abnormal values or deteriorating trends are highlighted with color-coded alerts (yellow for warning, red for critical), enabling clinicians to quickly identify and prioritize the most important information without being overwhelmed by the total volume of data.
4Loss of information
If multiple data sources are integrated, then the comprehensiveness of patient assessment is improved, but the efficiency of information delivery decreases
Solution Approach 1:
The system segments the comprehensive patient assessment into organized categories and hierarchical levels of information. The acuity score is divided into multiple parameters representing different organ systems (cardiovascular, respiratory, renal, neurological, etc.), allowing clinicians to efficiently access specific aspects of patient status without reviewing all available data. This segmented presentation maintains comprehensiveness while improving delivery efficiency through structured organization.
Solution Approach 2:
The patent implements feedback mechanisms that automatically generate alerts and notifications when specific thresholds are exceeded or when deterioration is detected. This feedback system delivers only the most critical information to clinicians in real-time, enabling efficient response to changing patient conditions while maintaining comprehensive monitoring of all parameters in the background. The feedback loop ensures that comprehensive assessment results are delivered efficiently through targeted alerts rather than requiring review of all data.
Data Source
AI summary
In a patient monitoring system (10), shorter interval physiological parameters and longer interval clinical data are collected from a monitored patient (12). A composite acuity score generator (70) generates or updates a composite acuity score indicative of wellbeing of the patient (12) based at least on the sensed physiological parameters and the longer interval data. A monitor (22, 56) displays current values of at least one of selected sensed physiological parameters, longer interval data, and the composite acuity score.