Dynamic Severity of Illness Scoring for Acute Care Progress Tracking
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Solution Overview
Problem
Current predictive methodologies for acute care patients, such as APACHE®, only provide a snapshot of a patient's severity of illness score during the initial 24-hour period and do not effectively track a patient's progress over time, limiting their ability to gauge condition improvements or deteriorations.
Innovation Solution
A method and system that determine a patient's severity of illness score by receiving data from electronic medical records, assigning weights to physiologic components based on deviation from normal values, and updating these weights to track a patient's progress, using a genetic algorithm to optimize weight assignment and improve predictive accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the APACHE® score uses fixed weights based on initial 24-hour data, then the score provides a standardized baseline measurement, but it cannot track patient progress over time
Solution Approach 1:
The patent applies dynamics by transitioning from fixed weights to dynamic, time-varying weights that adapt as the patient's condition changes. The weight for each physiological variable is recalculated at each time point based on the deviation from normal values at that specific moment, allowing the score to evolve and track patient progress throughout their hospital stay.
Solution Approach 2:
The patent changes the parameter of weight assignment from static to dynamic. Instead of using fixed weights determined from initial 24-hour data, the system recalculates weights continuously based on current physiological measurements, enabling the score to reflect real-time changes in patient status while maintaining standardized measurement through consistent calculation methodology.
2Productivity
If the APACHE® score is calculated only during the initial 24-hour period, then the calculation is simple and quick, but it provides only a snapshot rather than continuous monitoring
Solution Approach 1:
The patent implements continuity by extending the score calculation from a single initial assessment to continuous recalibration throughout the patient's hospital stay. The system automatically updates the severity of illness score at each time point as new physiological data becomes available, providing uninterrupted monitoring of patient status without requiring manual intervention for each calculation.
Solution Approach 2:
The system performs self-service by automatically retrieving current physiological measurements from electronic medical records, recalculating weights and scores, and updating patient status without requiring manual data entry or physician intervention at each time point, thereby maintaining calculation efficiency while enabling continuous monitoring.
3Ease of operation
If fixed weights are assigned to physiological variables, then the scoring system is easy to implement, but it cannot adapt to changing patient conditions
Solution Approach 1:
The patent changes the weight parameter from fixed to dynamic by recalculating it at each time point based on current physiological measurements. The weight for each variable is determined by the deviation from normal values at that specific moment, allowing the system to automatically adapt to changing patient conditions while maintaining a consistent calculation framework that preserves ease of implementation.
Data Source
AI summary
Systems, methods, and computer storage media are provided for determining a patient's severity of illness score (pSIS) for a patient admitted to an acute care facility. Data corresponding to physiologic components is received from an electronic medical record associated with a patient admitted to an acute care healthcare facility. The physiologic components include vital sign measurements and laboratory tests. Weights are assigned to a minimum, median, and maximum measured values for each vital sign. Weights are assigned to minimum and maximum values for each laboratory test. The weights are derived based on a deviation from normal within a time period. A pSIS is determined by summing the weights. Additional data corresponding to physiologic components may be received from the electronic medical record. The additional data may be utilized to update the weights and determine a patient's updated pSIS that may be utilized to track a progress of the patient.