Patient-Specific Drug Sensitivity Index for Anesthesia Monitoring

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Solution Overview

Problem

Current anesthesia monitoring systems lack the ability to predict a patient's future response to anesthetic drugs, relying on responsive data that does not provide proactive information, leading to challenges in maintaining appropriate sedation levels and increasing the risk of incorrect dosing, which can result in adverse patient outcomes.

Innovation Solution

A system that correlates population model information with sedation-level monitoring to create a patient-specific model, using drug modeling combined with depth of anesthesia monitoring to estimate future sedation levels and drug sensitivity, allowing for the calculation of a drug sensitivity index (DSI) that predicts a patient's response to anesthesia.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If population models are used to predict patient sedation level, then information about average patient responses is provided, but accuracy for individual patients deteriorates

Engineering Contradiction:

Improveinformation about average patient responsesVSAvoidaccuracy for individual patients

Core Design Contradiction:

Loss of informationVSMeasurement precision

Solution Approach 1:

The patent transitions from population-level average data to patient-specific localized data by using the individual patient's depth of anesthesia monitoring data to calculate their unique sensitivity index, thereby improving prediction accuracy for that specific patient

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system performs preliminary calculations of the patient's sensitivity index using early monitoring data before critical dosing decisions need to be made, enabling proactive adjustment of anesthetic administration based on predicted individual response

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If depth of anesthesia monitoring is used, then current sedation level is determined, but proactive information about future state is not provided

Engineering Contradiction:

Improvecurrent sedation level determinationVSAvoidproactive information about future state

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The system uses the patient-specific sensitivity index to predict future sedation levels and response to upcoming anesthetic doses before those doses are administered, providing clinicians with advance information to optimize dosing decisions

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors depth of anesthesia and compares actual responses with predicted responses based on the sensitivity index, creating a feedback loop that refines and updates the predictive model for ongoing anesthesia management

Inventive Principle:

Principle #23Feedback

3Measurement precision

If clinicians rely on responsive data from depth of anesthesia monitoring, then current sedation level is known, but correct dosing decisions are difficult to make

Engineering Contradiction:

Improvecurrent sedation level assessmentVSAvoidanesthesia administration decision making

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system calculates the patient-specific sensitivity index in advance and uses it to predict future sedation levels, allowing clinicians to make informed dosing decisions before administering anesthetic drugs rather than reacting after effects are observed

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patient-specific sensitivity index acts as an intermediary parameter that bridges the gap between population model predictions and individual patient responses, translating complex monitoring data into a simple multiplier that guides dosing decisions

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS9649063B2Point of care measurement of patient sensitivity to anesthetics

Publication Date: 2017.05.16 GE PRECISION HEALTHCARE LLC

AI summary

A method and system for monitoring a patient under anesthesia involves determining a drug sensitivity index for the patient. Patient demographic information and amount of anesthetic information is obtained, wherein the amount of anesthetic information includes each drug administered to the patient and the dose amount thereof. An effect site concentration, which represents a total anesthetic concentration in a patient's brain, is then estimated based on the anesthetic information. An expected response is determined based on the demographic information and the effect site concentration. Physiological data is recorded from sensors mounted to a patient, and a depth of anesthesia is determined based on physiological data. An actual response of the patient is then determined based on the depth of anesthesia and the effect site concentration. Finally, a drug sensitivity index is determined for the patient by comparing the expected response to the actual response.