Interactive Opioid Tapering Glide Paths for Personalized Dose Reduction
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Solution Overview
Problem
Current opioid tapering methods involve a one-size-fits-all approach, leading to high failure rates due to lack of personalized adjustment for withdrawal symptoms, anxiety, and side effects, with only 33% of patients successfully tapering off opioids and 34% resuming use within 6 months.
Innovation Solution
A system utilizing machine learning algorithms to generate personalized, non-linear glide paths for opioid dosage reduction, incorporating patient monitoring data on withdrawal scales and anxiety, with real-time adjustments and recommendations for side effect management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a fixed linear reduction schedule is used for opioid tapering, then the treatment protocol is simple to implement, but the success rate is low due to lack of personalization
Solution Approach 1:
The patent transforms the static fixed linear reduction schedule into a dynamic personalized glide path that adapts to each patient's response. The system continuously monitors patient status and adjusts the dosage reduction trajectory in real-time, making the treatment protocol both simple to implement (through automated algorithms) and highly personalized (through continuous adaptation to individual patient needs).
Solution Approach 2:
The patent changes the parameters of the reduction schedule from fixed values to variable parameters that are continuously adjusted based on patient monitoring data. The glide path methodology allows the reduction rate, timing, and dosage adjustments to vary according to measured patient outcomes, transforming a rigid protocol into a flexible, data-driven treatment plan.
2Reliability
If a personalized non-linear glide path is used for opioid tapering, then the tapering success rate is improved through individualization, but the system complexity increases
Solution Approach 1:
The patent implements a self-adjusting system where the personalized glide path automatically adapts to patient needs without requiring complex manual intervention. The algorithm continuously processes patient monitoring data and self-corrects the treatment trajectory, reducing the burden on clinicians while maintaining high personalization. The system serves itself by using its own data to make adjustments.
Solution Approach 2:
The patent incorporates continuous feedback loops where patient monitoring data (withdrawal symptoms, anxiety levels, side effects) is fed back into the algorithm to adjust the glide path in real-time. This feedback mechanism allows the system to maintain high personalization and success rates while automating the complexity, as the feedback-driven adjustments occur systematically rather than requiring complex manual decision-making.
3Measurement precision
If frequent patient monitoring is implemented to track withdrawal symptoms and anxiety, then personalized adjustments can be made, but the time and resource requirements increase
Solution Approach 1:
The patent replaces manual monitoring and adjustment processes with an automated computational system. The algorithm processes patient data, determines glide path adjustments, and generates recommendations automatically, substituting the mechanical time-consuming processes of manual assessment and plan modification with efficient automated calculations and decision-support generation.
Data Source
AI summary
Examples described herein generally relate to recommending drug dosage reductions for a patient. A computer system may generate an initial non-linear glide path of recommended dosages starting at an initial dosage of a drug for a patient and ending at a goal dosage at an estimated time of arrival. The system may receive periodic patient monitoring including at least one drug withdrawal scale score, anxiety scale score, and indicated side effect. The system may determine, using one or more machine learning algorithms, a revised glide path based on a data record for the patient, the at least the drug withdrawal scale score and the at least one anxiety scale score for the patient. The system may recommend at least one medication or therapy for the indicated side effect. The system may determine a prescription adjustment based on the revised glide path.