Implantable Infusion Device Dosing Evaluation via Symptom Analysis
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Solution Overview
Problem
Current implantable infusion systems face challenges in identifying inappropriate dosing of therapeutic agents, which can occur due to programming errors, incorrect concentrations, or patient-specific sensitivities, making it difficult to determine the source of under- or overdosing despite functional devices and catheters.
Innovation Solution
A system and method that utilize patient symptoms associated with specific therapeutic agents to determine appropriate dosing, allowing for improved detection of inappropriate dosing by interrogating the infusion device for potential sources such as malfunctions or programming errors, and calculating probabilities for each potential source.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the infusion device is programmed to deliver drug at a controlled rate, then the device can ensure appropriate dosing, but it cannot identify the source of inappropriate dosing when programming errors or patient sensitivities occur
Solution Approach 1:
The system segments the dosing evaluation process into multiple independent components: device functionality assessment, catheter status monitoring, drug concentration verification, and patient symptom analysis. Each component can be evaluated separately to identify the specific source of inappropriate dosing, transforming a monolithic diagnostic challenge into manageable discrete evaluations.
Solution Approach 2:
The system introduces an external device as an intermediary between the implantable infusion device and the healthcare provider. This intermediary collects data from multiple sources including device parameters, catheter status, and patient symptoms, then integrates this information to identify the source of dosing issues, acting as a mediator that synthesizes information from otherwise disconnected evaluation domains.
2Reliability
If the device includes electronics and sensors to monitor malfunctions, then device failures can be detected, but inappropriate dosing due to programming errors or patient sensitivity cannot be identified
Solution Approach 1:
The system creates a multi-functional evaluation framework that uses the existing malfunction monitoring capabilities while adding dosing appropriateness assessment. The same data collection infrastructure monitors both device failures and dosing issues, and the analysis process evaluates multiple hypotheses including programming errors, catheter problems, and patient sensitivities, making the system universal in addressing diverse dosing problems.
Solution Approach 2:
The system implements feedback loops where patient symptoms and device performance data are continuously monitored and fed back into the dosing evaluation process. This feedback mechanism allows the system to adjust its assessment of dosing appropriateness based on actual patient response and device behavior, enabling identification of inappropriate dosing that would otherwise be invisible to standard malfunction monitoring.
3Ease of operation
If the healthcare provider sets the infusion parameters, then the parameters may appear appropriate, but inappropriate dosing can still occur due to programming errors or incorrect concentration
Solution Approach 1:
The system performs preliminary evaluations of dosing appropriateness by comparing programmed parameters against expected outcomes and patient-specific factors before inappropriate dosing occurs. It proactively assesses whether the programmed infusion rate and drug concentration are appropriate for the patient's condition, identifying potential programming errors or concentration issues before they result in actual dosing problems.
Solution Approach 2:
The system replaces reliance on manual parameter setting judgment with an automated computational evaluation process. Instead of depending solely on the healthcare provider's expertise to set appropriate parameters, the system uses algorithms to objectively assess whether the programmed parameters will result in appropriate dosing, substituting mechanical/judgment-based parameter setting with systematic computational analysis.
Data Source
AI summary
A method for evaluating dosing from an implanted infusion system that includes receiving input regarding the identity of a therapeutic agent into an external device. The method further includes displaying on the external device a predetermined set of symptoms associated with the therapeutic agent; receiving input into the external device regarding with which of the symptoms the patient presents; and determining whether the therapeutic agent is being delivered, or has been delivered, at an appropriate dose based on the input identity of the therapeutic agent and the input symptoms.