Neurostimulation Programming Using Freeform Patient Feedback
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Solution Overview
Problem
Existing neurostimulation systems face delays in implementing new or improved treatments due to infrequent clinician oversight and lack of clear information on treatment results, with patients struggling to provide detailed feedback on treatment efficacy.
Innovation Solution
A system utilizing natural language processing to analyze freeform text inputs from patients to identify their state and the neurostimulation treatment state, enabling dynamic programming adjustments and alerts or recommendations based on sentiment analysis and device data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If neurostimulation devices provide patient capability to switch between programs or change stimulation levels, then patient autonomy and treatment customization are improved, but it becomes unclear whether such changes are beneficial and result in improvement to patient's medical condition
Solution Approach 1:
The system implements feedback by collecting patient feedback through freeform text inputs and analyzing them using natural language processing. The system processes this text data to determine treatment efficacy and provides feedback to both patients and clinicians about whether program changes are beneficial, thereby resolving the information loss problem while maintaining patient autonomy
2Adaptability or versatility
If advanced neurostimulation programs are made available, then treatment capability is improved, but implementation delay increases due to infrequent clinician oversight
Solution Approach 1:
The system enables self-service by allowing patients to provide feedback through freeform text inputs and by automatically processing this feedback using natural language processing algorithms. This automated system continuously monitors treatment efficacy without requiring frequent clinician intervention, thereby reducing implementation delays while maintaining advanced treatment capabilities
Solution Approach 2:
The system replaces the mechanical system of frequent manual clinician reviews with an automated natural language processing system that continuously analyzes patient feedback and determines treatment efficacy, thereby eliminating implementation delays associated with infrequent clinician oversight
3Measurement precision
If detailed feedback collection from patients is implemented, then treatment assessment accuracy is improved, but patient burden and complexity of interaction increase
Solution Approach 1:
The system changes the parameter of feedback collection from structured formats to freeform text inputs. This allows patients to provide detailed feedback in their own words without being constrained by predefined response options, thereby maintaining high treatment assessment accuracy while significantly reducing patient interaction complexity
Data Source
AI summary
Systems and techniques are disclosed to evaluate a neurostimulation treatment provided from a neurostimulation device, based on freeform text analysis. In an example, a system or device to evaluate a neurostimulation treatment provided from a neurostimulation device is configured to perform operations that: obtain text content, originating from text or voice input of a human patient, which relates to a state of a human patient; identify a state of the human patient from natural language processing of the text content; obtain device data from the neurostimulation device; identify a state of the neurostimulation treatment of the human patient from the device data; associate the identified state of the human patient to the identified state of the neurostimulation treatment; and initiate an action for the neurostimulation treatment, based on the identified state of the human patient that is associated with the identified state of the neurostimulation treatment.