Virtual Assistant for Patient Data Collection and Genetic Testing

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Current methods for collecting comprehensive patient data, including family, medical, lifestyle, and environmental exposure history, are inefficient and often not conducted due to lack of time, insufficient reimbursement, and limited training among physicians, hindering the adoption of precision medicine and genetic testing.

Innovation Solution

A conversational Virtual Assistant with Decision Support capabilities, utilizing natural language processing and Medi-tainment to engage patients in a user-friendly manner, collects and analyzes data to provide actionable recommendations for genetic testing and nutritional counseling, integrating with Electronic Medical Records for efficient data transfer and analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If physicians collect comprehensive patient data manually, then data accuracy is improved, but time consumption and cost increase significantly

Engineering Contradiction:

Improvedata accuracyVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system enables patients to self-collect their own health data through automated interactions with the virtual assistant, eliminating the need for physician intervention in data collection while maintaining high accuracy through structured questioning and validation algorithms

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The manual mechanical process of physician-patient interviews is replaced with an automated virtual assistant system using natural language processing and decision support algorithms to collect and analyze patient data

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If physicians provide genetic counseling and interpret genetic test results, then patient care quality is improved, but physician training requirements and complexity increase

Engineering Contradiction:

Improvepatient care qualityVSAvoidphysician training requirements

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

A virtual assistant with embedded decision support functionality serves as an intermediary between physicians and complex genetic counseling tasks, handling data collection, analysis, and recommendation generation while physicians focus on patient communication and decision-making

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system performs self-analysis of patient data and self-generation of genetic testing recommendations using built-in decision support algorithms, eliminating the need for physicians to manually interpret complex genetic data

Inventive Principle:

Principle #25Self-service

3Loss of information

If comprehensive health history data is collected from patients, then precision medicine capabilities are improved, but patient engagement difficulty and data collection complexity increase

Engineering Contradiction:

Improvecomprehensive health historyVSAvoidpatient engagement difficulty

Core Design Contradiction:

Loss of informationVSEase of operation

Solution Approach 1:

The virtual assistant dynamically adapts its questioning strategy based on patient responses, adjusting the depth and direction of inquiries in real-time to maintain engagement while comprehensively collecting necessary health history data

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes interaction parameters such as question complexity, tone, and pacing based on patient engagement levels and response patterns, optimizing the balance between data completeness and patient comfort

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11404170B2Method and system for patients data collection and analysis

Publication Date: 2022.08.02 SOAP INC

AI summary

A conversational and embodied Virtual Assistant (VA) with Decision Support (DS) capabilities that can simulate and improve upon information gathering sessions between clinicians, researchers, and patients. The system incorporates a conversational and embodied VA and a DS and deploys natural interaction enabled by natural language processing, automatic speech recognition, and an animation framework capable of rendering character animation performances through generated verbal and nonverbal behaviors, all supplemented by on-screen prompts.