Real-time Anomaly Detection in Remote Care Plan Support

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Solution Overview

Problem

Current healthcare systems face inefficiencies in reporting and analyzing patient health data, requiring manual reporting and physician review, which delays identification of anomalies and hampers timely care plan adjustments.

Innovation Solution

A secure intelligent networked architecture with a specialized hardware processor and memory for real-time anomaly detection, using serverless compute functionality and machine learning to automatically identify and notify anomalies, integrate with electronic healthcare records, and adjust care plans based on patient-specific data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Speed

If manual reporting and physician review methods are used, then system complexity is reduced, but response time and anomaly detection speed deteriorate

Engineering Contradiction:

Improveanomaly detection speedVSAvoidsystem complexity

Core Design Contradiction:

SpeedVSDevice complexity

Solution Approach 1:

The system employs automated anomaly detection algorithms and machine learning models that autonomously analyze patient data without requiring manual physician review for every data point. The intelligence embedded in the system enables self-service detection and classification of anomalies, significantly improving detection speed while maintaining manageable complexity through automation.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical review processes with electronic automated analysis systems. Machine learning models and computational algorithms substitute for human physician review, enabling rapid processing of patient data while reducing the time-consuming nature of manual analysis.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of time

If real-time data processing and anomaly detection are implemented, then care plan adjustment timeliness is improved, but computational resource requirements increase

Engineering Contradiction:

Improvecare plan adjustment delayVSAvoidcomputational resource consumption

Core Design Contradiction:

Loss of timeVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary processing and preprocessing of patient data as it is collected, preparing it for anomaly detection in advance. By pre-processing data streams and maintaining ready-to-analyze formats, the system reduces the computational burden during critical real-time decision moments, enabling timely care plan adjustments without excessive resource consumption.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system applies anomaly detection selectively to data points that require attention rather than processing every single data point with full computational intensity. By focusing computational resources on potentially anomalous or clinically significant measurements, the system achieves timely detection while optimizing resource utilization.

Inventive Principle:

Principle #16Partial or excessive action

3Measurement precision

If comprehensive patient data collection and analysis are performed, then care plan precision is improved, but data processing complexity increases

Engineering Contradiction:

Improvepatient data analysis accuracyVSAvoiddata processing complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments patient data into distinct categories and processing streams based on data type, source, and clinical relevance. By dividing comprehensive data sets into manageable segments that can be processed independently through specialized algorithms, the system maintains high analysis precision while reducing overall processing complexity through modular organization.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent employs universal data processing frameworks and standardized analysis pipelines that can handle multiple data types and sources through a common architecture. This multi-functional approach enables comprehensive data analysis without proportionally increasing complexity, as the same processing infrastructure serves multiple analytical purposes.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS12261871B2Real-time precision care plan support during remote care management

Publication Date: 2025.03.25 ELECTRONIC CAREGIVER INC

AI summary

Provided herein are exemplary embodiments including a secure intelligent networked architecture for real-time precision care plan remote support including a secure intelligent data receiving agent having a specialized hardware processor and a memory, the secure intelligent data receiving agent configured to automatically receive a digital data element over a network from a Bluetooth® equipped peripheral device, the digital data element representing an output in response to a predetermined plan, the secure intelligent data receiving agent caching the digital data element within a non-relational database for short term storage and the secure intelligent data receiving agent configured to process the digital data element using a serverless compute functionality and configured with logic for anomaly detection.