Medical Imaging Analytics Engine for Operational Efficiency

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Medical imaging data processing in healthcare settings faces challenges due to the complexity and variability of clinical data, leading to inefficiencies in resource allocation and management decisions, as advanced data analytics and statistical analysis are beyond the skills of most medical practitioners and existing solutions require significant overhead.

Innovation Solution

An information system is developed to automatically collect, analyze, and visualize medical imaging data using algorithms that combine business, operational, and clinical data, employing confidence and impact scoring to identify anomalies and opportunities for improvement, presented through user-friendly dashboards for actionable insights.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If advanced data analytics and statistical analysis are applied to medical imaging data, then operational efficiency and resource allocation improve, but system complexity and implementation difficulty increase

Engineering Contradiction:

Improveoperational efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary analytics engine that sits between the medical imaging data sources and the users. This engine automatically performs complex statistical analysis and data processing, transforming raw imaging data into actionable insights without requiring end users to possess advanced analytical skills. The intermediary handles the complexity internally while presenting simplified results to users.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system implements self-service capabilities where the analytics engine automatically detects data quality issues, selects appropriate analytical methods, and generates recommendations without requiring manual configuration or expert intervention. The system serves itself by autonomously performing data preprocessing, analysis, and result generation, reducing the burden on users while maintaining high operational efficiency.

Inventive Principle:

Principle #25Self-service

2Measurement precision

If comprehensive clinical data collection is performed across multiple sources, then data completeness and analysis accuracy improve, but data processing time and computational resources increase

Engineering Contradiction:

Improvedata completenessVSAvoiddata processing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary actions by pre-processing and validating data as it is collected from multiple clinical sources. Data quality checks, normalization, and initial analysis are conducted during the data ingestion phase rather than during final analysis, reducing the computational burden and processing time when comprehensive data is needed for decision-making.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent segments the data collection and processing workflow into distinct modular stages: data ingestion, validation, normalization, analysis, and reporting. Each stage handles specific tasks independently, allowing parallel processing of multiple data sources and enabling the system to manage comprehensive data collection without proportionally increasing overall processing time.

Inventive Principle:

Principle #1Segmentation

3Productivity

If automated analytics systems are deployed to reduce manual analysis, then productivity and consistency improve, but initial implementation cost and technical requirements increase

Engineering Contradiction:

Improveanalysis throughputVSAvoidimplementation ease

Core Design Contradiction:

ProductivityVSEase of manufacture

Solution Approach 1:

The analytics engine is designed with universal capabilities that can handle multiple types of medical imaging data and analytical tasks through a single unified platform. The system performs diverse functions including data validation, statistical analysis, anomaly detection, and recommendation generation, eliminating the need for separate specialized systems and reducing overall implementation complexity despite the advanced capabilities provided.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS11783262B2Automatic detection and generation of medical imaging data analytics

Publication Date: 2023.10.10 CANON MEDICAL SYST CORP

AI summary

An information system and user interface to enable the analysis of clinical data for operational improvement and issue identification in medical imaging procedures is disclosed. In an example, opportunity and usage analytics are generated from relevant imaging procedure data (e.g., radiology procedure data) through operations including: obtaining clinical data that indicates usage of imaging resources to perform medical imaging procedures; analyzing the usage of the imaging resources from the clinical data, to identify values of opportunities for predicted changes to the usage of the imaging resources; and generating a visualization of the values of the opportunities for output in a graphical user interface, the visualization indicating values of opportunities relative to past usage and predicted changes to the usage of the imaging resources. Further examples also enable a detailed visualization and interaction with data for a particular opportunity in relation to medical facilities, organizations, modalities, and staffing resources.