Dynamic Clinical Condition Risk Assessment Across Health Records

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Solution Overview

Problem

Existing healthcare systems face challenges in efficiently managing and integrating diverse clinical data from multiple sources, leading to incomplete, outdated, and conflicting patient information, which hinders effective clinical decision-making and patient care.

Innovation Solution

A system utilizing software agents and adaptive multi-agent platforms that dynamically integrate and analyze clinical data across various health records systems, providing contextually intelligent decision support by presenting relevant information tailored to caregivers' roles, conditions, and venues, and enabling predictive, preventative, and diagnostic services.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If diverse clinical data from multiple sources are integrated, then the completeness of patient information is improved, but the system complexity increases

Engineering Contradiction:

Improvecompleteness of patient informationVSAvoidsystem complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent introduces a standardized data interface layer and common data model that act as intermediaries between diverse clinical data sources and the analytics engine. This mediator layer translates various data formats and structures into a unified representation, enabling integration of multiple sources without proportionally increasing overall system complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system is divided into modular components including data ingestion modules, standardized interface layer, analytics engine, and presentation layers. Each module handles specific functions independently, allowing the system to scale and integrate new data sources without requiring complete system redesign, thus managing complexity through segmentation.

Inventive Principle:

Principle #1Segmentation

2Loss of time

If real-time clinical data analysis is performed, then the timeliness of decision support is improved, but the computational resources required increase

Engineering Contradiction:

Improvetimeliness of decision supportVSAvoidcomputational resources

Core Design Contradiction:

Loss of timeVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary data standardization, validation, and pre-processing as data enters the system, before analytics processing is required. Clinical decision support rules and risk models are pre-computed and cached where applicable, reducing the computational burden during real-time query execution and enabling faster response times with reduced resources.

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If contextualized decision support information is provided to caregivers, then the relevance of information is improved, but the data processing requirements increase

Engineering Contradiction:

Improverelevance of informationVSAvoiddata processing requirements

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system tailors decision support information to specific caregiver roles, clinical contexts, and patient conditions by filtering and prioritizing data locally at the point of use. Different caregiver types receive customized information sets relevant to their specific needs and responsibilities, reducing unnecessary data processing while maintaining high relevance.

Inventive Principle:

Principle #3Local quality

4Measurement precision

If multiple clinical data sources are integrated, then the accuracy of risk assessments is improved, but the difficulty of data integration increases

Engineering Contradiction:

Improveaccuracy of risk assessmentsVSAvoiddifficulty of data integration

Core Design Contradiction:

Measurement precisionVSDifficulty of detecting and measuring

Solution Approach 1:

The patent implements a universal data interface and common data model that can accommodate multiple clinical data sources with different formats and structures. This multi-functional interface layer handles diverse input types (labs, vitals, medications, demographics) through standardized protocols, reducing integration difficulty while enabling comprehensive data aggregation for accurate risk assessments.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS12417846B2Dynamically determining risk of clinical condition

Publication Date: 2025.09.16 CERNER INNOVATION INC

AI summary

Systems, methods and computer-readable media are provided for facilitating clinical decision support and managing patient population health by health-related entities including caregivers, health care administrators, insurance providers, and patients. Embodiments of the invention provide decision support services including providing timely contextual patient information including condition risks, risk factors and relevant clinical information that are dynamically updatable; imputing missing patient information; dynamically generating assessments for obtaining additional patient information based on context; data-mining and information discovery services including discovering new knowledge; identifying or evaluating treatments or sequences of patient care actions and behaviors, and providing recommendations based on this; intelligent, adaptive decision support services including identifying critical junctures in patient care processes, such as points in time that warrant close attention by caregivers; near-real time querying across diverse health records data sources, which may use diverse clinical nomenclatures and ontologies; improved natural language processing services; and other decision support services.