Electronic Medical Records Integrating Genetic Data Mapping
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Solution Overview
Problem
Current electronic medical records systems lack the capability to effectively manage and utilize genetic information, particularly from the human genome and microbiome, which is crucial for accurate patient treatment and management.
Innovation Solution
An electronic medical records system that intelligently selects and maps medical findings to associated genes, and vice versa, providing a graphical user interface for healthcare providers to visualize connections between medical conditions and genetic information, enabling comprehensive investigation of medical issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current electronic medical records systems are used, then basic patient record storage is maintained, but genetic information management capability is insufficient
Solution Approach 1:
The system segments genetic information into distinct categories (single-nucleotide polymorphisms, insertions/deletions, copy number variations, structural variations, chromosomal abnormalities) and stores them in separate data structures within the medical record. This allows the system to manage complex genetic data through organized modules without overwhelming the entire system architecture.
Solution Approach 2:
The system introduces a genetic information management module as an intermediary layer between existing medical record systems and genetic data sources. This intermediary component handles the complexity of genetic data parsing, validation, and integration, allowing the core medical records system to remain relatively simple while gaining genetic information capabilities.
2Measurement precision
If genetic information is integrated into patient records, then treatment precision is improved, but information management complexity increases
Solution Approach 1:
The system applies local quality by tailoring the genetic information management approach to specific clinical contexts. Different genetic data types are managed with appropriate specificity (e.g., detailed tracking of single-nucleotide polymorphisms versus broader chromosomal abnormalities), and the system can selectively display or process genetic information relevant to particular diagnoses or treatments.
Solution Approach 2:
The system incorporates feedback mechanisms that automatically interpret genetic findings and provide recommendations for updated treatments or diagnostic approaches. This feedback loop helps manage information complexity by automatically processing and prioritizing genetic data, reducing the manual effort required to interpret complex genetic information while maintaining high diagnostic precision.
Data Source
AI summary
Methods, apparatuses, and systems having an electronic medical records system which intelligently selects medical findings or related information and maps them to associated genes. An electronic medical records system intelligently selects genes and maps them to associated medical findings or other related information.