Medical Record Document Processor for Real-Time Health Prediction
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Solution Overview
Problem
Current healthcare systems are ineffective in predicting a patient's health condition in real-time, particularly in intensive care units, as discharge summaries are not available during medical observation, limiting the usefulness of historical data for timely predictions.
Innovation Solution
A system and method that utilize a document processor to extract headings and words from medical records, combined with physiological parameter measurements, to predict health conditions using historical and current medical data through a computer program product.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If discharge summaries are used to predict health conditions, then historical medical data can be utilized, but the prediction cannot be performed in real-time during medical observation
Solution Approach 1:
The system performs preliminary extraction and processing of medical record data during the patient's stay, preparing structured information in advance so that when combined with real-time physiological data, predictions can be made immediately without waiting for discharge summaries
Solution Approach 2:
The system introduces an intermediary processing layer that extracts relevant information from unstructured medical records and transforms it into a format that can be quickly analyzed alongside real-time sensor data, enabling timely predictions without requiring the final discharge summary
2Measurement precision
If comprehensive medical records are analyzed to improve prediction accuracy, then more historical data is available, but the system complexity increases
Solution Approach 1:
The system extracts only the most relevant features and keywords from comprehensive medical records using predefined rules and algorithms, separating essential predictive information from unnecessary details, thereby maintaining high prediction accuracy while reducing processing complexity
Solution Approach 2:
The analysis process is divided into distinct segments: extraction of medical record data, extraction of physiological parameter data, feature selection, and prediction. This segmentation allows each component to be optimized independently, managing overall system complexity while comprehensively analyzing medical data
Data Source
AI summary
According to embodiments illustrated herein, there is provided a system for predicting a health condition of a first patient. The system includes a document processor configured to extract one or more headings from one or more medical records of the first patient based on one or more predefined rules. The document processor is further configured to extract one or more words from one or more phrases written under each of the extracted one or more headings, wherein the one or more phrases correspond to documentation of the observation of the first patient by a medical attender. The system further includes one or more processors configured to predict the health condition of the first patient based on a count of the one or more words in historical medical records and the one or more medical records.