AI Medical Document Scanning for Unified Patient Decline Reporting
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Solution Overview
Problem
Current healthcare systems face challenges in managing and interpreting fragmented patient data across multiple facilities, leading to inefficiencies, errors, and potential adverse patient outcomes due to incomplete or outdated information, lack of unified data repositories, and inadequate security measures.
Innovation Solution
A system that collects patient data from multiple sources, uses artificial intelligence to analyze and consolidate it, generating real-time reports with trend identification and conflict resolution, while ensuring robust security and adaptability across diverse healthcare settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If patient data is stored and managed in a fragmented manner across different healthcare facilities and platforms, then data security and access control can be maintained at individual facility levels, but data consolidation and real-time access become difficult, leading to delays and incomplete information
Solution Approach 1:
The patent introduces a centralized data aggregation platform that acts as an intermediary between multiple healthcare facilities and providers. This platform receives data from various sources (hospitals, clinics, laboratories, imaging centers) through standardized interfaces and consolidates it into a unified patient record, enabling real-time access without compromising individual facility security protocols
Solution Approach 2:
The system implements a universal data repository that can accommodate multiple data formats and sources (structured databases, PDFs, voice calls, emails, physical documents) through a single interface. This multi-functional approach allows consolidation of diverse healthcare data types while maintaining security through role-based access control at the platform level
2Adaptability or versatility
If traditional communication methods such as phone calls, faxes, and emails are used to compile patient data, then data can be exchanged between facilities, but delays and risks of data miscommunication or loss occur, adversely affecting timeliness and reliability
Solution Approach 1:
The patent replaces traditional mechanical communication methods (phone calls, faxes, emails) with an automated electronic data aggregation system. The platform uses standardized digital interfaces and protocols to exchange data between facilities, eliminating manual transmission errors and ensuring data integrity through systematic validation and confirmation processes
Solution Approach 2:
The system implements feedback mechanisms where data received from various sources is automatically validated, confirmed, and tracked. The platform provides real-time status updates on data collection and consolidation, allowing providers to verify data completeness and accuracy, thereby reducing miscommunication risks
3Ease of operation
If manual data input into various systems is performed by healthcare workers, then data can be entered into different platforms, but the process becomes time-consuming and prone to errors, leading to incorrect diagnoses and treatments
Solution Approach 1:
The patent implements automated data collection where the system itself retrieves and consolidates patient information from multiple sources without requiring manual data entry by healthcare workers. The platform automatically queries connected systems, extracts relevant data, and populates unified patient records, significantly reducing time consumption and human error while maintaining ease of access for providers
4Loss of information
If comprehensive patient data from multiple sources is consolidated, then complete medical history becomes available, but the complexity of managing and interpreting diverse data formats and sources increases
Solution Approach 1:
The patent segments the complex data consolidation process into distinct functional modules: data collection from various sources, data validation, data normalization to standard formats, data storage in unified records, and data presentation to providers. This modular architecture manages complexity by handling each aspect separately while maintaining overall system integration and completeness of medical history
Data Source
AI summary
The invention provides a system and method for consolidated patient data reporting in healthcare facilities utilizing artificial intelligence for decline and terminal status assessment. The system includes a data input module configured to receive patient data from multiple healthcare providers across different facilities in various formats, and a processing module for processing and amalgamating stored patient data. An artificial intelligence module utilizes optical character recognition, natural language processing, and specialized algorithms to scan unstructured medical documents and extract pertinent patient data focused on deterioration markers including weight trends, laboratory results, symptom patterns, functional changes, and healthcare utilization patterns. A reporting module generates consolidated patient data reports providing real-time updates and summaries highlighting significant decline trends and terminal indicators. The system includes modal-based human-in-the-loop validation, comprehensive HIPAA compliance measures, and tiered access control for enhanced security and data integrity.