Cloud Medical Data Indexing for Real-Time Cross-System Access
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Solution Overview
Problem
Current systems fail to integrate patient data from clinical records and imaging studies from disparate sources in real-time and on-demand, leading to inefficiencies and delays in healthcare operations.
Innovation Solution
A method and system that utilize secure connectivity standards like HL7, FHIR, and DICOM to connect with multiple medical records databases, retrieve, index, and present patient data, including imaging records, to a user workstation or mobile device in real-time, using a graphical user interface, thereby enabling efficient access and collaboration among healthcare professionals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If patient data from multiple disparate databases is integrated in real-time, then accessibility and completeness of patient information is improved, but system complexity and data integration challenges increase
Solution Approach 1:
The patent implements a centralized indexing server that acts as an intermediary between multiple disparate medical databases (PACS, EMR, LIS, etc.) and user workstations. This indexing server maintains master indexes that map patient data across different systems without requiring direct integration between those systems, thereby reducing overall system complexity while improving data accessibility. The indexing server translates and coordinates data requests between different database formats and protocols.
Solution Approach 2:
The patent creates a universal indexing system that can handle multiple types of medical databases (PACS, EMR, LIS, RIS) through a single integrated interface. The master patient index and master study index provide universal access points that work across different data types and sources, allowing one system to serve multiple functions of data aggregation, retrieval, and coordination across heterogeneous databases.
2Loss of information
If comprehensive patient data is retrieved from multiple sources, then data completeness is improved, but retrieval time and processing delays increase
Solution Approach 1:
The patent pre-generates and maintains master indexes that contain organized metadata and access paths for patient data across multiple databases before retrieval is needed. These indexes are continuously updated and maintained in advance, allowing rapid query execution when complete patient data is needed. The preliminary organization of data relationships eliminates the need for time-consuming ad-hoc data gathering from multiple sources.
Solution Approach 2:
The patent creates simplified copies of patient data relationships through master indexes that store metadata, access paths, and organizational structures without duplicating the actual medical data. These index copies enable rapid data location and retrieval by providing pre-processed navigation structures that point to the actual data sources, significantly reducing retrieval time while maintaining data completeness.
3Loss of information
If data from multiple disparate systems is integrated, then information comprehensiveness is improved, but system security and access control challenges increase
Solution Approach 1:
The patent positions the indexing server as a security intermediary that centralizes access control functions. Instead of each database maintaining separate security protocols, the indexing server implements a unified access control system that mediates all data requests. This allows consistent security policies to be applied across all integrated databases while maintaining their individual security boundaries, improving overall system security without reducing information comprehensiveness.
4Productivity
If real-time data access is implemented across multiple databases, then workflow efficiency is improved, but network bandwidth and system resource demands increase
Solution Approach 1:
The patent extracts only the essential indexing metadata and access path information from complete medical databases, storing these lightweight index structures in a centralized location. When data access is needed, the system retrieves only the necessary index information and then queries the actual databases using these optimized paths. This extraction of essential access information reduces network bandwidth consumption compared to transferring or caching entire datasets, while still enabling real-time access efficiency.
Data Source
AI summary
The system brings together patient data both clinical records and imaging studies from disparate sources to the user workstation or mobile device in real-time and on-demand. In order to do so, the system needs to establish application layer connectivity utilizing HL7 or FHIR and DICOM for imaging. Once a secure connection is established, the system is able to search and retrieve records and present it to end user.