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Updated: Jan 9, 2026

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases
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Design and Implementation of a Scalable Clinical Data Warehouse for Resource-Constrained Healthcare Systems.

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    Summary

    Developing a scalable, privacy-preserving clinical data warehouse (NCDW) addresses challenges in integrating electronic health records (EHRs) in developing nations. This system enhances disease surveillance and public health research by enabling reliable data linkage and interoperability.

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    Area of Science:

    • Health Informatics
    • Public Health Data Management
    • Developing Country Health Systems

    Background:

    • Centralized electronic health record (EHR) repositories are vital for public health but face significant hurdles in developing countries.
    • Challenges include fragmented data, inconsistent practices, lack of unique patient identifiers, and privacy concerns, hindering data linkage and interoperability.

    Purpose of the Study:

    • To propose a scalable, privacy-preserving clinical data warehouse (NCDW) for heterogeneous EHR integration in resource-limited settings.
    • To demonstrate the framework's utility for disease surveillance and national decision-support systems.

    Main Methods:

    • Developed a wrapper-based data acquisition layer for secure, automated EHR data ingestion.
    • Implemented a Soundex algorithm for patient identity matching without unique identifiers.
    • Designed a modular data mart for disease-specific analytics, tested with a dengue fever case study in Bangladesh.
    • Evaluated database technologies (NoSQL vs. SQL) and system load capacity.

    Main Results:

    • The NCDW framework successfully integrated 1.16 million clinical records.
    • NoSQL databases outperformed SQL by 40-69% in complex query processing.
    • The system demonstrated capacity for managing 19 million daily records.
    • The dengue fever case study highlighted the data mart's utility for outbreak prediction and resource planning.

    Conclusions:

    • The proposed NCDW framework is a scalable and adaptable solution for integrating EHRs in resource-limited settings.
    • It enhances national decision-support systems and infectious disease management capabilities.
    • The framework can be modified to accommodate international standards (ICD-11, HL7 FHIR) for broader applicability in developing nations.