IDEAS home Printed from https://ideas.repec.org/a/jbh/ijsrcs/v11y2025i1id1009.html

Designing a Predictive Analytics Data Warehouse for Modern Hospital Management

Author

Listed:
  • Vishal Kumar Jaiswal

Abstract

This technical article explores the design and implementation of predictive analytics data warehouses in modern hospital management systems. The article examines the transformation of healthcare operations through sophisticated data management architectures, focusing on the integration of real-time analytics, machine learning, and advanced storage solutions. The article investigates four key areas: architectural framework design, storage layer optimization, analytics layer capabilities, and performance optimization strategies. The article analyzes how healthcare organizations are leveraging multi-layered architectural approaches to improve patient care outcomes, optimize resource allocation, and enhance operational efficiency. It also addresses critical challenges in managing structured and unstructured medical data, implementing security frameworks, and ensuring scalability while maintaining performance standards for critical healthcare operations.

Suggested Citation

  • Vishal Kumar Jaiswal, 2025. "Designing a Predictive Analytics Data Warehouse for Modern Hospital Management," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(1), pages 3309-3318, February.
    • Handle: RePEc:jbh:ijsrcs:v11:y2025:i1:id:1009
    DOI: 10.32628/CSEIT251112337
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112337
    as

    Download full text from publisher

    File URL: https://ijsrcseit.com/home/article/view/CSEIT251112337
    File Function: Article URL
    Download Restriction: no
    File URL: https://ijsrcseit.com/home/article/download/CSEIT251112337/CSEIT251112337
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.32628/CSEIT251112337?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jbh:ijsrcs:v11:y2025:i1:id:1009. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pankaj Sharma (USA) (email available below). General contact details of provider: https://ijsrcseit.com/home .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.