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Accessibility of big data in medicine: adjusting the duration of antibiotic treatment for gram-negative bloodstream infections

  • Ariel University
  • Kansas State University
  • Tel Aviv Sourasky Medical Center
  • Sheba Medical Center at Tel Hashomer

Research output: Contribution to journal › Article › peer-review

Abstract

The current article describes a process to mitigate challenges that arise when medical practitioners and data specialists operate with differing terminologies and face technological and organizational barriers in accessing and utilizing medical big data. We present a structured methodology for improving access to clinical data and apply this approach using a case study focused on optimizing antibiotic management for patients with gram-negative bloodstream infections. Using the ArchiMate® organizational architecture language, we developed a project framework that aligns strategic, business, application, and technological layers of hospital operations. Each component was used to articulate project goals, guide the implementation process, and track intervention outcomes. After implementing a real-time monitoring tool and engaging clinicians directly in the data workflow, 65% of the identified patients received targeted interventions, and the median duration of antibiotic therapy was reduced from 6 to 5 days. Our approach enabled faster decision-making, and drove meaningful organizational change–demonstrating how structured data access can lead to improved healthcare delivery and patient outcomes.

Original languageEnglish
Pages (from-to)51-65
Number of pages15
JournalHealth Systems
Volume15
Issue number1
DOIs
StatePublished - 2026

Keywords

  • ArchiMate®
  • Big data
  • antibiotic stewardship
  • gram-negative bloodstream infections
  • medical data

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