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Workflow‑Based Information Management Framework for Multicenter Research Studies: Design and Development.

Hasan Sulaeman1, Mars Stone1, Roberta Bruhn1

  • 1Vitalant Research Institute, 360 Spear Street, San Francisco, CA, 94115, United States, 1 (415) 923-5771.

Online Journal of Public Health Informatics
|April 20, 2026
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Summary
This summary is machine-generated.

The Workflow-based Information Management (WIM) framework offers a flexible, open-source solution for managing complex biological and health research data. It enhances reproducibility and speeds up study execution for public health insights.

Keywords:
ETLdata infrastructuredata managementdata systemextract transform loadlarge studiesmulticenter studiesopen source

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Area of Science:

  • Biological and health research
  • Epidemiology
  • Public health

Background:

  • Modern biological and health research generates vast amounts of data.
  • The COVID-19 pandemic highlighted the need for adaptable data infrastructures.
  • Timely insights from data are crucial for public health policy.

Purpose of the Study:

  • To describe the Workflow-based Information Management (WIM) framework.
  • To present WIM as a flexible system for epidemiologic workflows.
  • To support data-intensive research projects.

Main Methods:

  • Developed WIM as a modular, workflow-oriented framework.
  • Built WIM using the open-source R programming language.
  • Emphasized reproducibility, adaptability, and transparency in WIM's design.

Main Results:

  • WIM managed over 3.7 million records from 17 organizations.
  • The framework adapted to diverse data types and analytical needs.
  • WIM facilitated efficient data processing, analysis, and reporting.

Conclusions:

  • WIM offers a flexible, open-source approach to research information management.
  • The framework supports reproducible analysis and scalable research operations.
  • WIM provides adaptable data infrastructure for epidemiologic research and public health.