{"id":5,"date":"2022-02-03T10:39:42","date_gmt":"2022-02-03T15:39:42","guid":{"rendered":"https:\/\/ise.ncsu.edu\/ari-fhir\/home\/"},"modified":"2025-06-02T09:39:35","modified_gmt":"2025-06-02T13:39:35","slug":"data-factories-home","status":"publish","type":"page","link":"https:\/\/ise.ncsu.edu\/ari-fhir\/","title":{"rendered":"Data Factories for Real-time Public Health Bio-Surveillance"},"content":{"rendered":"\n
<\/span>
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Data Factories for Real-time Public Health Bio-Surveillance<\/span><\/span><\/h2>\n<\/div><\/div>\n\n\n\n

Data Factories for Real-Time Public Health Bio-Surveillance<\/h3>\n\n\n\n

In this Data Factories project, you explore how to build and use a new kind of tool called a data factory. This factory helps you track public health in real time by using a system called Fast Healthcare Interoperability Resources, or FHIR.<\/p>\n\n\n\n

FHIR, created by a group called HL7, lets you share health data electronically in a modern, web-based way. As a result, this system is changing how doctors and public health teams use data.<\/p>\n\n\n\n

Purpose of the Data Factories project<\/h3>\n\n\n\n

Your main goal is to use FHIR to monitor health trends as they happen. Specifically, you focus on illnesses that affect the lungs and breathing.<\/p>\n\n\n\n

To do this, you build a data factory that works with electronic health records, or EHRs. This factory lets you collect, clean, and study both clinical and lab data quickly.<\/p>\n\n\n\n

In this project, you track three key things:<\/p>\n\n\n\n

    \n
  • When patients visit the hospital with signs of respiratory illness.<\/li>\n\n\n\n
  • When patients are diagnosed with flu or other viruses<\/span><\/li>\n\n\n\n
  • When labs test for the flu or similar viruses.<\/li>\n<\/ul>\n\n\n\n

    You use real hospital data from MedStar Health, which runs 10 hospitals in Maryland, Virginia, and Washington, D.C.<\/p>\n\n\n\n

    Project Framework<\/h3>\n\n\n\n

    To make this work, you follow three main steps:<\/p>\n\n\n\n

      \n
    • First, you explore the data and figure out what to collect. You also decide which health signs to track.<\/li>\n\n\n\n
    • Next, you build and run a pipeline using FHIR. This pipeline helps you pull data from the hospitals in near real time.<\/li>\n\n\n\n
    • Finally, you test the system. You check if it works well, gives accurate results, and provides data fast enough to be useful.<\/li>\n<\/ul>\n\n\n\n

      Along the way, you use a flowchart to show how everything fits together. This chart helps you see how data moves from records to insights.<\/p>\n\n\n\n

      Executive Summary<\/h3>\n\n\n\n

      The framework includes the research questions, phases, tasks, and methods.<\/p>\n\n\n

      \n
      \"A<\/figure>\n<\/div>\n\n\n

      FHIR Flowchart<\/h3>\n\n\n\n

      The workflow of using FHIR for public health surveillance.<\/p>\n\n\n

      \n
      \"The<\/figure>\n<\/div>\n\n\n

      Why This Matters<\/h3>\n\n\n\n

      Because of illnesses like COVID-19 and the flu, it\u2019s more important than ever to track public health fast. Using a data factory powered by FHIR, you can help health leaders react quickly.<\/p>\n\n\n\n

      In the long run, this project shows how technology can support smarter and faster public health work.<\/p>\n","protected":false},"excerpt":{"rendered":"

      Data Factories for Real-Time Public Health Bio-Surveillance In this Data Factories project, you explore how to build and use a new kind of tool called…<\/p>\n","protected":false},"author":214,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-landing.php","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-5","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nData Factories<\/title>\n<meta name=\"description\" content=\"Explore how data factories using FHIR technology enable real-time public health bio-surveillance of respiratory illnesses\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ise.ncsu.edu\/ari-fhir\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Data Factories\" 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