Your browser doesn't support javascript.
Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform.
Schulz, Wade L; Durant, Thomas J S; Torre, Charles J; Hsiao, Allen L; Krumholz, Harlan M.
  • Schulz WL; Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, United States.
  • Durant TJS; Center for Outcomes Research & Evaluation, Yale New Haven Hospital, New Haven, CT, United States.
  • Torre CJ; Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, United States.
  • Hsiao AL; Center for Outcomes Research & Evaluation, Yale New Haven Hospital, New Haven, CT, United States.
  • Krumholz HM; Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, United States.
J Med Internet Res ; 22(5): e18707, 2020 05 28.
Article in English | MEDLINE | ID: covidwho-678506
ABSTRACT
The ongoing coronavirus disease outbreak demonstrates the need for novel applications of real-time data to produce timely information about incident cases. Using health information technology (HIT) and real-world data, we sought to produce an interface that could, in near real time, identify patients presenting with suspected respiratory tract infection and enable monitoring of test results related to specific pathogens, including severe acute respiratory syndrome coronavirus 2. This tool was built upon our computational health platform, which provides access to near real-time data from disparate HIT sources across our health system. This combination of technology allowed us to rapidly prototype, iterate, and deploy a platform to support a cohesive organizational response to a rapidly evolving outbreak. Platforms that allow for agile analytics are needed to keep pace with evolving needs within the health care system.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Medical Informatics / Coronavirus Infections / Delivery of Health Care / Public Health Surveillance / Betacoronavirus Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: 18707

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Medical Informatics / Coronavirus Infections / Delivery of Health Care / Public Health Surveillance / Betacoronavirus Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: 18707