Visualizing Patterns of Drug Prescriptions with EventFlow: A Pilot Study of Asthma Medications in the Military Health System

Abstract

The Food and Drug Administration and Department of Defense were interested in detecting sub-optimal use of long-acting beta-agonists (LABAs) in asthmatics within the Military Health System (MHS). Visualizing the patterns of asthma medication use surrounding a LABA prescription is a quick way to detect possible sub-optimal use for further evaluation. The US Army, Office of the Surgeon General, Pharmacovigilance Center (PVC) selected a random sample of 100 asthma patients under age 65 with a new LABA prescription from January 1, 2006-March 1, 2010 in MHS healthcare claims. Analysis was conducted in EventFlow, a novel interactive visualization tool being developed by the University of Maryland Human Computer Interaction Lab (HCIL) to display and summarize timepoint and interval data. EventFlow groups individuals that share the same sequence of medications and displays the average interval times between events. We found that EventFlow was effective in uncovering clinically relevant patterns in the data. Epidemiologists reported that EventFlow was a powerful tool for rapidly visualizing possible patterns of sub-optimal LABA use that can be targeted for intervention.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2013
Accession Number
ADA588017

Entities

People

  • Ben Shneiderman
  • Catherine Plaisant
  • Jeff Millstein
  • Krist Wongsuphasawat
  • Megan Monroe
  • Rongjian Lan
  • Sigfried Gold
  • Tamra E. Meyer
  • Trinka S. Coster

Organizations

  • Office of the Inspector General, U.S. Department of Defense

Tags

DTIC Thesaurus Topics

  • Case Studies
  • Databases
  • Diseases And Disorders
  • Drug Therapy
  • Health Services
  • Human-Computer Interaction
  • Intervals
  • Language
  • Maryland
  • Military Medicine
  • Pilot Studies
  • Relational Databases
  • Sequences
  • Therapy
  • Universities
  • Visualizations

Fields of Study

  • Medicine

Readers

  • Distributed Systems and Data Platform Development
  • Medical or Health Care Field.
  • Neurological Diseases/Conditions/Disorders