Optimizing Travel Time to Outpatient Interventional Radiology Procedures in a Multi-Site Hospital System Using a Google Maps Application. Academic Article uri icon

Overview

abstract

  • The purpose of this study is to determine whether a custom Google Maps application can optimize site selection when scheduling outpatient interventional radiology (IR) procedures within a multi-site hospital system. The Google Maps for Business Application Programming Interface (API) was used to develop an internal web application that uses real-time traffic data to determine estimated travel time (ETT; minutes) and estimated travel distance (ETD; miles) from a patient's home to each a nearby IR facility in our hospital system. Hypothetical patient home addresses based on the 33 cities comprising our institution's catchment area were used to determine the optimal IR site for hypothetical patients traveling from each city based on real-time traffic conditions. For 10/33 (30%) cities, there was discordance between the optimal IR site based on ETT and the optimal IR site based on ETD at non-rush hour time or rush hour time. By choosing to travel to an IR site based on ETT rather than ETD, patients from discordant cities were predicted to save an average of 7.29 min during non-rush hour (p = 0.03), and 28.80 min during rush hour (p < 0.001). Using a custom Google Maps application to schedule outpatients for IR procedures can effectively reduce patient travel time when more than one location providing IR procedures is available within the same hospital system.

publication date

  • October 1, 2018

Research

keywords

  • Maps as Topic
  • Mobile Applications
  • Outpatients
  • Radiology, Interventional
  • Travel

Identity

PubMed Central ID

  • PMC6148822

Scopus Document Identifier

  • 85042233137

Digital Object Identifier (DOI)

  • 10.1007/s10278-018-0054-2

PubMed ID

  • 29464433

Additional Document Info

volume

  • 31

issue

  • 5