Körpeoğlu, E;
Kurtz, Z;
Kılınç-Karzan, F;
Kekre, S;
Basu, PA;
(2014)
Business Analytics Assists Transitioning Traditional Medicine to Telemedicine at Virtual Radiologic.
Interfaces
, 44
(4)
pp. 393-410.
10.1287/inte.2014.0752.
Preview |
Text
vRad-Interfaces_Final.pdf - Accepted Version Download (1MB) | Preview |
Abstract
Virtual Radiologic (vRad), the largest teleradiology company in the United States, faces the difficult problem of matching more than 400 radiologists with time-varying and seasonal demand. In addition to the constraints that traditional medical facilities face, vRad is subject to supply and demand requirements that are unique to the teleradiology business environment. In this paper, we present a forecasting and capacity-planning model that more accurately assesses demand and plans system capacity to provide better service to vRad’s customers. We discuss the underlying reasons for improvement and quantify the impact on vRad’s entire system. We explain managerial insights that will help both vRad and other companies in the service sector with similar service-response requirements and demand patterns. We also highlight the implementation challenges our teams faced.
Type: | Article |
---|---|
Title: | Business Analytics Assists Transitioning Traditional Medicine to Telemedicine at Virtual Radiologic |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1287/inte.2014.0752 |
Publisher version: | https://doi.org/10.1287/inte.2014.0752 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | business analytics, capacity planning, forecasting, optimization, healthcare industry |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management |
URI: | https://discovery.ucl.ac.uk/id/eprint/10083818 |
Archive Staff Only
![]() |
View Item |