title: Cost-effectiveness of hub-and-spoke telestroke networks for the management of acute ischemic stroke from the hospitals' perspectives.
abstract: BACKGROUND
  A hub-and-spoke telestroke network is an effective way to extend quality acute stroke care to remote hospitals and to improve patient outcomes. This study assessed the cost-effectiveness of a telestroke network in the management of acute ischemic stroke from the perspectives of a network, a hub hospital, and a spoke hospital.
  
  
  RESULTS
  A model was developed to compare costs and effectiveness with and without a telestroke network over a 5-year time horizon. The model considered differences in rates of teleconsultations, intravenous thrombolysis, endovascular stroke therapies, and spoke-to-hub transfers. These inputs were estimated through the use of data from Georgia Health Sciences University and Mayo Clinic telestroke networks. A network model with 1 hub and 7 spokes predicted that 45 more patients would be treated with intravenous thrombolysis and 20 more with endovascular stroke therapies per year compared with no network, leading to an estimate of 6.11 more home discharges. Each year, a telestroke network was associated with $358 435 in cost savings; each spoke had $109 080 in cost savings, whereas the hub had positive costs of $405 121. However, cost sharing can be arranged so that each hospital could achieve an equal amount of cost savings ($44 804/y). Results were sensitive to the number of spokes, marginal treatment costs in spokes and rates of transfer, and endovascular stroke therapies.
  
  
  CONCLUSIONS
  The results of this study suggest that a telestroke network may increase the number of patients discharged home and reduce the costs borne by the network hospitals. Hospitals should consider their available resources and the network features when deciding whether to join or set up a network.
authors.affiliation: Georgia Health Sciences University, Augusta, GA, USA. jswitzer@me.com
authors.forename: Jeffrey A
authors.initials: JA
authors.lastname: Switzer
authors.forename: Bart M
authors.initials: BM
authors.lastname: Demaerschalk
authors.forename: Jipan
authors.initials: J
authors.lastname: Xie
authors.forename: Liangyi
authors.initials: L
authors.lastname: Fan
authors.forename: Kathleen F
authors.initials: KF
authors.lastname: Villa
authors.forename: Eric Q
authors.initials: EQ
authors.lastname: Wu
mesh_terms: D003195:Computer Communication Networks / Q000191:economics*; D003362:Cost-Benefit Analysis; D019468:Disease Management; D005845:Georgia / Q000453:epidemiology; D006780:Hospitals, Rural / Q000191:economics*; D006801:Humans; D017146:Models, Organizational; D010360:Patient Transfer / Q000191:economics; D019114:Remote Consultation / Q000191:economics; D020521:Stroke / Q000188:drug therapy* / Q000191:economics / Q000453:epidemiology; D017216:Telemedicine / Q000191:economics*; D015912:Thrombolytic Therapy / Q000191:economics; D016896:Treatment Outcome