Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-26T07:19:12.924Z Has data issue: false hasContentIssue false
  • English
  • Français

Influence of publicly available online wait time data on emergency department choice in patients with noncritical complaints

Published online by Cambridge University Press:  11 May 2015

Amelia Yip ,
Shelley McLeod ,
Andrew McRae  and
Bin Xie
Amelia Yip
Affiliation:
Schulich School of Medicine and Dentistry, Western University, London, ON
Shelley McLeod*
Affiliation:
Schulich School of Medicine and Dentistry, Western University, London, ON
Andrew McRae
Affiliation:
Division of Emergency Medicine, Calgary University, Calgary, AB
Bin Xie
Affiliation:
Schulich School of Medicine and Dentistry, Western University, London, ON
*
Division of Emergency Medicine, Department of Medicine, Western University, London, ON N6A 5W9; [email protected].

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Objectives:

Increased emergency department (ED) wait times lead to more patients who leave without being seen and decreased patient satisfaction. Many EDs post estimated wait times either online or in the ED to guide patient expectations. The objectives of this study were to assess patients' awareness of online wait time data and to investigate patients' willingness to use this information when choosing between two academic EDs in London, Ontario.

Methods:

A prospective study was conducted over a 2-month period in a tertiary ED with online available wait times. Patients over 18 years of age assigned a Canadian Triage and Acuity Scale (CTAS) score of 3, 4, or 5 were approached by trained research assistants to complete a 15-item paper-based questionnaire. Multivariable logistic regression models were used to determine factors independently associated with the outcomes.

Results:

A total of 1,211 patients completed the survey. Of these, 109 (9%) were aware that ED wait time information was available on the Internet; 544 (45%) reported that they would use the available data to make a decision on which ED to visit, and 536 (44%) indicated that they were more likely to go to the ED with a shorter wait time. Age, gender, household income, education, and Internet access were not associated with awareness of online ED wait times. Participants less than 40 years of age were more likely to use online wait time information.

Conclusion:

There is low awareness of the availability of ED wait time data published online in the study locaton. Future research may include the delivery of a public awareness strategy for ED wait time data and a re-evaluation of ED use and patient satisfaction following this.

Keywords

emergency department wait timenoncritical illnessesonline wait time datapatient perceptionpatient satisfaction
Type
Original Research • Recherche originale
Information
Canadian Journal of Emergency Medicine , Volume 14 , Issue 4 , July 2012 , pp. 237 - 246
Copyright
Copyright © Canadian Association of Emergency Physicians 2012

References

REFERENCES

1.Canadian Association of Emergency Physicians. Taking action on the issue of overcrowding in Canada’s emergency departments. 2005. Available at: http://www.waittimealliance.ca/waittimes/CAEP.pdf (accessed February 17, 2011).Google Scholar
2.Ontario Ministry of Health and Long-Term Care website. Available at: http://waittimes.hco-on.ca/EN/search/er/ (accessed Feb 2011).Google Scholar
3.Murray, M, Bullard, M, Grafstein, E, et al. Revisions to the Canadian Emergency Department Triage and Acuity Scale implementation guidelines. CJEM 2004;6:421–7.Google Scholar
4.London Health Sciences Centre. Emergency department wait times. Available at: http://www.lhsc.on.ca/About_Us/Accountability/Caring_for_our_Patients/Wait_Times/ED/ (accessed February 17, 2011).Google Scholar
5.Peduzzi, P, Concato, J, Kemper, E, et al. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol 1996;49:1373–9, doi:10.1016/S0895-4356(96)00236-3.Google Scholar
6.Development Core Team. A language and environment for statistical computing. Vienna (Austria): Foundation for Statistical Computing; 2010.Google Scholar
7.WESH.com Orlando. New billboards display ER wait times. Available at: http://www.wesh.com/health/20983530/detail.html# (accessed February 17, 2011).Google Scholar
8.Middlesex Hospital. Emergency room waiting time clock, Available at: http://middlesexertime.com/ (accessed February 17, 2011).Google Scholar
9.US Department of Health and Human Services, Centers for Disease Control and Prevention, National Centre for Health Statistics. Health care in America: trends in utilization. 2004. Washington: US DHHS; 2004. DHHS Pub No. 2004-1031.Google Scholar
10.US Census Bureau. Statistical abstract of the United States. 2011. Available at: http://www.census.gov/compendia/statab/ (accessed Feb 2011).Google Scholar
11. Available at: http://atlas.nrcan.gc.ca/auth/english/maps/health/servicesutilization/utilization_figure2.gif/image_view (accessed Feb 2011).Google Scholar
12.Gamble, KH. Wait watchers: smart organizations are demonstrating that while they can’t erase ED wait times, they can leverage technology to keep patients better informed. Healthc Inform 2010;27(4):30–1.Google ScholarPubMed