Nothing Special   »   [go: up one dir, main page]

skip to main content
research-article

Emergency department resilience to disaster‐level overcrowding: : A component resilience framework for analysis and predictive modeling

Published: 05 April 2019 Publication History

Abstract

Overcrowding poses a serious challenge to the operations of health care facilities, especially those with a mandate to provide emergency care. A better understanding of emergency department (ED) performance during disaster‐level overcrowding is a key to increasing a facility's resilience, optimizing patient outcomes, and more effectively allocating resources. With this in mind, this study quantitatively examines the extent to which different factors contribute to the resilience of hospital EDs during disaster‐level overcrowding events. A modeling framework was developed in collaboration with the Carilion Clinic ED, a level one trauma center in Virginia. The testing and analysis of the approach is based on data from actual disaster‐level overcrowding events that occurred in the Spring of 2016. Results indicate that by considering not only the capacity for resisting such events but also the capacity for recovering from them more quickly, hospital decision makers can improve both their operational effectiveness and the patient experience. Furthermore, by using our framework to identify precipitating factors and predict severe overcrowding, hospital decision makers can implement changes to improve the future resilience of their ED to such overcrowding events.

References

[1]
Adkins, E. J., & Werman, H. A. (2015). Ambulance diversion: Ethical dilemma and necessary evil. The American Journal of Emergency Medicine, 33(6), 820–821.
[2]
Affleck, A., Parks, P., Drummond, A., Rowe, B. H., & Ovens, H. J. (2013). Emergency department overcrowding and access block. Canadian Journal of Emergency Medicine, 15(6), 359–370.
[3]
Ambulkar, S., Blackhurst, J., & Grawe, S. (2015). Firm's resilience to supply chain disruptions: Scale development and empirical examination. Journal of Operations Management, 33, 111–122.
[4]
American Hospital Association . (2010a). Rapid response survey: Telling the hospital story. Washington, DC: American Hospital Association, March, 2010.
[5]
American Hospital Association . (2010b). The state of America's hospitals: Results of AHA survey of hospital leaders. Washington, DC: American Hospital Association, March/April, 2010.
[6]
Bair, A. E., Song, W. T., Chen, Y. C., & Morris, B. A. (2010). The impact of inpatient boarding on ED efficiency: A discrete‐event simulation study. Journal of Medical Systems, 34(5), 919–929.
[7]
Bellow, A. A., Jr., & Gillespie, G. L. (2014). The evolution of ED crowding. Journal of Emergency Nursing, 40(2), 153–160.
[8]
Besiou, M., Pedraza‐Martinez, A. J., & Van Wassenhove, L. N. (2014). Vehicle supply chains in humanitarian operations: Decentralization, operational mix, and earmarked funding. Production and Operations Management, 23(11), 1950–1965.
[9]
Bruneau, M., Chang, S. E., Eguchi, R. T., Lee, G. C., O'Rourke, T. D., Reinhorn, A. M., … von Winterfeldt, D. (2003). A framework to quantitatively assess and enhance the seismic resilience of communities. Earthquake Spectra, 19(4), 733–752.
[10]
Carilion Clinic . (2015). About Us. Retrieved from https://www.carilionclinic.org/about‐carilion‐clinic.
[11]
Cooney, D. R., Wojcik, S., Seth, N., Vasisko, C., & Stimson, K. (2013). Evaluation of ambulance offload delay at a university hospital emergency department. International Journal of Emergency Medicine, 6(1), 15.
[12]
Fatovich, D. M., Nagree, Y., & Sprivulis, P. (2005). Access block causes emergency department overcrowding and ambulance diversion in Perth, Western Australia. Emergency Medicine Journal, 22(5), 351–354.
[13]
Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861–874.
[14]
Felton, B. M., Reisdorff, E. J., Krone, C. N., & Laskaris, G. A. (2011). Emergency department overcrowding and inpatient boarding: A statewide glimpse in time. Academic Emergency Medicine, 18(12), 1386–1391.
[15]
Foley, M., Kifaieh, N., & Mallon, W. K. (2011). Financial impact of emergency department crowding. Western Journal of Emergency Medicine, 12(2), 192–197.
[16]
Griner, P. F., Mayewski, R. J., & Mushlin, A. I. P. (1981). Selection and interpretation of diagnostic tests and procedures. Annals of Internal Medicine, 94, 555–600.
[17]
Handel, D. A., Hilton, J. A., Ward, M. J., Rabin, E., Zwemer, F. L., Jr., & Pines, J. M. (2010). Emergency department throughput, crowding, and financial outcomes for hospitals. Academic Emergency Medicine, 17(8), 840–847.
[18]
Hoot, N. R., Zhou, C., Jones, I., & Aronsky, D. (2007). Measuring and forecasting emergency department crowding in real time. Annals of Emergency Medicine, 49(6), 747–755.
[19]
Hoyle, L. (2013). Condition yellow: A hospital‐wide approach to ED overcrowding. Journal of Emergency Nursing, 1(39), 40–45.
[20]
Hwang, U., & Concato, J. (2004). Care in the emergency department: How crowded is overcrowded? Academy of Emergency Medicine, 11(10), 1097–1101.
[21]
Johnston, A., Abraham, L., Greenslade, J., Thom, O., Carlstrom, E., Wallis, M., & Crilly, J. (2016). Staff perception of the emergency department working environment: Integrative review of the literature. Emergency Medicine Australasia, 28(1), 7–26.
[22]
Jones, S. S., Allen, T. L., Flottemesch, T. J., & Welch, S. J. (2006). An independent evaluation of four quantitative emergency department crowding scales. Academic Emergency Medicine, 13(11), 1204–1211.
[23]
Kadri, F., Harrou, F., Chaabane, S., & Tahon, C. (2014). Time series modelling and forecasting of emergency department overcrowding. Journal of Medical Systems, 38(107), 1–20.
[24]
Kim, Y., Chen, Y. S., & Linderman, K. (2015). Supply network disruption and resilience: A network structural perspective. Journal of Operations Management, 33, 43–59.
[25]
Liu, F., Song, J. S., & Tong, J. D. (2016). Building supply chain resilience through virtual stockpile pooling. Production and Operations Management, 25(10), 1745–1765.
[26]
Magnus, P., & Killion, S. (2008). Australia's health 2008 (p. 10). Canberra, Australia: Australian Institute of Health and Welfare.
[27]
McCarthy, M. L., Ding, R., Pines, J. M., & Zeger, S. L. (2011). Comparison of methods for measuring crowding and its effects on length of stay in the emergency department. Academic Emergency Medicine, 18(12), 1269–1277.
[28]
Nemeth, C., Wears, R., Woods, D., Hollnagel, E., & Cook, R. (2008). Minding the gaps: Creating resilience in health care. In Advances in patient safety: New directions and alternative approaches (Vol. 3: Performance and tools). Rockville, MD: Agency for Healthcare Research and Quality.
[29]
Pines, J. M., Hilton, J. A., Weber, E. J., Alkemade, A. J., Al Shabanah, H., Anderson, P. D., … Schull, M. J. (2011). International perspectives on emergency department crowding. Academic Emergency Medicine, 18(12), 1358–1370.
[30]
Press Ganey . (2010). Pulse report: Emergency department: Patient perspectives on American health care. Retrieved from http://helpandtraining.pressganey.com/Documents_secure/Pulse%20Reports/2010_ED_Pulse_Report.pdf.
[31]
Richardson, D., Kelly, A., & Kerr, D. (2009). Prevalence of access block in Australia 2004–2008. Emergency Medicine Australasia, 21, 472–478.
[32]
Richardson, S. K., Ardagh, M., & Gee, P. (2005). Emergency department overcrowding: The emergency department cardiac analogy model (EDCAM). Accident and Emergency Nursing, 13(1), 18–23.
[33]
Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. Retrieved from http://www.jstatsoft.org/v48/i02/.
[34]
Salway, R., Valenzuela, R., Shoenberger, J., Mallon, W., & Viccellio, A. (2017). Emergency department (ED) overcrowding: Evidence‐based answers to frequenctly asked questions. Revista Médica Clínica Las Condes, 28(2), 213–219.
[35]
Shen, Y. C., & Hsia, R. Y. (2015). Ambulance diversion associated with reduced access to cardiac technology and increased one‐year mortality. Health Affairs, 34(8), 1273–1280.
[36]
Shih, F. Y., Ma, M. H., Chen, S. C., Wang, H. P., Fang, C. C., Shyu, R. S., … Wang, S. M. (1999). ED overcrowding in Taiwan: Facts and strategies. The American Journal of Emergency Medicine, 17(2), 198–202.
[37]
Su, H. C., Linderman, K., Schroeder, R. G., & Van de Ven, A. H. (2014). A comparative case study of sustaining quality as a competitive advantage. Journal of Operations Management, 32(7), 429–445.
[38]
Sun, B. C., Hsia, R. Y., Weiss, R. E., Zingmond, D., Liang, L. J., Han, W., … Asch, S. M. (2013). Effect of emergency department crowding on outcomes of admitted patients. Annals of Emergency Medicine, 61(6), 605–611.e6. https://doi.org/10.1016/j.annemergmed.2012.10.026
[39]
Trauma Center Association of America . (2018). U.S. Trauma Centers. Retrieved from http://www.traumacenters.org/?page=MapsByLevel.
[40]
Tuller, D. (2016). Ambulance diversion: Efforts to mitigate ambulance diversion have been effective but questions remain for future progress. Health Affairs: Health Policy Brief, June 2, 2016.
[41]
U.S. Department of Health and Human Services . (2012). What is medical surge? Retrieved from http://www.phe.gov/Preparedness/planning/mscc/handbook/chapter1/Pages/whatismedicalsurge.aspx.
[42]
U.S. Government Accountability Office . (2009). Hospital emergency departments: Crowding continues to occur, and some patients wait longer than recommended time frames. Retrieved from http://www.gao.gov/products/GAO-09-347
[43]
Weiss, S. J., Derlet, R., Arndahl, J., Ernst, A. A., Richards, J., Fernández‐Frankelton, M., … Nick, T. (2004). Estimating the degree of emergency department overcrowding in academic medical centers: Results of the national ED overcrowding study (NEDOCS). Academic Emergency Medicine, 11(1), 38–50.
[44]
Weiss, S. J., Ernst, A. A., Derlet, R., King, R., Bair, A., & Nick, T. G. (2005). Relationship between the national ED overcrowding scale and the number of patients who leave without being seen in an academic ED. The American Journal of Emergency Medicine, 23(3), 288–294.
[45]
Weiss, S. J., Ernst, A. A., & Nick, T. G. (2006). Comparison of the national emergency department overcrowding scale and the emergency department work index for quantifying emergency department crowding. Academic Emergency Medicine, 13(5), 513–518.
[46]
Zobel, C. W. (2010). Comparative visualization of predicted disaster resilience. Seattle, WA: ISCRAM.
[47]
Zobel, C. W. (2011). Representing perceived tradeoffs in defining disaster resilience. Decision Support Systems, 50(2), 394–403.
[48]
Zobel, C. W. (2014). Quantitatively representing non‐linear disaster recovery. Decision Sciences, 45(6), 1053–1082.
[49]
Zobel, C. W., & Baghersad, M. (2018). Analytically comparing disaster resilience across multiple dimensions. Socio‐Economic Planning Sciences. https://doi.org/10.1016/j.seps.2018.12.005
[50]
Zobel, C. W., Baghersad, M., & Zhang, Y. (2018). An approach for quantifying the multidimensional nature of disaster resilience in the context of municipal service provision. In Urban disaster resilience and security (pp. 239–259). Cham, Switzerland: Springer.
[51]
Zobel, C. W., & Khansa, L. Z. (2012). Quantifying cyberinfrastructure resilience against multi‐event attacks. Decision Sciences, 43(4), 687–710.
[52]
Zobel, C. W., & Khansa, L. Z. (2014). Characterizing multi‐event disaster resilience. Computers and Operations Research, 42, 83–94.

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Journal of Operations Management
Journal of Operations Management  Volume 66, Issue 1-2
January/March 2020
272 pages
ISSN:0272-6963
EISSN:1873-1317
DOI:10.1002/joom.v66.1-2
Issue’s Table of Contents

Publisher

John Wiley & Sons, Inc.

United States

Publication History

Published: 05 April 2019

Author Tags

  1. component resilience
  2. decision support
  3. hospital operations
  4. multievent disasters
  5. overcrowding
  6. predicted resilience

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 0
    Total Downloads
  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 27 Nov 2024

Other Metrics

Citations

View Options

View options

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media