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224 Abdulrahman Albar, Ahmad Elshennawy, Mohammed Basingab et al.
linear regression or multiple regression could be used to model the demand side of the
problem in such a way to make the index more robust and accurate. A separate research
effort could focus on developing a set of action protocols for EDs, to specify a course of
action to both prevent and react to overcrowding when it occurs, as identified by the
index. Finally, a more rigorous validation study could simulate the index by integrating it
with a discrete event simulation model to study its performance over a longer period of
time. With such a simulation, the impact of the determinants on the overcrowding score
could be more accurately observed. Patterns of simulated data used to more closely
observe the impact of each factor on overcrowding could also be used to draw
conclusions for the development of future ED policy.
REFERENCES
AHA. (2014). AHA Annual Survey Database™. Retrieved from http://www.aha
dataviewer.com/book-cd-products/AHA-Survey/. from American Hospital Assoc-
iation http://www.ahadataviewer.com/book-cd-products/AHA-Survey/
Asplin, B. R., Magid, D. J., Rhodes, K. V., Solberg, L. I., Lurie, N., & Camargo, C. A.
(2003). A conceptual model of emergency department crowding. Annals of
emergency medicine, 42(2), 173-180.
Bellow, A. A., & Gillespie, G. L. (2014). The evolution of ED crowding. Journal of
Emergency Nursing, 40(2), 153.
Bernstein, S. L., Verghese, V., Leung, W., Lunney, A. T., & Perez, I. (2003).
Development and validation of a new index to measure emergency department
crowding. Academic Emergency Medicine, 10(9), 938-942.
Eitel, D. R., Rudkin, S. E., Malvehy, M. A., Killeen, J. P., & Pines, J. M. (2010).
Improving service quality by understanding emergency department flow: a White
Paper and position statement prepared for the American Academy of Emergency
Medicine. The Journal of emergency medicine, 38(1), 70-79.
Epstein, S. K., Huckins, D. S., Liu, S. W., Pallin, D. J., Sullivan, A. F., Lipton, R. I., &
Camargo, C. A. (2012). Emergency department crowding and risk of preventable
medical errors. Internal and emergency medicine, 7(2), 173-180.
Epstein, S. K., & Tian, L. (2006). Development of an emergency department work score
to predict ambulance diversion. Academic Emergency Medicine, 13(4), 421-426.
Gilboy, N., Tanabe, P., Travers, D., Rosenau, A., & Eitel, D. (2005). Emergency severity
index, version 4: implementation handbook. Rockville, MD: Agency for Healthcare
Research and Quality, 1-72.
Hwang, U., McCarthy, M. L., Aronsky, D., Asplin, B., Crane, P. W., Craven, C. K.,
Pines, J. M. (2011). Measures of crowding in the emergency department: a
systematic review. Academic Emergency Medicine, 18(5), 527-538.