Introduction: Extended length of stay (LOS) in emergency departments (EDs) and overcrowding are a problems for the Canadian healthcare system, which can lead to the creation of a healthcare access block, a reduced health outcome for acute care patients, and decreased satisfaction with the health care system. The goal of this study is to identify and assess specific factors that predict length of stay in EDs for those patients who fall in the highest LOS category. Methods: A total of 130 patient charts from EDs in Regina were reviewed. Charts included in this study were from the 90th-100th percentile of time-users, who were registered during February 2016, and were admitted to hospital from the ED. Patient demographic data and ED visit data were collected. T-tests and multiple regression analyses were conducted to identify any significant predictors of our outcome variable, LOS. Results: None of the demographic variables showed a significant relationship with LOS (age: p=.36; sex: p=.92, CTAS: p=.48), nor did most of the included ED visit data such as door to doctor time (p=.34) and time for imaging studies (X-ray: p=.56; ultrasound: p=.50; CT p=.45). However, the time between the request for consult until the decision to admit did show a significant relationship with LOS (p<.01).Potential confounding variables analyzed were social work consult requests (p=.14), number of emergency visits on day of registration (p=.62), and hour of registration (00-12 or 12-24-p<.01). After adjustment for time of registration, using hierarchical multiple regression, time from consult request to admit decision maintained a significant predictor (p<.01) of LOS. Conclusion: After adjusting for the influence of confounding factors, “consult request to admit decision” was by far the strongest predictor of LOS of all included variables in our study. The results of this study were limited to some extent by inconsistencies in the documentation of some of the analyzed metrics. Establishing standardized documentation could reduce this issue in future studies of this nature. Future areas of interest include establishing a standard reference for our variables, a further analysis into why consult requests are a major predictor, and how to alleviate this in the future.