Variable Definitions We defined three time points for each patient encounter (Figure ​(Figure1):1): time of ED triage assessment (T0); time of decision to admit (T1); and time of discharge (T2). All three times were

recorded to include the date and time in hours and minutes. The time of decision to admit (T1) is the time that the admission order Inhibitors,research,lifescience,medical is written by the admitting service and is extracted by chart reviews. Pre-admission ED time to decision to admit (TTD) was the time period between arrival at ED triage and decision to admit (i.e., T1-T0). We defined delay as a binary variable taking the value 1 if ED TTD > 12 hours and 0 otherwise. We defined delay this way for two Selleck KPT-330 reasons. First, previous literature on this topic has used a dichotomous definition of delay, typically defining delay to occur

if ED LOS > 8 hours [3,5,6,14]. Second, we believe that it would be unlikely that there would be a 12 hour delay in ED TTD due to patient complexity alone, and that a delay of this magnitude would be Inhibitors,research,lifescience,medical caused, at least in part, by system factors. Figure 1 Timeline of hospital treatment divided into ED episode and in-patient episode of care. Our first outcome, IP LOS, was the time between T1 and T2. Our second outcome, total IP cost, was the cumulative cost incurred from T1 to T2. In multivariate analysis we included the following covariates: Inhibitors,research,lifescience,medical age, age2, Inhibitors,research,lifescience,medical gender (0 = male 1 = female), arrival by ambulance (0 = no 1 = yes), admission to ICU or surgery (0 = general wards 1 = ICU or surgery), case mix group (CMG), ED triage category, and site of ED. We included age to account for the possibility that older patients may be more complex and require more time to treat. We included age2 as a mathematical means to account for the possibility that

the trend in age is non-linear (i.e., the increase in complexity associated with a 1-year increase in age would be greater among older patients than among younger patients). Inhibitors,research,lifescience,medical We included CMGs, which categorize patients into clinically homogenous groups, to adjust for severity of illness and case complexity. We included a separate binary variable for each of 350 groups in the data 17-DMAG (Alvespimycin) HCl set. CMGs for inpatients are determined by the Health Records department at the study institution. An algorithm provided to Canadian hospitals by the Canadian Institute for Health Information (CIHI) is used to abstract relevant information from each patient’s chart in order to assign a CMG. ED triage categories were included to adjust for initial acuity. The ED triage categories were defined according to the 5-level Canadian Triage and Acuity Scale (CTAS), which groups patients as follows: CTAS 1 – Resuscitation, CTAS 2 – Emergent, CTAS 3 – Urgent, CTAS 4 – Less Urgent and CTAS 5 – Non-Urgent. The specific site of an ED visit was included to adjust for site level characteristics.