Mathematical Modeling of the Impact of Hospital Occupancy: When Do Dwindling Hospital Beds Cause ED Gridlock?

Abstract

Objectives. The time emergency department (ED) patients spend from presentation to admittance is known as their length of stay (LOS). This study aimed to quantify the inpatient occupancy rate (InptOcc)/ED LOS relationship and develop a methodology for identifying resource-allocation triggers using InptOcc-LOS association-curve inflection points.Methods. This study was conducted over 200 consecutive days at a 700-bed hospital with an annual ED census of approximately 50,000 using multivariate spline (piecewise) regression to model the InptOcc/LOS relationship while adjusting for confounding covariates. Nonlinear modeling was used to assess for InptOcc/LOS associations and determine the inflection point where InptOcc profoundly impacted LOS.Results. At lower InptOcc, there was no association. Once InptOcc reached ≥88%, there was a strong InptOcc/LOS association; each 1% InptOcc increase predicted a 16-minute (95% CI, 12–20 minutes) LOS prolongation, while the confounder-adjusted analysis showed each 1% InptOcc increase >89% precipitating a 13-minute (95% CI, 10–16 minutes) LOS prolongation.Conclusions. The study hospital’s InptOcc was a significant predictor of prolonged ED LOS beyond the identified inflection point. Spline regression analysis identified a clear inflection point in the InptOcc-LOS curve that potentially identified a point at which to optimize inpatient bed availability to prevent increased costs of prolonged LOS.

Marginal analysis in assessing factors contributing time to physician in the Emergency Department using operations data

“…These parameters, as well as the related covariate of hospital occupancy, have been demonstrated previously to be major drivers of ED operations performance. 20 As is the case in many EDs, the clinical areas tend to be less full at the beginning of the day and with increasing lengths of stay the ED becomes “more fully” independent of actual numbers of patients arriving to be seen. This finding will be explored in a future analysis at the study center, as the ability to track hospital occupancy is integrated into the EDAD.…”

“…Analysis of operations data includes focus on variables with impact on the medical outcome as well as economic and patient-satisfaction outcomes. 1 , 16 , 17 , 18 , 19 , 20 One factor of particular importance is the time interval between the initial patient arrival at the ED and initial patient contact with a physician ( tMD ). Faster tMD indicates a higher likelihood of optima patient safety and care quality (due to more-rapid physician evaluation); patients who are attended to more quickly are also more satisfied and less likely to leave the ED before their evaluation.…”

Identifying Patient Door-to-Room Goals to Minimize Left-Without-Being-Seen Rates

“…Medical outcomes problems (including medical-legal risk issues) are at the top of the list of LWBS concerns. 1 , 16 , 17 Other problems may include decreased patient satisfaction scores, 18 financial loss to the hospital, 3 , 19 and even system-based efficiency issues such as repeated patient presentation after the initial LWBS episode. 20 …”

“…There was no information on actual financial or clinical impact of improving LWBS. As previously reported, the study hospital system uses an averaged-out “value” for an individual LWBS case (about $200), 3 but this average value is understood to be both imperfect and not necessarily generalizable. Therefore, the authors emphasize that the endpoint of “meeting LWBS goal” is the major aim of this analysis, with the extrapolation of the value of meeting that goal left for future discussion.…”

“… 1 , 2 In the current era of ED crowding, there is growing concern about LWBS. 1 , 3 The literature still identifies this area as being among the most important performance measures relating directly to the patient. 4 – 6 Progress is being reported for specific populations (e.g.…”