|Saturday, February 22|
|PS3 Poster Session III & Continental Breakfast||
Sat, Feb 22, 7:30 AM - 9:00 AM
Quantile Regression with ED Wait Time Data (302720)John Carew, Carolinas Healthcare System
Marcy Neale, Carolinas Healthcare System
*Jie Zhou, Carolinas Healthcare System
Keywords: Quantile Regression, ED Wait Times, Patients' Queue Size, Patients' Flow Rate
Wait times are a key component of customer satisfaction. In the emergency department (ED), informing patients of accurate wait times can substantially affect patient satisfaction and outcomes. Many health care systems publish ED wait time estimates. Carolinas Healthcare System uses a previous two-hour average that is updated every 15 minutes. This resultant wait time distribution of estimates captures the general trend of the actual wait times, but exhibits a lag. Moreover, the local rapid changes in the wait times caused by crowding factors (patients’ queue size, etc.) are not included. This presentation demonstrates a multivariate quantile regression-based ED wait time algorithm developed for Carolinas Medical Center (CMC) ED. We will discuss the key factors that contribute to ED wait times in the CMC ED. We will provide prospective real-time testing results on a two-hour average algorithm and a quantile regression algorithm. The quantile regression-based ED wait time estimation will improve resource allocation within the ED and reduce wait times.