Early Task Initiation and Other Load-Adaptive Mechanisms in the Emergency Department

Abstract

We study a multistage service process that adapts to system occupancy level. Using operational data from more than 140,000 patient visits to a hospital emergency department, we show that the system-level performance of the emergency department is an aggregation of several simultaneous server-level workload response mechanisms. We identify early task initiation as a between-stage adaptive response mechanism that occurs when an upstream stage initiates tasks that are normally handled by a downstream stage. We show that having some diagnostic tests ordered during the triage process reduces treatment time by 20 minutes, on average. However, ordering too many tests at triage can lead to an increase in the total number of tests performed on the patient. We also demonstrate the presence of other response mechanisms such as queuing delays for tasks such as medication delivery, and rushing as nurses spend less time with their patients when the queue length is high. This paper was accepted by Serguei Netessine, operations management.

The value of process friction: The role of justification in reducing medical costs

“…In contrast to previous work that finds that task shifting results from increases in demand (Batt & Terwiesch, 2016;Freeman et al, 2014), our study suggests that justification, independent of demand, can affect task shifting rates. In contrast to previous work that finds that task shifting results from increases in demand (Batt & Terwiesch, 2016;Freeman et al, 2014), our study suggests that justification, independent of demand, can affect task shifting rates.…”

“…For each visit, we have the patient's medical record number (MRN), demographic information (e.g., age, gender, race, insurance), emergency severity index (ESI, a measure of the patient's severity and urgency), attending physician, time of arrival, waiting time to enter the ED (from the time of arrival until the patient enters the ED bed), and ED LOS (from the time when a patient enters an ED bed until a discharge order is written, following previous convention [Batt & Terwiesch, 2016Song, Tucker, Murrell, & Vinson, 2015]). In addition, each record has time-stamped medical and procedure orders, such as medication, laboratory, consult requests, and radiology orders, as well as the reason for a patient's visit (known as the primary complaint), and the disposition of the patient at the end of the visit (e.g., admission to hospital, discharge from ED, transfer to another health care facility).…”

Work after work: The impact of new service delivery models on work hours

“…Prior literature in operations management studies how servers respond to workload, particularly when servers have discretion over work content or sequence (Ibanez et al, ; Song, Tucker, & Murrell, ). Several papers have documented speeding up behavior in response to workload among different tasks: patient transportation within a hospital (Kc & Terwiesch, ), outpatient care (Deo & Jain, ), emergency room care (Batt & Terwiesch, ), inpatient care (Berry Jaeker & Tucker, ), customer email support (Hasija, Pinker, & Shumsky, ), and restaurant service (Tan & Netessine, ).…”

Task Selection and Workload: A Focus on Completing Easy Tasks Hurts Long-Term Performance

“…Also examining hospital data Berry Jaeker and Tucker (2015) find that beyond a certain level of congestion in the system, patient length of stay increases because the patients that are left in the system have high demands. Other papers have considered the role of workload, for example in the intensive care admissions decision (Kim et al 2015) and in emergency department service times (Batt and Terwiesch 2016). We contribute to this line of literature as we are the first to consider, directly, the role of individual task selection in the workload speedup effect.…”