The paradox of Pods

Emergency department (ED) overcrowding has been one of the most complex problems in health care systems worldwide over the past 20 years. While demand has increased significantly over this period, ED capacity has remained the same, causing long queues of patients who cannot receive the required medical service in time.

This has been a severe problem adversely affecting patient experience, quality of care and health costs. There is increasing evidence linking overcrowding with an increase in mortality rate. Overcrowding can also result in prolonged length of stay, long wait times, delayed care for critical patients, compromised quality of care, medical team fatigue, increased medical errors, high numbers of patients leaving without being seen, and reduced patient satisfaction.

To address the overcrowding problem and reduce wait times in EDs, some governments (including the UK, Australia and New Zealand) have introduced time-based targets for EDs. New Zealand's target, implemented in 2009, is that 95 percent of patients in public hospital EDs should be seen, treated or discharged within six hours. Although there are some major external causes for ED overcrowding, several interventions have been proposed to meet these targets and improve the timeliness and efficiency of care within EDs. Operations management (OM) principles, particularly queue management, have been widely used in these interventions to streamline patient flow, use resources effectively and improve ED performance.

A reportedly successful intervention in decreasing wait times called Pods, divides EDs into smaller parts, each with a specific medical team, number of beds and dedicated queue of patients. The University of Pittsburgh Medical Centre, Sharp Memorial Hospital, University of Tennessee Medical Centre, Torrance Memorial Emergency Department, NYU Lutheran Medical Centre and University of Michigan Health System were all EDs that reported improvement after implementing Pods. On the other hand, the specifications of Pods seem to contradict one of the most basic queueing theory principles, that pooling service capacities leads to shorter wait times. This surprising paradox was a trigger for my PhD research proposal to search for the underlying factors that can counter the loss of pooling synergy in Pods and make its performance superior.

The field of OM has deep roots in the studies of Frederick W. Taylor in 1883 and the Scientific Management movement of the early 20th century. Because of the focus of these early studies, the OM field developed a tradition of studying the physical tasks in manufacturing, construction and other industries. Therefore, there is a disconnect identified by academics and practitioners between the concepts introduced and the real service systems where human work predominates.

I plant to employ controlled experiments to identify the exact behavioural factors that affect performance in EDs and study how they can change the dynamics between the traditional OM variables. Ultimately, I want to propose the optimal design for ED work environments that takes both operations management and behavioural operations factors into account.

Aida Shams is a PhD candidate in the Information Systems and Operations Management department. Her interest is mainly behavioural OM. She is currently working on behavioural operations in healthcare systems.