Point-of-Care Testing: Improving Emergency Department Performance through Process Redesign
33 Pages Posted: 11 Oct 2012 Last revised: 8 Dec 2012
Date Written: October 10, 2012
Hospital emergency departments (EDs) typically rely on central laboratories to analyze patient samples for the purposes of diagnosing and treating patients. Point-of-care testing (POCT) is a process redesign that shifts the analysis of samples from the central lab to the ED. Using a queueing model, we generate hypotheses about how POCT impacts operational performance and then test those hypotheses empirically using data collected from a large, urban, tertiary, academic hospital. Specifically, we analyze how the adoption of POCT impacts service time, defined as the time between patient bed assignment and disposition, and waiting time, defined as the time between patient intake and bed assignment, as well as the quality of care provided to patients, defined by the 72 hour bounceback rate. We find POCT to be associated with statistically significant improvements in nearly all measures of operational performance. Specifically, we find the adoption of POCT to be associated with a 21.6% reduction in service time among test patients during peak hours and a 35.5% reduction in waiting time among all low priority patients presenting during peak hours. Moreover, we find the adoption of POCT to be associated with improved service quality as patients’ predicted probability of bounceback decreased by 0.6% during its usage. We also find system wide spillover effects for patients who do not receive POCT (no-test patients). In other words, the adoption of POCT is associated with a service time reduction among these no-test patients of 4.73% and the observed changes in waiting time are statistically similar across test and no-test patients. By examining the impact of POCT among both the population of patients receiving the test and the population that does not, this research is unique in identifying the system-wide benefits that can be attained through ED process redesign.
Keywords: Healthcare Management, Empirical Research, Queueing Theory, Technology Management, Process Design, Service Operations
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