Alix J E Carter1, Jerry Overton2, Mikiko Terashima3, David C Cone4. 1. Emergency Health Services - Nova Scotia, Halifax, Nova Scotia, Canada; Department of Emergency Medicine, Dalhousie University School of Medicine, Halifax, Nova Scotia, Canada. 2. Richmond Ambulance Authority, Richmond, Virginia. 3. Department of Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada. 4. Section of EMS, Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut.
Abstract
BACKGROUND: "Offload delay" occurs when the transfer of care from paramedics to the emergency department (ED) is prolonged. Accurately measuring the delivery interval or "offload" is important, because it represents the time patients are waiting for definitive care. Because recording this interval presents a significant challenge, most emergency medical services systems only measure the complete at-hospital time or "turnaround interval," and most offload delay research and policy is based on this proxy. OBJECTIVE: This study sought to test the validity of using the turnaround interval as a surrogate for the delivery interval. METHODS: This observational study examined levels of correspondence, or correlation, between delivery interval and turnaround interval, to assess whether turnaround is a reasonable surrogate for delivery. Delivery and turnaround intervals were logged by Richmond Ambulance Authority (RAA) in Richmond, Virginia, United States from April 1 to December 31, 2008. A total of 1732 ambulance runs from RAA were included. RESULTS: Pearson's correlation analysis showed a good correlation between turnaround and actual offload time (delivery), with a coefficient (r) of 0.753. A post hoc analysis explored patterns in the relationship, which is quite complex. CONCLUSION: The results show that the correlation between the delivery and turnaround intervals is good. However, there remains much to be learned about the at-hospital time intervals and how to use these data to make decisions that will improve resource utilization and patient care. Efforts to establish a method to accurately record the delivery interval and to understand the at-hospital portion of the ambulance response are necessary.
BACKGROUND: "Offload delay" occurs when the transfer of care from paramedics to the emergency department (ED) is prolonged. Accurately measuring the delivery interval or "offload" is important, because it represents the time patients are waiting for definitive care. Because recording this interval presents a significant challenge, most emergency medical services systems only measure the complete at-hospital time or "turnaround interval," and most offload delay research and policy is based on this proxy. OBJECTIVE: This study sought to test the validity of using the turnaround interval as a surrogate for the delivery interval. METHODS: This observational study examined levels of correspondence, or correlation, between delivery interval and turnaround interval, to assess whether turnaround is a reasonable surrogate for delivery. Delivery and turnaround intervals were logged by Richmond Ambulance Authority (RAA) in Richmond, Virginia, United States from April 1 to December 31, 2008. A total of 1732 ambulance runs from RAA were included. RESULTS: Pearson's correlation analysis showed a good correlation between turnaround and actual offload time (delivery), with a coefficient (r) of 0.753. A post hoc analysis explored patterns in the relationship, which is quite complex. CONCLUSION: The results show that the correlation between the delivery and turnaround intervals is good. However, there remains much to be learned about the at-hospital time intervals and how to use these data to make decisions that will improve resource utilization and patient care. Efforts to establish a method to accurately record the delivery interval and to understand the at-hospital portion of the ambulance response are necessary.
Authors: Julia Crilly; Amy Nb Johnston; Marianne Wallis; John O'Dwyer; Joshua Byrnes; Paul Scuffham; Ping Zhang; Emma Bosley; Wendy Chaboyer; David Green Journal: Emerg Med Australas Date: 2019-12-23 Impact factor: 2.151