Structural Predictors of Lights and Sirens Use by Emergency Medical Services

Structural Predictors of Lights and Sirens Use by Emergency Medical Services by Justin A. Sleffel MHA, Ashworth College, 2018 BA, Ashworth College, 2014 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Healthcare Administration Walden University November 2020 Abstract Ambulances regularly respond to scenes and transport patients while using lights and sirens (L&S), which are associated with an increased risk of vehicle crashes. The use of L&S persists, despite the risks, which impact emergency medical service (EMS) workers, patients, and other drivers and pedestrians on U.S. roadways. To understand the factors associated with ambulance crashes while using L&S, this study applied the DonabedianAmbulances regularly respond to scenes and transport patients while using lights and sirens (L&S), which are associated with an increased risk of vehicle crashes. The use of L&S persists, despite the risks, which impact emergency medical service (EMS) workers, patients, and other drivers and pedestrians on U.S. roadways. To understand the factors associated with ambulance crashes while using L&S, this study applied the Donabedian model to the problem. The purpose of this study was to investigate the association between 3 organizational structural factors—organizational type, organizational status (staffing model), and level of service—and ambulance crash rates while using L&S. This study used a quantitative, correlational, cross-sectional design with a sample drawn from the National EMS Information System data set to examine the relationship between these factors and ambulance crashes while using L&S. After application of inclusion criteria, a sample of 4,951,063 cases was drawn and analyzed using X test of association and multiple logistic regression. There was a statistically significant association between level of service and ambulance crashes while using L&S, using the X test of association with a small effect. There was no statistically significant relationship found between the other variables using X tests or the logistic model. The organizational structural factors examined in this study failed to explain most of the variance in ambulance crash rates. EMS healthcare administrators and researchers should continue to explore potential modifiable factors to reduce the incidence of these events and promote positive social change by reducing the risk of injury to patients, EMS workers, and the public at large. Structural Predictors of Lights and Sirens Use by Emergency Medical Services by Justin A. Sleffel MHA, Ashworth College, 2018 BA, Ashworth College, 2014 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Healthcare Administration Walden University November 2020 Dedication I dedicate this study to my son, Julian. You are my greatest joy, and with this work and those that follow it, I hope to create a better, brighter world for you to inherit. I look forward to the day when you add your own stone to the foundation that I and so many others leave for you—and I know that when your time comes, you will blow us all away. Acknowledgments First, I would like to thank Dr. Ross, whose guidance and support during the completion of this doctoral study has been immeasurable, as well as Dr. Oswald for the direction and support he provided. Next, I would like to thank my parents, Don and Susan, for their lifelong support of my academic success and for instilling a love of learning in me from an early age. I would not be where I am if not for you. I would also like to acknowledge the EMTs and paramedics who instructed me and supported my career as a paramedic, especially Bill Robben, Angela Hamilton, and Kevin Hartley, who nurtured and supported my early career in EMS. Finally, I would like to thank my wife, Sarah, who has supported me through many long days and nights and stood by my side throughout this journey. I could not have done this without you.