Howell, StuartSmith, KarenFinn, JudithCameron, PeterBall, StephenBosley, EmmaDoan, TanDicker, BridgetFaddy, StevenNehme, ZiadSwain, AndyThorrowgood, MelanieThomas, AndrewPerillo, SamuelMcDermott, MikeSmith, TonyBray, JanetAus-ROC OHCA Epistry Management Committee2023-06-262023-06-262023-05-19Resuscitation, ISSN: 0300-9572 (Print); 1873-1570 (Online), Elsevier, 188, 109847-. doi: 10.1016/j.resuscitation.2023.1098470300-95721873-1570http://hdl.handle.net/10292/16319INTRODUCTION: The aim of this study was to develop a risk adjustment strategy, including effect modifiers, for benchmarking emergency medical service (EMS) performance for out-of-hospital cardiac arrest (OHCA) in Australia and New Zealand. METHOD: Using 2017-2019 data from the Australasian Resuscitation Outcomes Consortium (Aus-ROC) OHCA Epistry, we included adults who received an EMS attempted resuscitation for a presumed medical OHCA. Logistic regression was applied to develop risk adjustment models for event survival (return of spontaneous circulation at hospital handover) and survival to hospital discharge/30 days. We examined potential effect modifiers, and assessed model discrimination and validity. RESULTS: Both OHCA survival outcome models included EMS agency and the Utstein variables (age, sex, location of arrest, witnessed arrest, initial rhythm, bystander cardiopulmonary resuscitation, defibrillation prior to EMS arrival, and EMS response time). The model for event survival had good discrimination according to the concordance statistic (0.77) and explained 28% of the variation in survival. The corresponding figures for survival to hospital discharge/30 days were 0.87 and 49%. The addition of effect modifiers did little to improve the performance of either model. CONCLUSION: The development of risk adjustment models with good discrimination is an important step in benchmarking EMS performance for OHCA. The Utstein variables are important in risk-adjustment, but only explain a small proportion of the variation in survival. Further research is required to understand what factors contribute to the variation in survival between EMS.http://creativecommons.org/licenses/by-nc-nd/4.0/Emergency medical servicesHeart arrestOut of hospital cardiac arrestRegistriesResuscitationAus-ROC OHCA Epistry Management Committee4203 Health Services and Systems32 Biomedical and Clinical Sciences3202 Clinical Sciences42 Health SciencesHeart DiseaseEmergency CareCardiovascularCardiovascular1103 Clinical Sciences1110 Nursing1117 Public Health and Health ServicesEmergency & Critical Care Medicine3202 Clinical sciences4205 Nursing4206 Public healthJournal ArticleOpenAccess10.1016/j.resuscitation.2023.109847