The variables predictive of ambulance non-conveyance of patients in the Western Cape, South Africa

Introduction: Emergency medical service (EMS) resources are limited and should be reserved for incidents of appropriate acuity. Over-triage in dispatching of EMS resources is a global problem. Analysing patients that are not transported to hospital is valuable in contributing to decision-making models/algorithms to better inform dispatching of resources. The aim is to determine variables associated with patients receiving an emergency response but result in non-conveyance to hospital.Methods: A retrospective cross-sectional study was performed on data for the period October 2018 to September 2019. EMS records were reviewed for instances where a patient received an emergency response but the patient was not transported to hospital. Data were subjected to univariate and multivariate regression analysis to determine variables predictive of non-transport to hospital.Results: A total of 245 954 responses were analysed, 240 730 (97.88 %) were patients that were transported to hospital and 5 224 (2.12 %) were not transported. Of all patients that received an emergency response, 203 450 (82.72 %) patients did not receive any medical interventions. Notable variables predictive of non-transport were green (OR 4.33 (95 % CI: 3.55-5.28; p<0.01)) and yellow on-scene (OR 1.95 (95 % CI: 1.60-2.37; p<0.01). Incident types most predictive of non-transport were electrocutions (OR 4.55 (95 % CI: 1.36-15.23; p=0.014)), diabetes (OR 2.978 (95 % CI: 2.10-3.68; p<0.01)), motor vehicle accidents (OR 1.92 (95 % CI: 1.51-2.43; p<0.01)), and unresponsive patients (OR 1.98 (95 % CI: 1.54-2.55; p<0.01)). The highest treatment predictors for non-transport of patients were nebulisation (OR 1.45 (95 % CI: 1.21-1.74; p<0.01)) and the administration of glucose (OR 4.47 (95 % CI: 3.11-6.41; p<0.01)).Conclusion: This study provided factors that predict ambulance non-conveyance to hospital. The prediction of patients not transported to hospital may aid in the development of dispatch algorithms that reduce over-triage of patients, on-scene discharge protocols, and treat and refer guidelines in EMS.