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Motor vehicle crashes (MVCs) comprise a significant component of emergency medical service workload. Due to the potential for life-threatening injuries, ambulances are often dispatched at the highest priority to MVCs. However, previous research has shown that only a small proportion of high-priority ambulance responses to MVCs encounter high acuity patients. Alternative methods for triaging patients over the phone are required to reduce the burden of over-triage. One method is to use information readily available at the scene (e.g. whether a person was a motorcyclist, ejection status or whether an airbag deployed) as potential predictors of high acuity. Methods: A retrospective cohort study was conducted of all MVC patients in Perth attended by St John Western Australia between 2014 and 2016. Ambulance data was linked with Police crash data. The outcome variable of interest was patient acuity, where high acuity was defined as where a patient (1) died on-scene or (2) was transported by ambulance on priority one (lights & sirens) from the scene to hospital. Crash characteristics that are predictive of high acuity patients were identified by estimating crude odds ratios and 95% confidence intervals. Results: Of the 18,917 MVC patients attended by SJ-WA paramedics, 6.4% were classified as high acuity patients. The odds of being a high acuity patient was greater for vulnerable road users (motorcyclists, pedestrians and cyclists) than for motor vehicle occupants (OR 3.19, 95% CI, 2.80–3.64). A 'not ambulant patient' (one identified by paramedics as unable to walk or having an injury incompatible with being able to walk) had 15 times the odds of being high acuity than ambulant patients (OR 15.34, 95% CI, 11.48–20.49). Those who were trapped in a vehicle compared to those not trapped (OR 4.68, 95% CI, 3.95–5.54); and those who were ejected (both partial and full) from the vehicle compared to those not ejected (OR 6.49, 95% CI, 4.62–9.12) had higher odds of being high acuity patients. Discussion: There were two important findings from this study: (1) few MVC patients were deemed to be high acuity; and (2) several crash scene characteristics were strong predictors of high acuity patients. [ABSTRACT FROM AUTHOR]

Objective: The objective of the present study is to examine variations in paramedic care of the agitated patient, including verbal de‐escalation, physical restraint and sedation, provided by ambulance services in Australia and New Zealand. Methods: To examine the care of agitated patients, we first identified and reviewed all clinical practice guidelines for the management of agitated patients in Australian and New Zealand ambulance services between September and November 2018. We then conducted a structured questionnaire to obtain further information on the training, assessment and care of agitated patients by the ambulance services. Two authors extracted the data independently, and all interpretations and results were reviewed and confirmed by relevant ambulance services. Results: There were 10 independent clinical practice guidelines for the care of agitated patients in the 10 ambulance services. All services reported training in the management of agitated patients, and two services used a validated tool to assess the level of agitation. All services used physical restraint, although six services required police presence to restrain the patient. All ambulance services used some form of sedation, typically divided into the management of mild to moderate, and severe agitation. The most common agent for sedation was midazolam, while ketamine was the most common agent for sedating severely agitated patients. The maximum dose was varied, and contraindications for sedating agents varied between services. Conclusions: There were wide variations across the ambulance services in terms of the assessment of agitation, as well as the use of physical restraint and sedation. [ABSTRACT FROM AUTHOR]

Objective To compare chief complaints of the Medical Priority Dispatch System in terms of the match between dispatch priority and patient condition. Methods This was a retrospective whole-of-population study of emergency ambulance dispatch in Perth, Western Australia, 1 January 2014 to 30 June 2015. Dispatch priority was categorised as either Priority 1 (high priority), or Priority 2 or 3. Patient condition was categorised as time-critical for patient(s) transported as Priority 1 to hospital or who died (and resuscitation was attempted by paramedics); else, patient condition was categorised as less time-critical. The χ2 statistic was used to compare chief complaints by false omission rate (percentage of Priority 2 or 3 dispatches that were time-critical) and positive predictive value (percentage of Priority 1 dispatches that were time-critical). We also reported sensitivity and specificity. Results There were 211 473 cases of dispatch. Of 99 988 cases with Priority 2 or 3 dispatch, 467 (0.5%) were time-critical. Convulsions/seizures and breathing problems were highlighted as having more false negatives (time-critical despite Priority 2 or 3 dispatch) than expected from the overall false omission rate. Of 111 485 cases with Priority 1 dispatch, 6520 (5.8%) were time-critical. Our analysis highlighted chest pain, heart problems/automatic implanted cardiac defibrillator, unknown problem/collapse, and headache as having fewer true positives (time-critical and Priority 1 dispatch) than expected from the overall positive predictive value. Conclusion Scope for reducing under-triage and over-triage of ambulance dispatch varies between chief complaints of the Medical Priority Dispatch System. The highlighted chief complaints should be considered for future research into improving ambulance dispatch system performance. [ABSTRACT FROM AUTHOR]

Introduction: Demand for emergency ambulances is increasing, therefore it is important that ambulance dispatch is prioritised appropriately. This means accurately identifying which incidents require a lights and sirens (L&S) response and those that do not. For traffic crashes, it can be difficult to identify the needs of patients based on bystander reports during the emergency phone call; as traffic crashes are complex events, often with multiple patients at the same crash with varying medical needs. This study aims to determine how well the text sent to paramedics en-route to the traffic crash scene by the emergency medical dispatcher (EMD), in combination with dispatch codes, can predict the need for a L&S ambulance response to traffic crashes.Methods: A retrospective cohort study was conducted using data from 2014 to 2016 traffic crashes attended by emergency ambulances in Perth, Western Australia. Machine learning algorithms were used to predict the need for a L&S response or not. The features were the Medical Priority Dispatch System (MPDS) determinant codes and EMD text. EMD text was converted for computation using natural language processing (Bag of Words approach). Machine learning algorithms were used to predict the need for a L&S response, defined as where one or more patients (a) died before hospital admission, (b) received L&S transport to hospital, or (c) had one or more high-acuity indicators (based on an a priori list of medications, interventions or observations.Results: There were 11,971 traffic crashes attended by ambulances during the study period, of which 22.3 % were retrospectively determined to have required a L&S response. The model with the highest accuracy was using an Ensemble machine learning algorithm with a score of 0.980 (95 % CI 0.976-0.984). This model predicted the need for an L&S response using both MPDS determinant codes and EMD text.Discussion: We found that a combination of EMD text and MPDS determinate codes can predict which traffic crashes do and do not require a lights and sirens ambulance response to the scene with a high degree of accuracy. Emergency medical services could deploy machine learning algorithms to improve the accuracy of dispatch to traffic crashes, which has the potential to result in improved system efficiency. [ABSTRACT FROM AUTHOR]