Aligning ambulance dispatch priority to patient acuity: A methodology

Refining ambulance clinical response models: The impact on ambulance response and emergency department presentations

OBJECTIVE

The ambulance service in Victoria, Australia implemented a revised clinical response model (CRM) in 2016 which was designed to increase the diversion of low-acuity Triple Zero (000) calls to secondary telephone triage and reduce emergency ambulance dispatches. The present study evaluates the influence of the revised CRM on emergency ambulance response times and ED presentations.

METHODS

A retrospective study of emergency calls for ambulance between 1 January 2015 and 31 December 2018. Ambulance data were linked with ED presentations occurring up to 48 h after contact. Interrupted time series analyses were used to evaluate the impact of the revised CRM.

RESULTS

A total of 2 365 529 calls were included. The proportion allocated a Code 1 (time-critical, lights/sirens) dispatch decreased from 56.6 to 41.0% after implementation of the revised CRM. The proportion of calls not receiving an emergency ambulance increased from 10.4 to 19.6%. Interrupted time series analyses demonstrated an improvement in Code 1 cases attended within 15 min (Key Performance Indicator). However, for patients with out-of-hospital cardiac arrest or requiring lights and sirens transport to hospital, there was no improvement in response time performance. By the end of the study period, there was also no difference in the proportion of callers presenting to ED when compared with the estimated proportion assuming the revised CRM had not been implemented.

CONCLUSION

The revised CRM was associated with improved Code 1 response time performance. However, there was no improvement in response times for high acuity patients, and no change in the proportion of callers presenting to ED.

Long-term effects of a coalmine fire on hospital and ambulance use: An interrupted time series study

BACKGROUND

In 2014, the Hazelwood coalmine fire in regional Victoria, Australia shrouded nearby communities in smoke for six weeks. Prior investigations identified substantial adverse effects, including increases in the use of health services. In this study, we examined the effects on hospital and ambulance use in the eight years following the fire.

METHODS

Using Victorian hospital (Jan 2009-Jun 2022) and ambulance (Jan 2013-Dec 2021) data, we conducted an interrupted time series of changes to the rate of hospital admissions, emergency presentations, and ambulance attendances. A categorical exposure model compared two locations, most-exposed Morwell and less-exposed Latrobe Valley, to the rest of regional Victoria. A continuous exposure model used spatial estimates of fire-related PM2.5. Analyses were stratified by sex, age group (<65/65+ years), and condition (cardiovascular, respiratory, mental health, injury).

RESULTS

There were small but significant increases in overall hospital admissions and emergency presentations across all analyses, but little evidence of change in overall ambulance attendances. Effects varied considerably by condition, with the biggest relative increases observed among hospital admissions for mental health conditions and injuries. While cardiovascular-related hospital admissions and emergency presentations increased post-fire, ambulance attendances decreased.

CONCLUSIONS

Our findings suggest the Hazelwood coalmine fire likely increased hospital usage. However, it is unclear whether this was due to the direct effects of smoke exposure on health, or the disruptive socioeconomic and behavioural impacts of an environmental disaster that affected how communities engaged with various health services.

How should non-emergency EMS presentations be managed? A thematic analysis of politicians', policymakers', clinicians' and consumers' viewpoints

OBJECTIVE

In 2023, Australian government emergency medical services (EMS) responded to over 4 million consumers, of which over 56% were not classified as an 'emergency', at the cost of AU$5.5 billion. We explored the viewpoints of politicians, policymakers, clinicians and consumers on how these non-emergency requests should be managed.

DESIGN

A realist framework was adopted; a multidisciplinary team (including paramedicine, medicine and nursing) was formed; data were collected via semistructured focus groups or interviews, and thematic analysis was performed.

SETTING AND PARTICIPANTS

56 participants were selected purposefully and via open advertisement: national and state parliamentarians (n=3); government heads of healthcare disciplines (n=3); government policymakers (n=5); industry policymakers in emergency medicine, general practice and paramedicine (n=6); EMS chief executive officers, medical directors and managers (n=7); academics (n=8), frontline clinicians in medicine, nursing and paramedicine (n=8); and consumers (n=16).

RESULTS

Three themes emerged: first, the reality of the EMS workload (theme titled 'facing reality'); second, perceptions of what direction policy should take to manage this ('no silver bullet') and finally, what the future role of EMS in society should be ('finding the right space'). Participants provided 16 policy suggestions, of which 10 were widely supported: increasing public health literacy, removing the Medical Priority Dispatch System, supporting multidisciplinary teams, increasing 24-hour virtual emergency departments, revising undergraduate paramedic university education to reflect the reality of the contemporary role, increasing use of management plans for frequent consumers, better paramedic integration with the healthcare system, empowering callers by providing estimated wait times, reducing ineffective media campaigns to 'save EMS for emergencies' and EMS moving away from hospital referrals and towards community care.

CONCLUSIONS

There is a need to establish consensus on the role of EMS within society and, particularly, on whether the scope should continue expanding beyond emergency care. This research reports 16 possible ideas, each of which may warrant consideration, and maps them onto the standard patient journey.

Performance of 21 Early Warning System scores in predicting in-hospital deterioration among undifferentiated admitted patients managed by ambulance services

BACKGROUND

The optimal Early Warning System (EWS) scores for identifying patients at risk of clinical deterioration among those transported by ambulance services remain uncertain. This retrospective study compared the performance of 21 EWS scores to predict clinical deterioration using vital signs (VS) measured in the prehospital or emergency department (ED) setting.

METHODS

Adult patients transported to a single ED by ambulances and subsequently admitted to the hospital between 1 January 2019 and 18 April 2019 were eligible for inclusion. The primary outcome was 30-day mortality; secondary outcomes included 3-day mortality, admission to intensive care or coronary care units, length of hospital stay and emergency call activations. The discriminative ability of the EWS scores was assessed using the area under the receiver operating characteristic curve (AUROC). Subanalyses compared the performance of EWS scores between surgical and medical patient types.

RESULTS

Of 1414 patients, 995 (70.4%) (53.1% male, mean age 68.7±17.5 years) were included. In the ED setting, 30-day mortality was best predicted by VitalPAC EWS (AUROC 0.71, 95% CI (0.65 to 0.77)) and National Early Warning Score (0.709 (0.65 to 0.77)). All EWS scores calculated in the prehospital setting had AUROC <0.70. Rapid Emergency Medicine Score (0.83 (0.73 to 0.92)) and New Zealand EWS (0.88 (0.81 to 0.95)) best predicted 3-day mortality in the prehospital and ED settings, respectively. EWS scores calculated using either prehospital or ED VS were more effective in predicting 3-day mortality in surgical patients, whereas 30-day mortality was best predicted in medical patients. Among the EWS scores that achieved AUROC ≥0.70, no statistically significant differences were detected in their discriminatory abilities to identify patients at risk of clinical deterioration.

CONCLUSIONS

EWS scores better predict 3-day as opposed to 30-day mortality and are more accurate when estimated using VS measured in the ED. The discriminatory performance of EWS scores in identifying patients at higher risk of clinical deterioration may vary by patient type.

The Economic Impact of Community Paramedics Within Emergency Medical Services: A Systematic Review

BACKGROUND AND OBJECTIVE

Globally, emergency medical services (EMSs) report that their demand is dominated by non-emergency (such as urgent and primary care) requests. Appropriately managing these is a major challenge for EMSs, with one mechanism employed being specialist community paramedics. This review guides policy by evaluating the economic impact of specialist community paramedic models from a healthcare system perspective.

METHODS

A multidisciplinary team (health economics, emergency care, paramedicine, nursing) was formed, and a protocol registered on PROSPERO (CRD42023397840) and published open access. Eligible studies included experimental and analytical observational study designs of economic evaluation outcomes of patients requesting EMSs via an emergency telephone line ('000', '111', '999', '911' or equivalent) responded to by specialist community paramedics, compared to patients attended by usual care (i.e. standard paramedics). A three-stage systematic search was performed, including Peer Review of Electronic Search Strategies (PRESS) and Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA). Two independent reviewers extracted and verified 51 unique characteristics from 11 studies, costs were inflated and converted, and outcomes were synthesised with comparisons by model, population, education and reliability of findings.

RESULTS

Eleven studies (n = 7136 intervention group) met the criteria. These included one cost-utility analysis (measuring both costs and consequences), four costing studies (measuring cost only) and six cohort studies (measuring consequences only). Quality was measured using Joanna Briggs Institute tools, and was moderate for ten studies, and low for one. Models included autonomous paramedics (six studies, n = 4132 intervention), physician oversight (three studies, n = 932 intervention) and/or special populations (five studies, n = 3004 intervention). Twenty-one outcomes were reported. Models unanimously reduced emergency department (ED) transportation by 14-78% (higher quality studies reduced emergency department transportation by 50-54%, n = 2639 intervention, p < 0.001), and costs were reduced by AU$338-1227 per attendance in four studies (n = 2962). One study performed an economic evaluation (n = 1549), finding both that the costs were reduced by AU$454 per attendance (although not statistically significant), and consequently that the intervention dominated with a > 95% chance of the model being cost effective at the UK incremental cost-effectiveness ratio threshold.

CONCLUSIONS

Community paramedic roles within EMSs reduced ED transportation by approximately half. However, the rate was highly variable owing to structural (such as local policies) and stochastic (such as the patient's medical condition) factors. As models unanimously reduced ED transportation-a major contributor to costs-they in turn lead to net healthcare system savings, provided there is sufficient demand to outweigh model costs and generate net savings. However, all models shift costs from EDs to EMSs, and therefore appropriate redistribution of benefits may be necessary to incentivise EMS investment. Policymakers for EMSs could consider negotiating with their health department, local ED or insurers to introduce a rebate for successful community paramedic non-ED-transportations. Following this, geographical areas with suitable non-emergency demand could be identified, and community paramedic models introduced and tested with a prospective economic evaluation or, where this is not feasible, with sufficient data collection to enable a post hoc analysis.

Characteristics and Outcomes of Patients Referred to a General Practitioner by Victorian Paramedics

OBJECTIVE

Many patients who are attended by paramedics do not require conveyance to an emergency department (ED). Our study focuses on comparing the characteristics and outcomes of patients who were advised to follow up with a general practitioner (GP) by an attending paramedic with those of patients who were discharged at scene or transported to hospital.

METHODS

This was a retrospective data linkage cohort study of ambulance, ED, hospital admission, and death records for all adults attended by paramedics in Victoria, Australia between the 1st of January 2015 and 30th of June 2019. Patients were excluded if they presented in cardiac arrest, resided in a residential aged care facility, or were receiving palliative care services. Outcomes of interest included reattendance by ambulance, ED presentation; and, a high acuity outcome which we defined as a patient who (1) presented to ED and received an Australasian Triage Scale of category 1 (Resuscitation) or 2 (Emergency) AND was admitted to a ward OR (2) was admitted to an Intensive Care Unit, Coronary Care Unit or Catheter laboratory (regardless of triage category) OR (3) died. Outcomes of interest were considered within 48-h of initial EMS attendance.

RESULTS

A total of 1,777,950 cases were included in the study of which 3.1% were referred to a GP, 9.0% were discharged at scene without a follow-up recommendation, and 87.9% were transported to hospital. Patients referred to a GP were more likely than those discharged at scene to subsequently present to an ED within 48 h of their attendance (5.3% vs 3.8%). However, GP referral was not associated with any change to high acuity outcome (0.3% vs 0.2%) or ambulance reattendance (6.0% vs 6.0%) compared to discharge at scene. The only factors that were associated with ambulance reattendance, ED presentation, and a high acuity outcome were male gender and elevated temperature.

CONCLUSIONS

Despite increasing low and medium-acuity casework in this EMS system, paramedic referral to a GP is not common practice. Referring a patient to a GP did not reduce the likelihood of patients experiencing a high acuity outcome or recalling an ambulance within 48 h, suggesting opportunity exists to refine paramedic to GP referral practices.

Association between initial presenting level of consciousness and patient acuity - A potential application for secondary triage in emergency ambulance calls

INTRODUCTION

Conscious state assessment is important for the triage of emergency patients. In this study, we measured the association between ambulance patients' conscious state and high versus lower acuity, with a view to informing telephone triage assessment of conscious state.

METHODS

Data were analysed from one year of emergency ambulance incidents in Perth, Western Australia. Patient conscious state at the time of paramedic arrival was compared to acuity (based on paramedic assessment and management). We determined the proportion of high-acuity patients across six levels of consciousness (Alert, Confused, Drowsy, Voice Response, Pain Response, Unresponsive) overall, and within individual protocols of the Medical Priority Dispatch System (MPDS).

RESULTS

The proportion of high acuity patients increased with each step across the consciousness scale. Applying conscious state as a binary predictor of acuity, the largest increases occurred moving the threshold from Alert to Confused (22.0-48.6% high acuity) and Drowsy to Voice Response (61.9-89.5% high acuity). The Area Under the Curve (AUC) of the Receiver Operating Characteristic was 0.65. Within individual protocols, the highest AUC was in Cardiac Arrest (0.89), Overdose/Poisoning (0.81), Unknown Problem (0.76), Diabetic Problem, (0.74) and Convulsions/Fitting (0.73); and lowest in Heart problems (0.55), Abdominal Pain (0.55), Breathing Problems (0.55), Back Pain (0.53), and Chest Pain (0.52).

CONCLUSION

Based on these proportions of high acuity patients, it is reasonable to consider patients with any altered conscious state a high priority. The value of conscious state assessment for predicting acuity varies markedly between MPDS protocols. These findings could help inform secondary triage of ambulance patients during the emergency call.

Multi-criteria assignment problems for optimising the emergency medical services (EMS), considering non-homogeneous speciality of the emergency departments and EMS crews

Dispatching of the EMS crews (ambulances) to awaiting patients and then directing the patients, that are already onboard, to appropriate Emergency Departments (ED), is a nontrivial decision problem. In many emergency medical systems it is handled by the Medical Dispatcher using various strategies-sometimes preferring the closest unit. However, applying a wrong strategy may result in transferring acute-state patients, who require very specialised medical aid, to low-speciality EDs with insufficient treatment capabilities. Then, they would need to be re-transferred to referential units, prolonging substantially the time to receive treatment. In some cases such a delay might make the treatment less effective or even impossible. In this work we propose two multi-criteria mathematical optimisation problems-the first one allows us to calculate the ambulance-to-patient assignment, the second one-to establish the patient-to-hospital assignment. These problems not only take the time-to-support criterion into consideration but also optimise for the speciality of care received by each patient. The ED dispatching problem proposed allows both for direct transfers of patients to referential units and for re-transferring them from non-referential EDs. The performance of the proposed approach is tested in simulations with real-life emergency cases from the NEMSIS data set and compared with classic assignment strategies. The tests showed the proposed approach is able to produce better and more fit-for-purpose dispatching results than other strategies tested. Additionally, we propose a framework for embedding the proposed optimisation problems in the current EMS/ED dispatching process.

Differences between the dispatch priority assessments of emergency medical dispatchers and emergency medical services: a prospective register-based study in Finland

BACKGROUND

Responsive and efficient emergency medical services (EMS) require accurate telephone triage. In Finland, such services are provided by Emergency Response Centre Agency (ERC Agency). In 2018, a new Finnish computer-assisted emergency dispatch system was introduced: the Emergency Response Integrated Common Authorities (ERICA). After the introduction of ERICA, the appropriateness of EMS dispatch has not been investigated yet. The study´s objective is to determine the consistency between the priority triage of the emergency medical dispatcher (EMD) and the on-scene priority assessment of the EMS, and whether the priority assessment consistency varied among the dispatch categories.

METHODS

This was a prospective register-based study. All EMS dispatches registered in the Tampere University Hospital area from 1 August 2021 to 31 August 2021 were analysed. The EMD's mission priority triaged during the emergency call was compared with the on-scene EMS's assessment of the priority, derived from the pre-set criteria. The test performance levels were measured from the crosstabulation of true or false positive and negative values of the priority assessment. Statistical significance was analysed using the chi-square test and the Kruskal-Wallis H test, and p-values < 0.05 were considered significant.

RESULTS

Of the 6416 EMS dispatches analysed in this study, 36% (2341) were urgent according to the EMD's dispatch priority, and of these, only 29% (688) were urgent according to the EMS criteria. On the other hand, 64% (4075) of the dispatches were non-urgent according to the EMD's dispatch priority, of which 97% (3949) were non-urgent according to the EMS criteria. Moreover, there were differences between the EMD and EMS priority assessments among the dispatch categories (p < 0.001). The overall efficiency was 72%, sensitivity 85%, specificity 71%, positive predictive value 29%, and negative predictive value 97%.

CONCLUSION

While the EMD recognised the non-urgent dispatches with high consistency with the EMS criteria, most of the EMD's urgent dispatches were not urgent according to the same criteria. This may diminish the availability of the EMS for more urgent missions. Thus, measures are needed to ensure more accurate and therefore, more efficient use of EMS resources in the future.

Paramedic Education to Support the Use of Low-Acuity Care Pathways: A Scoping Review Protocol

Ambulance services worldwide have transformed over time into health care services that not only attend to life-threatening emergencies, but are also increasingly being utilised for patients with low-acuity or non-urgent illness and injury. As a result, there has been a need to adapt and include mechanisms to assist paramedics in the assessment and management of such patients, including alternative pathways of care. However, it has been identified that education and training for paramedics in the care of low-acuity patients is limited. This study aims to identify potential gaps in the literature and inform further research, paramedic education and training, patient care guidelines, and policy. A scoping review will be conducted utilising the Joanna Briggs Institutes methodology. A range of relevant electronic databases will be searched along with the grey literature, using search terms related to paramedic education for low-acuity patient care pathways. The search results will be screened by two authors and presented in the PRISMA-ScR format, with articles presented in tabular format and analysed thematically. The results of this scoping review will inform further research exploring paramedic education, clinical guidelines, policy and experiences in the management of low-acuity patients.

Study of prehospital video telehealth for callers with mental health-related complaints

BACKGROUND

Patients with mental health-related complaints are a key driver of increasing emergency medical service (EMS) demand; however, they require minimal intervention by EMS personnel. We describe the outcomes of a video telehealth study by mental health nurses (MHNs) in an EMS call-taking centre.

METHODS

This was a prospective study of adult (≥18 years) EMS callers with non-urgent mental health concerns in Victoria, Australia who underwent secondary triage between 1 March 2020 and 31 May 2021. Multivariable logistic regression models were used to compare the influence of video telehealth with voice-only triage by an MHN or secondary triage practitioner on the need for ambulance dispatch. One-week follow-up was conducted with video telehealth patients. Interviews were conducted with MHNs and a cost analysis was performed.

RESULTS

A total of 9588 patients were included of which 738 (7.7%) completed video consultation. The median age of video telehealth patients was 34 years (Q1: 24, Q3: 47), 62% were female and the most common complaint was suicidal or self-harm ideation (50.0%). After multivariable adjustment, video telehealth was associated with reduced odds of emergency ambulance dispatch (OR=0.173, 95% CI 0.144 to 0.209) when compared with voice-only triage by a secondary triage practitioner, but not voice-only triage by an MHN (OR=1.009, 95% CI 0.827 to 1.232). Video triage was associated with increased referrals to alternative services (excluding EDs) when compared with voice-only triage by an MHN (OR=1.321, 95% CI 1.087 to 1.606). Among those responding to 1-week follow-up, 92.8% were satisfied with the telehealth service and MHNs viewed it favourably. The average cost per video telehealth case was half that of a traditional secondary triage.

CONCLUSION

The use of video telehealth by MHNs was associated with fewer emergency ambulance dispatches when compared with voice-only triage by secondary triage practitioners, and increased referrals to alternative services. This cost-effective technology was viewed favourably by patients and MHNs. Expansion of video technology in EMS call taking warrants exploration.

Outcomes of paediatric patients who are not transported to hospital by Emergency Medical Services: a data linkage study

BACKGROUND

Data on the safety of non-transport decisions for paediatric patients attended by Emergency Medical Services (EMS) are lacking. We describe the characteristics and outcomes of paediatric non-transported patients in Victoria, Australia.

METHODS

A retrospective data linkage study of consecutive paediatric (aged <18 years) non-transported patients between January 2015 and June 2019. Patients were linked to ED, hospital admission and death records. Multivariable logistic regression analyses were used to determine factors associated with EMS recontact, ED presentation, hospital admission and an adverse event (death/cardiac arrest, intensive care unit admission or highest ED triage category) within 48 hours of the initial emergency call.

RESULTS

In total, 62 975 non-transported patients were included. The mean age was 7.1 (SD 6.0) years and 48.9% were male. Overall, 2.2% recontacted the EMS within 48 hours, 13.7% self-presented to a public ED, 2.4% were admitted to hospital and 0.1% had an adverse event, including two deaths. Among patients with paramedic-initiated non-transport (excluding transport refusals and transport via other means), 5.6% presented to a public ED, 1.1% were admitted to hospital and 0.05% had an adverse event. In the overall population, an abnormal vital sign on initial assessment increased the odds of hospital admission and an adverse event. Among paramedic-initiated non-transports, cases occurring in the early hours of the morning (04:00-08:00 hours) were associated with increased odds of subsequent hospital admission, while the odds of ED presentation and hospital admission also increased with increasing prior exposure to non-transported cases.

CONCLUSION

Adverse events were rare among paramedic-initiated non-transport cases. Vital sign derangements and attendance by paramedics with higher prior exposure to non-transports were associated with poorer outcomes and may be used to improve safety.

A predictive ambulance dispatch algorithm to the scene of a motor vehicle crash: the search for optimal over and under triage rates

Background

Calls for emergency medical assistance at the scene of a motor vehicle crash (MVC) substantially contribute to the demand on ambulance services. Triage by emergency medical dispatch systems is therefore important, to ensure the right care is provided to the right patient, in the right amount of time. A lights and sirens (L&S) response is the highest priority ambulance response, also known as a priority one or hot response. In this context, over triage is defined as dispatching an ambulance with lights and sirens (L&S) to a low acuity MVC and under triage is not dispatching an ambulance with L&S to those who require urgent medical care. We explored the potential for crash characteristics to be used during emergency ambulance calls to identify those MVCs that required a L&S response.

Methods

We conducted a retrospective cohort study using ambulance and police data from 2014 to 2016. The predictor variables were crash characteristics (e.g. road surface), and Medical Priority Dispatch System (MPDS) dispatch codes. The outcome variable was the need for a L&S ambulance response. A Chi-square Automatic Interaction Detector technique was used to develop decision trees, with over/under triage rates determined for each tree. The model with an under/over triage rate closest to that prescribed by the American College of Surgeons Committee on Trauma (ACS COT) will be deemed to be the best model (under triage rate of ≤ 5% and over triage rate of between 25–35%.

Results

The decision tree with a 2.7% under triage rate was closest to that specified by the ACS COT, had as predictors—MPDS codes, trapped, vulnerable road user, anyone aged 75 + , day of the week, single versus multiple vehicles, airbag deployment, atmosphere, surface, lighting and accident type. This model had an over triage rate of 84.8%.

Conclusions

We were able to derive a model with a reasonable under triage rate, however this model also had a high over triage rate. Individual EMS may apply the findings here to their own jurisdictions when dispatching to the scene of a MVC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12873-022-00609-5.

Use of a metalearner to predict emergency medical services demand in an urban setting

OBJECTIVE

To develop and internally validate a metalearner algorithm to predict the hourly rate of emergency medical services (EMS) dispatches in an urban setting.

METHODS

We performed an analysis of EMS data from New York City between years 2015-2019. Our outcome was hourly EMS dispatches, expressed as continuous data. Hours were split into derivation (75%) and validation (25%) datasets. Candidate variables included averages of prior rates, temporal and weather characteristics. We used a metalearner to evaluate and aggregate individual learners (generalized linear model, generalized additive model, random forest, multivariable adaptive regression splines, and extreme gradient boost). Four models were investigated: 1) temporal variables, 2) weather and temporal variables, and datasets in which weather data were lagged by 3) six and 4) twelve hours. In exploratory analyses, we constructed learners for high acuity and trauma encounters.

RESULTS

7,364,275 EMS dispatches occurred during the 43,823-hour period. When using temporal variables, the mean absolute error (MAE) rate was 11.5 dispatches in the validation dataset. These were slightly improved following incorporation of weather variables (MAE 11.3). When using 6- and 12-hour lagged weather variables, learners demonstrated lower accuracy (MAE 11.8 in 6-hour lagged datasets; 12.2 in 12-hour lagged dataset). All models had a coefficient of determination (R²) ≥0.91. The extreme gradient boosting and random forest learners were assigned the highest coefficients. In an investigation of variable importance, hour of day and average EMS dispatches over the previous six hours were the most important variables in both the extreme gradient boosting and random forest learners. The algorithm performed well at predicting frequently occurring peaks, with greater challenges at both extremes. Learners created high-acuity and for trauma-related encounters demonstrated superior MAE, but with lower R² in the validation cohort (MAE 6.9 and R² 0.84 for high acuity encounters; MAE 5.3 and R² 0.79 for trauma in learners using time and weather variables).

CONCLUSION

We developed an ensemble machine learning algorithm to predict EMS dispatches in an urban setting. These models demonstrated high accuracy, with MAEs <12 per hour in all. These algorithms may carry benefit in the real-time prediction of EMS responses, allowing for improved resource utilization.

The Impact of the COVID-19 Pandemic on Demand for Emergency Ambulances in Victoria, Australia

Objective: Relatively little has been reported about the impact of COVID-19 restrictions on emergency ambulance services. We describe the influence of the COVID-19 pandemic on the emergency ambulance system in Victoria, Australia.Methods: We performed an interrupted time series analysis of consecutive calls for ambulance from January 2018 to February 2021, including two waves of COVID-19. The COVID-19 lockdown period included seven months of stay-at-home restrictions (16/03/2020-18/10/2020). Nineteen weeks of post-lockdown data were included (19/10/2020-28/02/2021).Results: In total, 2,356,326 consecutive calls were included. COVID-19 lockdown was associated with an absolute reduction of 64,991 calls (almost 2,100 calls/week). According to time series analysis, lockdown was associated with a 12.6% reduction in weekly calls (IRR = 0.874 [95% CI 0.811, 0.941]), however no change in long-term trend (IRR = 1.000 [95% CI 0.996, 1.003]). During lockdown, the long-term trend of attendances to patients with suspected acute coronary syndromes (ACS, IRR = 1.006 [95% CI 1.004, 1.009]) and mental health-related issues (IRR = 1.005 [95% CI 1.002, 1.008]) increased. After lockdown, the call volume was 5.6% below pre-COVID-19 predictions (IRR = 0.944 [95% CI 0.909, 0.980]), however attendances for suspected ACS were higher than predicted (IRR = 1.069 [95% CI 1.009, 1.132]). Ambulance response times deteriorated, and total case times were longer than prior to the pandemic, driven predominantly by extended hospital transfer times.Conclusion: The COVID-19 pandemic had a dramatic impact on the emergency ambulance system. Despite lower call volumes post-lockdown than predicted, we observed deteriorating ambulance response times, extended case times and hospital delays. The pattern of attendance to patients with suspected ACS potentially highlights the collateral burden of delaying treatment for urgent conditions.

Weather and temporal models for emergency medical services: An assessment of generalizability

BACKGROUND

Emergency medical services (EMS) response volume has been linked to weather and temporal factors in a regional EMS system. We aimed to identify if models of EMS utilization incorporating these data are generalizable through geographically disparate areas in the United States.

METHODS

We performed a retrospective analysis of EMS dispatch data from four regions: New York City, San Francisco, Cincinnati, and Marin County for years 2016-2019. For each model, we used local weather data summarized from the prior 6 h into hourly bins. Our outcome for each model was EMS dispatches as count data. We fit and optimized a negative binomial regression model for each region, to estimate incidence rate ratios. We compared findings to a prior study performed in Western Pennsylvania.

RESULTS

We included 5,940,637 EMS dispatches from New York City, 809,405 from San Francisco, 260,412 from Cincinnati, and 77,461 from Marin County. Models demonstrated consistency with the Western Pennsylvania model with respect to temperature, season, wind speed, dew point, and time of day; both in terms of direction and effect size when expressed as incidence rate ratios. Precipitation was associated with increasing dispatches in the New York City, Cincinnati, and Marin County models, but not the San Francisco model.

CONCLUSION

With minor differences, regional models demonstrated consistent associations between dispatches and time and weather variables. Findings demonstrate the generalizability of associations between these variables with respect to EMS use. Weather and temporal factors should be considered in predictive modeling to optimize EMS staffing and resource allocation.

Drivers of Increasing Emergency Ambulance Demand

Objectives: Although the factors driving emergency department demand have been extensively investigated, a comparatively minimal amount is known about the factors that are driving an increase in emergency ambulance demand. Methods: We conducted a retrospective observational study of consecutive cases attended by Ambulance Victoria in Melbourne, Australia from 2008 to 2015. Incidence rates were calculated, and adjusted time series regression analyses were performed to assess the driving factors of ambulance demand. Results: A total of 2,443,952 consecutive cases were included. Demand grew by 29.2% over the 8-year period. The age-specific incidence increased significantly over time for patients aged < 60 years, but not for patients aged ≥ 60 years. After adjustment for seasonality and population growth, demand increased by 1.4% per annum (incident rate ratio [IRR] = 1.014 [1.011-1.017]). The largest annual growth in demand was observed in patients with a history of mental health issues (IRR = 1.058 [1.054-1.062]), alcohol/drug abuse (IRR = 1.061 [1.056-1.066]), or a Charlson Comorbidity Index [CCI] score ≥ 4 (IRR = 1.045 [1.039-1.051]). Cases involving patients of relative socio-economic/educational disadvantage, younger age, or with no preexisting health conditions according to the CCI also grew faster than the overall patient population. Cases requiring transport to hospital increased by 1.2% annually (IRR = 1.012 [1.009-1.016]), although patients not requiring medical intervention from paramedics increased by 6.7% annually (IRR = 1.067 [1.063-1.072]). Conclusions: Increases in ambulance demand exceeded population growth. Emergency ambulances were increasingly utilized for transport of patients who did not require medical intervention from paramedics. Identifying the characteristics of patients driving ambulance demand will enable targeted demand management strategies.