Analyzing emergency call volume, call durations, and unanswered calls during the first two waves of the COVID-19 pandemic compared to 2019: An observational study of routine data from seven bavarian dispatch centres.

Background: The spread of the COVID-19 pandemic and the corresponding implementation of measures such as stay-at-home orders and curfews had a major impact on health systems, including emergency medical services. This study examined the effect of the pandemic on call volumes, duration of calls and unanswered calls to the emergency number 112. Method: For this retrospective, descriptive study, 986,650 calls to seven emergency dispatch centres in Bavaria between January 01, 2019 and May 31, 2021 were analysed. The absolute number of calls and calls per 100,000 inhabitants as well as the number of unanswered calls are reported. The Mann‒Whitney U test was used to compare mean call durations between 2019 and 2020/2021 during several periods. Results: Call volume declined during the pandemic, especially during periods with strict lockdown restrictions. The largest decline (-12.9 %) occurred during the first lockdown. The largest reduction in the number of emergency calls overall (-25.3 %) occurred on weekends during the second lockdown. Emergency call duration increased, with the largest increase (+13 s) occurring during the "light" lockdown. The number of unanswered calls remained at a similar level as before the pandemic. Conclusion: This study showed that the studied Bavarian dispatch centres experienced lower call volumes and longer call durations during the first two waves of the COVID-19 pandemic (up to May 2021). Longer call durations could be the result of additional questions to identify potentially infectious patients. The fact that the number of unanswered calls hardly changed may indicate that the dispatch centres were not overwhelmed during the study period.

Ambulance deployment without transport: a retrospective difference analysis for the description of emergency interventions without patient transport in Bavaria.

BACKGROUND: Not all patients who call the ambulance service are subsequently transported to hospital. In 2018, a quarter of deployments of an emergency ambulance in Bavaria were not followed by patient transport. This study describes factors that influence patient transport rates. METHOD: This is a retrospective cross-sectional study based on data from all Integrated Dispatch Centres of the Free State of Bavaria in 2018. Included were ambulance deployments without emergency physician involvement, which were subdivided into ambulance deployments without transport and ambulance deployments with transport. The proportion of transported patients were determined for the primary reasons for deployment and for the different community types. On-scene time was compared for calls with and without patient transport. Differences were tested for statistical significance using Chi2 tests and the odds ratio was calculated to determine differences between groups. RESULTS: Of 510,145 deployments, 147,621 (28.9%) could be classified as ambulance deployments without transport and 362,524 (71.1%) as ambulance deployments with transport.The lowest proportion of patients transported was found for activations where the fire brigade was involved ("fire alarm system" 0.6%, "fire with emergency medical services" 5.4%) and "personal emergency response system active alarm" (18.6%). The highest transport rates were observed for emergencies involving "childbirth/delivery" (96.9%) and "trauma" (83.2%). A lower proportion of patients is transported in large cities as compared to smaller cities or rural communities; in large cities, the odds ratio for emergencies without transport is 2.02 [95% confidence interval 1.98-2.06] referenced to rural communites. The median on-scene time for emergencies without transport was 20.8 min (n = 141,052) as compared to 16.5 min for emergencies with transport (n = 362,524). The shortest on-scene times for emergencies without transport were identified for activations related to "fire alarm system" (9.0 min) and "personal emergency response system active alarm" (10.6 min). CONCLUSION: This study indicates that the proportion of patients transported depends on the reason for deployment and whether the emergency location is urban or rural. Particularly low transport rates are found if an ambulance was dispatched in connection with a fire department operation or a personal emergency medical alert button was activated. The on-scene-time of the rescue vehicle is increased for deployments without transport. The study could not provide a rationale for this and further research is needed. Trial registration This paper is part of the study "Rettungswageneinsatz ohne Transport" ["Ambulance deployment without transport"] (RoT), which was registered in the German Register of Clinical Studies under the number DRKS00017758.

Pre-Hospital Emergency Medical Services Utilization Amid COVID-19 in 2020: Descriptive Study Based on Routinely Collected Dispatch Data in Bavaria, Germany.

BACKGROUND AND IMPORTANCE: The COVID-19 pandemic affected the utilization of health care services and posed organizational challenges. While many previous studies focused on the misuse of pre-hospital EMS for low-urgency health problems, the pandemic has put more emphasis on the avoidance of medically necessary calls. OBJECTIVE: To compare the utilization of pre-hospital emergency medical services before and after specific pandemic periods. DESIGN, SETTING AND PARTICIPANTS: This was a retrospective, descriptive analysis of routine data from 26 dispatch centers in Bavaria, Germany. OUTCOMES MEASURE AND ANALYSIS: We investigated the number of emergencies per 100,000 population, as well as the relative change in the emergency rates and transport rates in 2020, compared to the two previous years. Boxplots showed the distributions across the Bavarian districts per calendar week. The mean rates and standard deviations as well as the relative changes were presented for the specific periods. A paired samples t-test was used to compare the rates. MAIN RESULTS: Compared to the average of the two previous years, the emergency rates in 2020 were lower in 35 out of 52 calendar weeks. The strongest reductions were observed during the first wave, where the average emergency rate declined by 12.9% (SD 6.8, p < 0.001). There was no statistically significant difference in the overall emergency rate during the summer holidays. Lower transport rates were observed throughout the year, especially during the first wave. CONCLUSIONS: Utilization of pre-hospital emergency medical services decreased in 2020, especially during the periods with strict measures. This could be due to the lower morbidity from the behavioral changes during the pandemic, but also to the avoidance of medical services for both less urgent and severe conditions. While a reduction in unnecessary care would be beneficial, patients must be encouraged to seek necessary urgent care, even during a pandemic.

[Differences between emergency medical services operations with and without patient transport : A retrospective analysis of dispatch center data in a territorial state]. / Unterschiede zwischen Rettungsdiensteinsätzen mit und ohne Patiententransport : Eine retrospektive Analyse der Leitstellendaten in einem Flächenstaat.

BACKGROUND: The use of the emergency medical services (EMS) in Bavaria has been increasing for years. We hypothesized that emergency response without patient transport (RoT) is often an expression of inadequate alert planning. The aim of the study was to describe the differences between the integrated dispatch centers (ILSs) for such operations with regard to the characteristics of transport quotas and ranges according to the reason for deployment as well as times and days of the week. METHOD: Retrospective cross-sectional study of data from all 26 ILSs in the Free State of Bavaria in 2018. Transport quotas for emergency operations for essential reasons without emergency physician involvement were analyzed comparatively in relation to dispatch center area, time of day, and day of the week. Deployments were categorized as RoT or ambulance deployment with transport (TP). RESULTS: Of 510,145 call-outs, 147,621 (28.9%) were RoT and 362,524 (71.1%) were TP. There were significant regional differences in the transport quotas for all deployment reasons investigated. The highest range among the ILSs was found for the deployment reasons "fire alarm system" (16.8 percentage points), "personal emergency response system" (16.1%), and "heart/circulation" (14.6%). In the morning hours, the number of calls decreases with increasing TP. The fewest RoT took place between 8 and 10 am. The days of the week analysis revealed small differences in the frequency of RoT on Mondays as well as on weekends without planning relevance. CONCLUSION: We found significant differences in the ranges. This could indicate locally different alert planning specifications or dispatching decisions by the ILS. The control centers probably have considerable potential for controlling and improving resource allocation.

Differences between cases admitted to hospital and discharged from the emergency department after emergency medical services transport.

OBJECTIVE: Rising emergency medical services (EMS) utilisation increases transport to hospital emergency departments (ED). However, some patients receive outpatient treatment (discharged) while others are hospitalised (admitted). The aims of this analysis were to compare admitted and discharged cases, to assess whether cases that were discharged from the ED could be identified using dispatch data and to compare dispatch keyword categories and hospital diagnoses. DESIGN: Retrospective observational study using linked secondary data. SETTING AND PARTICIPANTS: 78 303 cases brought to 1 of 14 ED in the city of Munich, Germany, by EMS between 1 July 2013 and 30 June 2014. MAIN OUTCOME MEASURES: Characteristics of admitted and discharged cases were assessed. Logistic regression was used to estimate the association between discharge and age, sex, time of day, ambulance type and dispatch keyword category. Keyword categories were compared to hospital diagnoses. RESULTS: 39.4% of cases were discharged. They were especially likely to be young (OR 10.53 (CI 9.31 to 11.92), comparing <15-year-olds to >70-year-olds) and to fall under the categories 'accidents/trauma' (OR 2.87 (CI 2.74 to 3.01)) or 'other emergencies (unspecified)' (OR 1.23 (CI 1.12 to 1.34) (compared with 'cardiovascular'). Most frequent diagnoses came from chapter 'injury and poisoning' (30.1%) of the 10th revision of the international statistical classification of disease and related health problems (ICD-10), yet these diagnoses were more frequent at discharge (42.7 vs 22.0%) whereas circulatory system disease was less frequent (2.6 vs 21.8%). Except for accidents/trauma and intoxication/poisoning many underlying diagnoses were observed for the same dispatch keyword. CONCLUSION: Young age and dispatch for accidents or trauma were the strongest predictors of discharge. Even within the same dispatch keyword category the distribution of diagnoses differed between admitted and discharged cases. Discharge from the ED does not indicate that urgent response was unnecessary. However, these cases could be suitable for allocation to hospitals with low inpatient bed capacities and are of particular interest for future studies regarding the urgency of their condition.

Use of pre-hospital emergency medical services in urban and rural municipalities over a 10 year period: an observational study based on routinely collected dispatch data.

BACKGROUND: Pre-hospital emergency medical services (EMS) are an integral part of emergency medical care. EMS planning can be achieved by analyzing patterns of use. However, long-term time trends of EMS use have rarely been studied. The objective of this retrospective study was to investigate utilization patterns over a ten year period, and to compare utilization trends between urban and rural municipalities and between events with and without prehospital emergency physician (PEP) dispatch. METHODS: Routine data collected by 26 dispatch centers in the federal state of Bavaria, Germany, from 2007 to 2016 was analyzed. Emergency locations were classified into five levels of rurality. Negative binomial mixed effects regression models were fitted to predict emergency rates and to investigate differences in rates and utilization trends. Graphical representation methods were used to compare distribution of transport rates and distribution across daytime and weekday. RESULTS: Twelve million two hundred thousand one hundred fifty-five dispatches assigned to 7,725,636 single emergencies were included. The mean number of emergencies per year and 1000 population (emergency rate) was 42.8 (±16.0) in rural municipalities and 80.7 (±9.3) in large cities. Compared to rural municipalities, cities had higher emergency rates without (IRR = 3.0, CI 2.2-4.0) and with pre-hospital physicians (IRR = 1.5, CI 1.2-2.0). Between 2007 and 2016, the absolute number of emergencies increased by 49.1%. Estimated annual percent change of emergency rates without physician activation ranged from 5.7% (CI 4.3-7.1) in cities to 7.8% (CI 7.6-7.9) in rural areas. Changes in emergency rates with physician attendance were lower, with estimated increases between 1.3 and 2.4%. The average proportion of patients transported to a hospital was lower in cities and remained unchanged. There were no considerable differences or changes in the distribution across daytime and weekdays. CONCLUSION: Differences between cities and other areas suggest that the planning of EMS should be targeted to regional characteristics. A substantial increase in emergency rates was observed across all areas of Bavaria, but did not impact transport rates or temporal distributions. Further research is needed to better understand the urgency of emergency events and reasons behind increasing EMS utilization.