Design
The research involved a comprehensive register-based study examining all emergency ambulance dispatches that occurred in the Region Zealand from the years 2013 to 2022. This robust analysis followed the principles of the RECORD statement, which expands upon the well-established STROBE statement to ensure transparency and completeness in reporting observational research findings.
Setting
Denmark, with a population of approximately 5.9 million as of January 2022, has administratively been categorized into five distinct regions since 2007. Each region independently oversees its healthcare system, including Emergency Medical Services (EMS), ensuring that medical assistance and hospital admissions are free for all residents. For non-emergency situations, general practitioners are accessible during regular business hours, while an out-of-hours doctor’s service is available on weekends, public holidays, and outside of typical working hours, providing patients with both telephone consultations and in-person examinations. The comprehensive EMS is managed through a well-structured network of regional Emergency Medical Dispatch Centers (EMDCs). In response to emergency calls made to the number 1-1-2, trained dispatchers who are either specialized nurses or paramedics evaluate the circumstances and send the appropriate medical resources, which may include ambulances and advanced emergency response units if necessary. The dispatcher’s decision-making process is guided by a criteria-based protocol known as the Danish Index for Emergency Care. Even though a new administrative EMDC software was implemented in October 2017, the dispatch criteria have consistently remained unchanged throughout the entire study period.
According to statutory requirements, every ambulance must be operated by a minimum of two emergency medical technicians, although they can additionally include paramedics for advanced medical care. The advanced emergency response units feature a helicopter emergency medical service as well as mobile critical care teams staffed with physicians and paramedics to ensure effective patient management.
Region Zealand, located in eastern Denmark, spans an area of 7,274 square kilometers and is home to around 850,000 residents. Roskilde stands as the largest city with a population of 51,916, alongside four other cities that house between 20,000 and 45,000 people. As of 2022, the region has been segmented into four catchment areas, each represented by a hospital equipped with an emergency department, although it is noteworthy that two of these emergency departments were closed during the study period. Alarmingly, Region Zealand reports the lowest life expectancy in comparison to Denmark’s other regions.
Fig. 1
Map of Region Zealand. Illustrating the four catchment areas corresponding to the four hospitals with emergency departments in the region
A unique personal identification number is assigned to every Danish citizen at birth or upon immigrating, facilitating precise individual-level linkage of data with all Danish registries.
Participants
The study encompasses all emergency ambulance dispatches that occurred in Region Zealand from January 1, 2013, to December 31, 2022. Each emergency ambulance dispatch is classified into priority A or B categories. Priority A dispatches, activated with lights and sirens, respond to patients experiencing potentially life-threatening conditions, while priority B dispatches, operating without lights and sirens, are designated for patients whose conditions could potentially escalate into life-threatening situations. Ambulances may be deployed either following a 1-1-2 emergency call or upon direct requests from healthcare professionals, including general practitioners and personnel working in pre-hospital or hospital settings. Additionally, the Danish EMS includes two other priority classifications: Priority C entails urgent or planned transport for patients who require monitoring and possibly treatment during transportation, while Priority D is geared towards planned supine transport for patients who do not necessitate monitoring or treatment.
Exclusions were made for interhospital ambulance transports and for dispatches responding to incidents beyond the region’s borders. If a patient experienced multiple separate ambulance transports during the study period, each of those dispatches was accounted for in the study’s findings. However, if several ambulances were dispatched for a single incident involving one patient, only one ambulance was factored into the study’s analysis. Dispatches remained part of the study even when the patient was not taken to a hospital. The response time calculation spanned from the moment the ambulance was requested until the arrival time of the first ambulance on the scene, while instances of negative response times were omitted from further analyses.
For comparative purposes, absolute numbers of ambulance dispatches for priorities C and D were also calculated. Dispatches were excluded if patients were taken from a hospital to another location, such as their residence, rendering it impossible to identify cases wherein the patient was transferred to a hospital for ambulatory care.
Data sources
Data were meticulously gathered from administrative records that are routinely maintained by the EMDC in Region Zealand. The comprehensive database employed to construct the study population encompassed all EMS dispatches from the specified study period. Following a transition to updated administrative EMDC software in October 2017, the final dataset that encapsulated the entire study duration from 2013 to 2022 was synthesized from two distinct datasets that possessed differing structural attributes.
This merging of datasets required careful management, at which point the variables of interest were harmonized to maintain consistency in the final dataset designated for analytical purposes. The data comprised extensive details on each ambulance dispatch, including essential identifiers like the patient’s personal identification number, detailed time stamps, and geographical location information. In order to evaluate the Charlson Comorbidity Index (CCI), diagnosis codes were sourced from the Danish National Patient Register and linked to individual patients through their personal identification numbers. The CCI was calculated based on data spanning 10 years prior to the emergency ambulance dispatch, ensuring a comprehensive assessment of each patient’s comorbidities. The comorbidity index was categorized into three distinct groups: 0 (no comorbidities), 1–2 (mild comorbidities), and ≥3 (severe comorbidities). For patients absent relevant diagnoses in the Danish National Patient Register, the CCI was assigned a value of 0.
Data were stored securely in compliance with applicable regulations and guidelines to ensure patient confidentiality and data integrity.
Variables
The study’s primary outcomes included the total number of emergency ambulance dispatches, the incidence rate (IR) of ambulance dispatches per 1,000 residents annually, and the median response time. Secondary outcomes were categorized by the sex, age group, and CCI of the patients. Information regarding age and sex was derived from the patient’s unique personal identification number.
Statistical analysis
A thorough descriptive analysis was conducted to outline the characteristics of the study population utilizing frequency distributions (n, %) both overall and segmented by catchment area.
Poisson regression analyses were employed to explore time trends in the rate of emergency ambulance dispatches per 1,000 residents annually. These analyses took into account both the calendar year and the catchment area as independent variables, with adjustments made for the median age of ambulance patients to address increases in patient age over time. The reference year selected for comparative analysis was 2013, while the reference catchment area was “East,” noted for its lowest incidence rate. The outcomes of these analyses were presented as incidence rate ratios (IRR) alongside their corresponding 95% confidence intervals (95% CI).
Ordinal logistic regression analyses were executed to scrutinize trends concerning higher odds of comorbidity. The analysis framework included calendar year, catchment area, and age group as key variables. Changes in response times for both priority A and B dispatches were assessed using linear regression, integrating calendar year and catchment area among the independent variables. Given that response time data exhibited a left-skewed distribution, both log- and rank transformations were applied to normalize the data.
All statistical analyses were performed for the entire dataset as well as stratified by the catchment area where each incident occurred. A p-value
Data management and statistical analysis were effectively conducted using R version 4.4.0.
**Interview with Dr. Mia Jensen, Lead Researcher on Emergency Medical Services in Region Zealand**
**Editor:** Thank you for joining us today, Dr. Jensen. Your recent study on emergency ambulance dispatches in Region Zealand has garnered attention. Can you tell us what prompted this comprehensive analysis?
**Dr. Jensen:** Thank you for having me! The primary motivation for this study was to understand the patterns and efficiency of our emergency medical services, particularly given that Region Zealand has been reported to have the lowest life expectancy in Denmark. By analyzing ambulance dispatch data from 2013 to 2022, we aimed to identify areas for improvement in emergency response.
**Editor:** That’s a significant undertaking. Can you explain how you structured this research and what methodologies you employed?
**Dr. Jensen:** Certainly! We conducted a register-based study that followed the RECORD statement principles, which are designed to enhance the transparency and completeness of observational research. We examined all emergency ambulance dispatches in Region Zealand, categorizing them into priority A and B, based on the urgency of the medical situation. This allowed us to draw clear insights into response times and dispatch patterns.
**Editor:** Speaking of response times, how did your study define and measure this crucial metric?
**Dr. Jensen:** We calculated response times from the moment the ambulance was requested to when the first unit arrived on the scene. This meticulous measurement is vital because timely medical response can significantly affect patient outcomes in emergency situations. Importantly, we excluded instances of negative response times to ensure data integrity.
**Editor:** With the comprehensive data collected, what were some key findings of your research?
**Dr. Jensen:** Our analysis revealed not only the number of dispatches but also their incidence rate per 1,000 residents, and the median response time for each priority category. Interestingly, we also assessed the impact of patient demographics and comorbidities on dispatch efficiency, which is critical for tailoring EMS resources more effectively in the future.
**Editor:** It’s intriguing to hear about the link between patient demographics and ambulance use. How do you think the findings of your study could influence emergency medical practices in Denmark?
**Dr. Jensen:** One of our goals is to provide insights that can help policymakers and healthcare administrators optimize emergency services. By understanding dispatch trends and response times in relation to patient demographics, we can enhance training for dispatchers, refine protocols, and ultimately improve patient care. Additionally, these findings could support the need for more resources in specific areas of Region Zealand to better cater to the community’s needs.
**Editor:** Thank you for sharing your insights, Dr. Jensen. As this research continues to unfold, we look forward to seeing how it shapes the future of emergency medical services in Denmark.
**Dr. Jensen:** Thank you for having me! I’m excited to see how our work contributes to ongoing improvements in healthcare delivery for all residents.
