Why and when citizens call for emergency help: an observational study of 211,193 medical emergency calls.

BACKGROUND: A medical emergency call is citizens' access to pre-hospital emergency care and ambulance services. Emergency medical dispatchers are gatekeepers to provision of pre-hospital resources and possibly hospital admissions. We explored causes for access, emergency priority levels, and temporal variation within seasons, weekdays, and time of day for emergency calls to the emergency medical dispatch center in Copenhagen in a two-year study period (December 1(st), 2011 to November 30(th), 2013). METHODS: Descriptive analysis was performed for causes for access and emergency priority levels. A Poisson regression model was used to calculate adjusted ratio estimates for the association between seasons, weekdays, and time of day overall and stratified by emergency priority levels. RESULTS: We analyzed 211,193 emergency calls for temporal variation. Of those, 167,635 calls were eligible for analysis of causes and emergency priority level. "Unclear problem" was the most frequent category (19%). The five most common causes with known origin were categorized as "Wounds, fractures, minor injuries" (13%), "Chest pain/heart disease" (11%), "Accidents" (9%), "Intoxication, poisoning, drug overdose" (8%), and "Breathing difficulties" (7%). The highest emergency priority levels (Emergency priority level A and B) were assigned in 81% of calls. In the analysis of temporal variation, the total number of calls peaked at wintertime (26%), Saturdays (16%), and during daytime (39%). CONCLUSION: The pattern of citizens' contact causes fell into four overall categories: unclear problems, medical problems, intoxication and accidents. The majority of calls were urgent. The magnitude of unclear problems represents a modifiable factor and highlights the potential for further improvement of supportive dispatch priority tools or educational interventions at dispatch centers. Temporal variation was identified within seasons, weekdays and time of day and reflects both system load and disease occurrence. Data on contact patterns could be utilized in a public health perspective, benchmarking of EMS systems, and ultimately development of best practice in the area of emergency medicine.

Dynamic ambulance reallocation for the reduction of ambulance response times using system status management.

OBJECTIVES: Dynamically reassigning ambulance deployment locations throughout a day to balance ambulance availability and demands can be effective in reducing response times. The objectives of this study were to model dynamic ambulance allocation plans in Singapore based on the system status management (SSM) strategy and to evaluate the dynamic deployment plans using a discrete event simulation (DES) model. METHODS: The geographical information system-based analysis and mathematical programming were used to develop the dynamic ambulance deployment plans for SSM based on ambulance calls data from January 1, 2011, to June 30, 2011. A DES model that incorporated these plans was used to compare the performance of the dynamic SSM strategy against static reallocation policies under various demands and travel time uncertainties. RESULTS: When the deployment plans based on the SSM strategy were followed strictly, the DES model showed that the geographical information system-based plans resulted in approximately 13-second reduction in the median response times compared to the static reallocation policy, whereas the mathematical programming-based plans resulted in approximately a 44-second reduction. The response times and coverage performances were still better than the static policy when reallocations happened for only 60% of all the recommended moves. CONCLUSIONS: Dynamically reassigning ambulance deployment locations based on the SSM strategy can result in superior response times and coverage performance compared to static reallocation policies even when the dynamic plans were not followed strictly.

Can emergency medical services use turnaround time as a proxy for measuring ambulance offload time?

BACKGROUND: "Offload delay" occurs when the transfer of care from paramedics to the emergency department (ED) is prolonged. Accurately measuring the delivery interval or "offload" is important, because it represents the time patients are waiting for definitive care. Because recording this interval presents a significant challenge, most emergency medical services systems only measure the complete at-hospital time or "turnaround interval," and most offload delay research and policy is based on this proxy. OBJECTIVE: This study sought to test the validity of using the turnaround interval as a surrogate for the delivery interval. METHODS: This observational study examined levels of correspondence, or correlation, between delivery interval and turnaround interval, to assess whether turnaround is a reasonable surrogate for delivery. Delivery and turnaround intervals were logged by Richmond Ambulance Authority (RAA) in Richmond, Virginia, United States from April 1 to December 31, 2008. A total of 1732 ambulance runs from RAA were included. RESULTS: Pearson's correlation analysis showed a good correlation between turnaround and actual offload time (delivery), with a coefficient (r) of 0.753. A post hoc analysis explored patterns in the relationship, which is quite complex. CONCLUSION: The results show that the correlation between the delivery and turnaround intervals is good. However, there remains much to be learned about the at-hospital time intervals and how to use these data to make decisions that will improve resource utilization and patient care. Efforts to establish a method to accurately record the delivery interval and to understand the at-hospital portion of the ambulance response are necessary.

Comparing emergency medical service systems--a project of the European Emergency Data (EED) Project.

AIM: The aim of this prospective study was the comparison of four emergency medical service (EMS) systems-emergency physician (EP) and paramedic (PM) based-and the impact of advanced live support (ALS) on patients status in preclinical care. METHODS: The EMS systems of Bonn (GER, EP), Cantabria (ESP, EP), Coventry (UK, PM) and Richmond (US, PM) were analysed in relation to quality of structure, process and performance when first diagnosis on scene was cardiac arrest (OHCA), chest pain or dyspnoea. Data were collected prospectively between 01.01.2001 and 31.12.2004 for at least 12 month. RESULTS: Over all 6277 patients were included in this study. The rate of drug therapy was highest in the EP-based systems Bonn and Cantabria. Pain relief was more effective in Bonn in patients with severe chest pain. In the group of patients with chest pain and tachycardia ≥ 120 beats/min, the heart rate was reduced most effective by the EP-systems. In patients with dyspnoea and S(p)O(2) <90% the improvement of oxygen saturation was most effective in Bonn and Richmond. After OHCA significant more patients reached the hospital alive in EMS systems with EPs than in the paramedic staffed (Bonn = 35.6%, Cantabria = 30.1%; Coventry = 11.9%, Richmond = 9.2%). The introduction of a Load Distributing Band chest compression device in Richmond improved admittance rate after OHCA (21.7%) but did not reach the survival rate of the Bonn EMS system. CONCLUSIONS: Higher qualification and greater training and experience of ALS unit personnel increased survival after OHCA and improved patient's status with cardiac chest pain and respiratory failure.

Geographic-time distribution of ambulance calls in Singapore: utility of geographic information system in ambulance deployment (CARE 3).

INTRODUCTION: Pre-hospital ambulance calls are not random events, but occur in patterns and trends that are related to movement patterns of people, as well as the geographical epidemiology of the population. This study describes the geographic-time epidemiology of ambulance calls in a large urban city and conducts a time demand analysis. This will facilitate a Systems Status Plan for the deployment of ambulances based on the most cost effective deployment strategy. MATERIALS AND METHODS: An observational prospective study looking at the geographic-time epidemiology of all ambulance calls in Singapore. Locations of ambulance calls were spot mapped using Geographic Information Systems (GIS) technology. Ambulance response times were mapped and a demand analysis conducted by postal districts. RESULTS: Between 1 January 2006 and 31 May 2006, 31,896 patients were enrolled into the study. Mean age of patients was 51.6 years (S.D. 23.0) with 60.0% male. Race distribution was 62.5% Chinese, 19.4% Malay, 12.9% Indian and 5.2% others. Trauma consisted 31.2% of calls and medical 68.8%. 9.7% of cases were priority 1 (most severe) and 70.1% priority 2 (moderate severity). Mean call receipt to arrival at scene was 8.0 min (S.D. 4.8). Call volumes in the day were almost twice those at night, with the most calls on Mondays. We found a definite geographical distribution pattern with heavier call volumes in the suburban town centres in the Eastern and Southern part of the country. We characterised the top 35 districts with the highest call volumes by time periods, which will form the basis for ambulance deployment plans. CONCLUSION: We found a definite geographical distribution pattern of ambulance calls. This study demonstrates the utility of GIS with despatch demand analysis and has implications for maximising the effectiveness of ambulance deployment.

Using demand analysis and system status management for predicting ED attendances and rostering.

INTRODUCTION: It has been observed that emergency department (ED) attendances are not random events but rather have definite time patterns and trends that can be observed historically. OBJECTIVES: To describe the time demand patterns at the ED and apply systems status management to tailor ED manpower demand. METHODS: Observational study of all patients presenting to the ED at the Singapore General Hospital during a 3-year period was conducted. We also conducted a time series analysis to determine time norms regarding physician activity for various severities of patients. RESULTS: The yearly ED attendances increased from 113387 (2004) to 120764 (2005) and to 125773 (2006). There was a progressive increase in severity of cases, with priority 1 (most severe) increasing from 6.7% (2004) to 9.1% (2006) and priority 2 from 33.7% (2004) to 35.1% (2006). We noticed a definite time demand pattern, with seasonal peaks in June, weekly peaks on Mondays, and daily peaks at 11 to 12 am. These patterns were consistent during the period of the study. We designed a demand-based rostering tool that matched doctor-unit-hours to patient arrivals and severity. We also noted seasonal peaks corresponding to public holidays. CONCLUSION: We found definite and consistent patterns of patient demand and designed a rostering tool to match ED manpower demand.

An observational, prospective study exploring the use of heart rate variability as a predictor of clinical outcomes in pre-hospital ambulance patients.

OBJECTIVE: To explore the use of pre-hospital heart rate variability (HRV) as a predictor of clinical outcomes such as hospital admission, intensive care unit (ICU) admission and mortality. We also implemented an automated pre-analysis signal processing algorithm and multiple principal component analysis (PCA) for outcomes. MATERIALS AND METHODS: We conducted a prospective observational clinical study at an emergency medical services (EMS) system in a medium sized urban setting in the United States. Electrocardiogram (ECG) data was obtained from a sample of 45 ambulance patients conveyed to a tertiary hospital, monitored with a LIFEPAK12 defibrillator/monitor. After extracting the data, filtering for noise reduction and isolating non-sinus beats, various HRV parameters were computed. These included time domain, frequency domain and geometric parameters. PCA was performed on the hospital outcomes for these patients. RESULTS: We used a combination of HRV parameters, age and vital signs such as respiratory rate, SpO2 and Glasgow coma score (GCS) in a PCA analysis. For predicting admission to ICU, sensitivity was 100%, specificity was 48.6%, and negative predictive value (NPV) was 100%; for predicting admission to hospital, sensitivity was 78.9%, specificity was 85.7%, and NPV was 75.0%; for predicting death, sensitivity was 50.0%, specificity was 100%, and NPV was 97.4%. There was also a significant correlation of several HRV parameters with length of hospital stay. CONCLUSIONS: With signal processing techniques, it is feasible to filter and analyze ambulance ECG data for HRV. We found a combination of HRV parameters and traditional 'vital signs' to have an association with clinical outcomes in pre-hospital patients. This may have potential as a triage tool for ambulance patients.

An observational study describing the geographic-time distribution of cardiac arrests in Singapore: what is the utility of geographic information systems for planning public access defibrillation? (PADS Phase I).

INTRODUCTION: Public access defibrillation (PAD) has shown potential to increase cardiac arrest survival rates. OBJECTIVES: To describe the geographic epidemiology of prehospital cardiac arrest in Singapore using geographic information systems (GIS) technology and assess the potential for deployment of a PAD program. METHODS: We conducted an observational prospective study looking at the geographic location of pre-hospital cardiac arrests in Singapore. Included were all patients with out-of-hospital cardiac arrest (OHCA) presented to emergency departments. Patient characteristics, cardiac arrest circumstances, emergency medical service (EMS) response and outcomes were recorded according to the Utstein style. Location of cardiac arrests was spot-mapped using GIS. RESULTS: From 1 October 2001 to 14 October 2004, 2428 patients were enrolled into the study. Mean age for arrests was 60.6 years with 68.0% male. 67.8% of arrests occurred in residences, with 54.5% bystander witnessed and another 10.5% EMS witnessed. Mean EMS response time was 9.6 min with 21.7% receiving prehospital defibrillation. Cardiac arrest occurrence was highest in the suburban town centers in the Eastern and Southern part of the country. We also identified communities with the highest arrest rates. About twice as many arrests occurred during the day (07:00-18:59 h) compared to night (19:00-06:59 h). The categories with the highest frequencies of occurrence included residential areas, in vehicles, healthcare facilities, along roads, shopping areas and offices/industrial areas. CONCLUSION: We found a definite geographical distribution pattern of cardiac arrest. This study demonstrates the utility of GIS with a national cardiac arrest database and has implications for implementing a PAD program, targeted CPR training, AED placement and ambulance deployment.

Use of an automated, load-distributing band chest compression device for out-of-hospital cardiac arrest resuscitation.

CONTEXT: Only 1% to 8% of adults with out-of-hospital cardiac arrest survive to hospital discharge. OBJECTIVE: To compare resuscitation outcomes before and after an urban emergency medical services (EMS) system switched from manual cardiopulmonary resuscitation (CPR) to load-distributing band (LDB) CPR. DESIGN, SETTING, AND PATIENTS: A phased, observational cohort evaluation with intention-to-treat analysis of 783 adults with out-of-hospital, nontraumatic cardiac arrest. A total of 499 patients were included in the manual CPR phase (January 1, 2001, to March 31, 2003) and 284 patients in the LDB-CPR phase (December 20, 2003, to March 31, 2005); of these patients, the LDB device was applied in 210 patients. INTERVENTION: Urban EMS system change from manual CPR to LDB-CPR. MAIN OUTCOME MEASURES: Return of spontaneous circulation (ROSC), with secondary outcome measures of survival to hospital admission and hospital discharge, and neurological outcome at discharge. RESULTS: Patients in the manual CPR and LDB-CPR phases were comparable except for a faster response time interval (mean difference, 26 seconds) and more EMS-witnessed arrests (18.7% vs 12.6%) with LDB. Rates for ROSC and survival were increased with LDB-CPR compared with manual CPR (for ROSC, 34.5%; 95% confidence interval [CI], 29.2%-40.3% vs 20.2%; 95% CI, 16.9%-24.0%; adjusted odds ratio [OR], 1.94; 95% CI, 1.38-2.72; for survival to hospital admission, 20.9%; 95% CI, 16.6%-26.1% vs 11.1%; 95% CI, 8.6%-14.2%; adjusted OR, 1.88; 95% CI, 1.23-2.86; and for survival to hospital discharge, 9.7%; 95% CI, 6.7%-13.8% vs 2.9%; 95% CI, 1.7%-4.8%; adjusted OR, 2.27; 95% CI, 1.11-4.77). In secondary analysis of the 210 patients in whom the LDB device was applied, 38 patients (18.1%) survived to hospital admission (95% CI, 13.4%-23.9%) and 12 patients (5.7%) survived to hospital discharge (95% CI, 3.0%-9.3%). Among patients in the manual CPR and LDB-CPR groups who survived to hospital discharge, there was no significant difference between groups in Cerebral Performance Category (P = .36) or Overall Performance Category (P = .40). The number needed to treat for the adjusted outcome survival to discharge was 15 (95% CI, 9-33). CONCLUSION: Compared with resuscitation using manual CPR, a resuscitation strategy using LDB-CPR on EMS ambulances is associated with improved survival to hospital discharge in adults with out-of-hospital nontraumatic cardiac arrest.

European Emergency Data Project (EED Project): EMS data-based health surveillance system.

Emergency Medical Services (EMS) constitute a unique component of health care at the interface between primary and hospital care. EMS data within the pre-hospital setting represents an unparalleled source of epidemiological and health care information that have so far been neglected for public health monitoring. The European Emergency Data Project (EED Project) thus intends to identify common indicators for European EMS systems and to evaluate their suitability for integration into a comprehensive public health monitoring strategy. The article provides a brief overview on objectives and methodology in the form of a progress report.

Current issues in cardiopulmonary resuscitation.

Current Advanced Cardiac Life Support (ACLS) guidelines and emergency medical services (EMS) clinical protocols usually recommend immediate defibrillation for victims of out-of-hospital cardiac arrest who have ventricular fibrillation (VF). However, animal studies and results from a small number of clinical investigations now suggest that a short period of chest compressions or ACLS procedures delivered before defibrillation may improve the outcome of patients with prolonged VF. Although the basic science and clinical data supporting a chest-compression-first procedure are compelling, large, multicenter randomized trials are still necessary to determine whether such protocols do indeed improve outcome. In current EMS dispatch practice, traditional cardiopulmonary resuscitation (CPR) instructions are given when needed to bystanders who report a possible cardiac arrest. Recent literature has shown that in certain circumstances, CPR instructions involving chest compressions alone may be given more quickly and can yield an equivalent, if not better, chance of survival. Although this practice is controversial, the general consensus is that any CPR is better than none at all. Therefore, telephone CPR protocols that recommend the immediate initiation of chest compressions may be preferred, particularly for callers who have no previous training in CPR.

Reimbursement in emergency medical services: how to adapt in a changing environment.

The proposed Medicare fee schedule for medically necessary ambulance transportation will have a profound impact on emergency medical services (EMS) systems throughout the country. When the new Medicare rules are implemented, reimbursement for Medicare patients will be largely based on national relative value units that vary depending on the level of service provided, from basic life support to advanced life support emergency. Under the new fee schedule, nearly all EMS systems will lose money when compared with the actual cost of providing the service, particularly advanced life support services, rural services, efficient systems, and those that bill for services. To adapt to these impending changes, EMS administrators and medical directors must work together to diversify and solidify their revenue sources and to seek out ways to make their systems even more efficient while maintaining a high quality of clinical care.

Performance measurements in emergency medical services.

With the strong encouragement of leading health care agencies, business principles are being implemented throughout health care, including emergency medical services (EMS). The reason is simple--quality of care can be enhanced by incorporating the management concepts of continuous quality improvement (CQI). The CQI process couples carefully identified, measurable performance indicators with information systems to monitor, analyze, and trend data. Benchmarking outcomes with other EMS systems allows the identification of "best practices" and the evolution of standards. Emergency medical services professionals must actively participate with the broader health care community in creating performance measurements to ensure that high-quality care is delivered consistently.

Synchronization of Timepieces to the Atomic Clock in an Urban Emergency Medical Services System.

STUDY OBJECTIVE: Erroneous time documentation of emergency treatment caused by the variation in the accuracy of timepieces has profound medical, medicolegal, and research consequences. The purpose of this study was to confirm the variation of critical timepiece settings in an urban emergency care system noted in previous studies and to implement and monitor the results of a prospective program to improve time synchronization. METHODS: Timepieces (n=393) used by firefighters, paramedics, and emergency physicians and nurses were randomly sampled immediately before and at two time intervals (1 and 4 months) after attempted synchronization to the US atomic clock standard. The setting on each timepiece was compared with the atomic clock. From the data, a mathematical simulation estimated the number of time-related documentation errors that would occur in 2,500 simulated cardiac arrest cases using timepieces with accuracy similar to those found in the EMS system before and after attempted synchronization. RESULTS: Before attempted synchronization, the timepieces had a mean error of 2.0 (95% confidence interval 1.8 to 2.3) minutes. One month after attempted synchronization, the mean error decreased significantly to .9 (.8 to 1.1) minute. However, it increased to 1.7 (1.5 to 1.9) minutes within 4 months. Mathematical simulation before attempted synchronization predicted that 93% of cardiac arrest cases would contain a documentation error of 2 minutes or more and that 41% of cases would contain a documentation error of 5 minutes or more. Attempted synchronization cut the 2-minute documentation error rate in half and reduced the 5-minute documentation error rate by three fourths. However, the error rates were predicted to return to baseline 4 months after attempted synchronization. CONCLUSION: Emergency medical timepieces are often inaccurate, making it difficult to reconstruct events for medical, medicolegal, or research purposes. Community synchronization of timepieces to the atomic clock can reduce the problem significantly, but the effects of a one-time attempted synchronization event are short-lived. [Ornato JP, Doctor ML, Harbour LF, Peberdy MA, Overton J, Racht EM, Zauhar WG, Smith AP, Ryan KA: Synchronization of time-pieces to the atomic clock in an urban emergency medical services system. Ann Emerg Med April 1998;31:483-487.].