Emergency Medical Service Vehicle Research Articles

Spread of infectious microbes during emergency medical response

BackgroundTo our knowledge, no studies to date demonstrate potential spread of microbes during actual emergency medical service (EMS) activities. Our study introduces a novel approach to identification of contributors to EMS environment contamination and development of infection control strategies, using a bacteriophage surrogate for pathogenic organisms.MethodsBacteriophage ΦX174 was used to trace cross-contamination and evaluate current disinfection practices and a hydrogen peroxide (H2O2) wipe intervention within emergency response vehicles. Prior to EMS calls, 2 surfaces were seeded with ΦX174. On call completion, EMS vehicle and equipment surfaces were sampled before decontamination, after decontamination per current practices, and after implementation of the intervention.ResultsCurrent decontamination practices did not significantly reduce viral loads on surfaces (P = .3113), but H2O2 wipe intervention did (P = .0065). Bacteriophage spread to 56% (27/48) of sites and was reduced to 54% (26/48) and 40% (19/48) with current decontamination practices and intervention practices, respectively.ConclusionResults suggest firefighters' hands were the main vehicles of microbial transfer. Current practices were not consistently applied or standardized and minimally reduced prevalence and quantity of microbial contamination on EMS surfaces. Although use of a consistent protocol of H2O2 wipes significantly reduced percent prevalence and concentration of viruses, training and promotion of surface disinfection should be provided.

Time-dependent MEXCLP with start-up and relocation cost

Abstract In this paper we introduce a time-dependent probabilistic location model for Emergency Medical Service (EMS) vehicles. The goal is to maximize the expected coverage throughout the day and at the same time minimize the number of opened facilities and the number of relocations. We apply our model to both a randomly generated test instance and to data from the city of Amsterdam, the Netherlands. We see that time-dependent models can result in better solutions than time-independent models. Furthermore, we see that the current set of base locations in Amsterdam is not optimal. We can obtain higher coverage with even less base locations.

Heuristic Approach for Optimizing Emergency Medical Services in Road Safety within Large Urban Networks

Emergency medical service (EMS) providers participating in vehicle crash-induced incident management aim to offer as wide and efficient coverage as possible to meet the demand for incident responses effectively; however, the design and provision of efficient and cost-effective services are tough issues faced by emergency management authorities. This paper introduces a double standard model (DSM), along with a genetic algorithm (GA) for assigning EMS fleet from vehicle locations to intersection vehicle crash sites such that crash demand sites can be covered in accordance with two service coverage standards. Specifically, all demand sites are required to receive single coverage according to the secondary coverage standard and at least a portion (α) of demand sites need to maintain single coverage as per the primary coverage standard. The proposed model is applied for top 200 intersections in the City of Chicago selected using intersection crash records for 2004–2010 according to crash frequency-based and severity-based scenarios. The top 200 intersections are split into high and low severity sites for model application. Using the EMS vehicle fleet size currently maintained by the Chicago Fire Department as 15 basic life support (BLS) and 60 advanced life support (ALS) ambulances, almost 100% of double vehicle coverage can be achieved. Extended model application is conducted by keeping 15 BLS ambulances unchanged and reducing the 60 ALS ambulances by 50% to 30. Results show that nearly 90% of double coverage according to the primary standard can still be reached.

Time-dependent ambulance allocation considering data-driven empirically required coverage

Empirical studies considering the location and relocation of emergency medical service (EMS) vehicles in an urban region provide important insight into dynamic changes during the day. Within a 24-hour cycle, the demand, travel time, speed of ambulances and areas of coverage change. Nevertheless, most existing approaches in literature ignore these variations and require a (temporally and spatially) fixed (double) coverage of the planning area. Neglecting these variations and fixation of the coverage could lead to an inaccurate estimation of the time-dependent fleet size and individual positioning of ambulances. Through extensive data collection, now it is possible to precisely determine the required coverage of demand areas. Based on data-driven optimization, a new approach is presented, maximizing the flexible, empirically determined required coverage, which has been adjusted for variations due to day-time and site. This coverage prevents the EMS system from unavailability of ambulances due to parallel operations to ensure an improved coverage of the planning area closer to realistic demand. An integer linear programming model is formulated in order to locate and relocate ambulances. The use of such a programming model is supported by a comprehensive case study, which strongly suggests that through such a model, these objectives can be achieved and lead to greater cost-effectiveness and quality of emergency care.

Abstract T P246: Mode of Arrival for Acute Stroke Patients Directly Impacts Emergency Care Delivery

Background: Tissue plasminogen activator (tPA) administration is very time sensitive with an odds ratio of a good outcome that is inversely proportional to time from onset to tPA administration. Extensive systems have been put in place to ensure rapid delivery of tPA in emergency medical systems, but little data exists evaluating the success of these systems for patients who arrive via Emergency Medical Services (EMS) vs. private vehicle. This study evaluates this issue using data from a single institution. Purpose: The purpose of this study is to gather data on process differences between acute stroke patients arriving via EMS vs. private vehicle and show how the data is utilized to identify areas for improvement in patient care delivery. Methods: Data was collected on 138 consecutive acute stroke patients, encompassing patient mode of arrival, as well as time to stroke alert activation, order entry, CT completion, lab results, and where applicable, telemedicine activation and tPA administration. This data was analyzed to evaluate for differences in performance of the stroke alert process based on mode of arrival. Results: Overall, the stroke alert process performed better for EMS patients than for patients arriving via private vehicle. Conclusions: Statistically significant differences were found between EMS and private vehicle arrival, with far better process performance seen for EMS patients. The delays in care occur initially in the activation of the stroke alert, then are continued throughout the process of care after the stroke alert has been called. In conclusion, recognition that processes do not perform equally in all situations is important in system design, and rigorous performance monitoring is paramount to ensure optimal care of all patients through performance improvement activities.

Time-Dependent Ambulance Allocation Considering Data Driven Empirically Required Coverage

Empirical studies considering the location and relocation of emergency medical services (EMS) vehicles in an urban region provide important insight into dynamic changes during the day. Within a time period of one day the demand, travel time/speed of ambulances and covered areas change cyclically. Nevertheless, most existing approaches in literature ignore these variations and require a (temporally and spatially) fixed (double) coverage of the planning area. Neglecting these variations and fixation of the coverage could lead to a false estimation of the time dependent fleet size and individual positioning of ambulances. Through extensive data collection, nowadays it is possible to precisely determine the required coverage of demand areas. Based on data driven optimization a new approach is presented, maximizing the flexible, empirically determined required coverage, which has been adjusted for variations due to day-time and site. This coverage prevents the EMS system from unavailability of ambulances due to parallel operations to ensure an improved coverage of the planning area closer to realistic demand. An integer linear programming model is formulated in order to locate and relocate ambulances. Based on a comprehensive case study it is shown, that the approach achieves these objectives and leads to cost savings and improvement in the quality of emergency care.

Emergency medical service allocation in response to large-scale events

In the event of a catastrophic or large-scale event, demand for Emergency Medical Service (EMS) vehicles will almost certainly overwhelm the available supply. In such cases, it is necessary for cities to request aid (in the form of added capacity) from neighboring municipalities in order to bring the affected region back to its day-to-day levels of operation. In particular, we consider a region consisting of several cities, where each city is in charge of managing its own EMS vehicles. We propose that a centralized or statewide decision-maker coordinate the temporary transfer of resources (EMS vehicles) from cities in the unaffected region into the cities in the affected region. The control of each city’s EMS vehicles is modeled as a multi-server queueing system and classical results are used to estimate the number of vehicles available at each city. We then develop a deterministic resource allocation model to guide the allocation of available vehicles from the donor area into the affected one and a clearing system model to dynamically control the added resources.As the dimension of the problem is large, a heuristic we call the buddy system is proposed where cities are paired to form city groups. Within the city groups the clearing system model is solved by Markov decision processes. The performance of our heuristic is compared to several other reasonable heuristics via a detailed numerical study. Results show that the buddy system exhibits significant cost and time savings, and is generally robust to varying parameters.

Location Analysis for Emergency Medical Service Vehicle in Sub District Area

This research aims to formulate a mathematical model and develop an algorithm for solving a location problem in emergency medical service vehicle parking. To find an optimal parking location which has the least risk score or risk priority number calculated from severity, occurrence, detection, and distance from parking location for emergency patients, data were collected from Pratoom sub-district Disaster Prevention and Mitigation Center from October 2010 to April 2011. The criteria of risk evaluation were modified from Automotive Industry Action Group’s criteria. An adaptive simulated annealing algorithm with multiple cooling schedules called multi-agent simulated quenching (MASQ) is proposed for solving the problem in two schemes of algorithms including dual agent and triple agent quenching. The result showed that the solution obtained from both scheme of MASQ was better than the traditional solution. The best locations obtained from MASQ-dual agent quenching scheme was nodes #5 and #133. The risk score was reduced 61% from 6,022 to 2,371 points.

Predictors of Ambulance Transport in Patients with ST-Elevation Myocardial Infarction

Despite intense public awareness campaigns, many patients with ST-elevation myocardial infarction (STEMI) do not utilize Emergency Medical Services (EMS) transportation to the Emergency Department (ED). Predictors for mode of transport by EMS versus private vehicle in patients with an acute STEMI were investigated. Hypothesis It was hypothesized that patient characteristics, specifically older age, male sex, and a history of a prior cardiac intervention, would be associated with a higher likelihood of EMS utilization. A retrospective, observational cohort study was performed for all STEMI patients treated from April 1, 2007 through June 30, 2010 at an urban, academic ED with 24-hour cardiac catheterization available. Multivariable analyses with predetermined predictors (age, sex, prior cardiac intervention, weekend/evening arrival) were performed to investigate associations with mode of transport. Door-to-balloon (D2B) times were calculated. Of the 209 STEMI patients, 11 were excluded, leaving 198 for analysis. Median age was 60 years (IQR: 53-70), 138 (70%) arrived by private vehicle, and 60 (30%) by EMS. The primary analysis did not identify significant predictors for EMS, but a post-hoc model found that private insurance (OR 0.18; 95% CI, 0.07-0.45) was associated with fewer EMS transports. Although not statistically significant due to the great variability in time of arrival for STEMI patients transported by private vehicle, EMS transports had shorter D2B times. During business hours and weekend/evenings, EMS had D2B times of 50 (IQR: 42-61) and 58 minutes (IQR: 47-63), respectively, while private vehicle transports had median D2B times of 62 (IQR: 50-74) and 78 minutes (IQR: 66-106). Conclusion No associations between mode of transport and patient age, sex, weekend/evening presentation and history of a prior cardiac intervention were identified. Privately insured patients were less likely to use EMS when experiencing a STEMI. More effective ways are needed to educate the public on the importance of EMS activation when one is concerned for acute coronary syndrome.

Structured Inspection of Medications Carried and Stored by Emergency Medical Services Agencies Identifies Practices That May Lead to Medication Errors

Background. Medications are essential to emergency medical services (EMS) agencies when providing lifesaving care, but the EMS environment has challenges related to safe medication storage when compared with a hospital setting. We developed a structured process, based on common pharmacy practices, to review medications carried by EMS agencies to identify situations that may lead to medication error and to determine some best practices that may reduce potential errors and the risk of patient harm. Objective. To provide a descriptive account of EMS practices related to carrying and storing medications that have the potential for causing a medication administration error or patient harm. Methods. Using a structured process for inspection, an emergency medicine pharmacist and emergency physician(s) reviewed the medication carrying and storage practices of all nine advanced life support ambulance agencies within a five-county EMS region. Each medication carried and stored by the EMS agency was inspected for predetermined and spontaneously observed issues that could lead to medication error. These issues were documented and photographed. Two EMS medical directors reviewed each potential error for the risk of producing patient harm and assigned each to a category of high, moderate, or low risk. Because issues of temperature on EMS medications have been addressed elsewhere, this study concentrated on potential for EMS medication administration errors exclusive of storage temperatures. Results. When reviewing medications carried by the nine EMS agencies, 38 medication safety issues were identified (range 1 to 8 per EMS agency). Of these, 16 were considered to be high risk, 14 moderate risk, and eight low risk for patient harm. Examples of potential issues included carrying expired medications, container-labeling issues, different medications stored in look-alike vials or prefilled syringes in the same compartment, and carrying crystalloid solutions next to solutions premixed with a medication. When reviewing medications stored at the EMS agency stations, eight safety issues were identified (range from 0 to 4 per station), including five moderate-risk and three low-risk issues. No agency had any high-risk medication issues related to storage of medication stock in the station. Conclusion. We observed potential medication safety issues related to how medications are carried and stored at all nine EMS agencies in a five-county region. Understanding these issues may assist EMS agencies in reducing the potential for a medication error and risk of patient harm. More research is needed to determine whether following these suggested best practices for carrying medications on EMS vehicles actually reduces errors in medication administration by EMS providers or decreases patient harm.

Emergency Medical Service Location Problem

This paper suggests emergency medical service vehicle (ambulance) algorithm when the emergency patient occurs in order to be sufficient the maximum permission time T of arrival about all sectors in one city that is divided in the various areas. This problem cannot be solved in polynomial times. One can obtains the solution using the integer programming. In this paper we suggest vertex set (or dominating set) algorithm and easily decide the location of ambulances. The core of the algorithm decides the location of ambulance is to the maximum degree vertex among the neighborhood of minimum degree vertex. For the 33 sectors Ostin city in Texas, we apply minutes. The traditional set cover algorithm with integer programming cannot obtains the solution in several T in 18 cases. But, this algorithm obtains solution for all of the 18 cases.

Quality of cardiopulmonary resuscitation in out-of-hospital cardiac arrest is hampered by interruptions in chest compressions—A nationwide prospective feasibility study

Aim of the studyQuality of cardiopulmonary resuscitation (CPR) is a critical determinant of outcome following out-of-hospital cardiac arrest. The aim of our study was to evaluate the quality of CPR provided by emergency medical service providers (Basic Life Support (BLS) capability) and emergency medical service providers assisted by paramedics, nurse anesthetists or physician-manned ambulances (Advanced Life Support (ALS) capability) in a nationwide, unselected cohort of out-of-hospital cardiac arrest cases. MethodsWe conducted a prospective, observational study of out-of-hospital cardiac arrest with non-traumatic etiology (>18 years of age) occurring from the 1st to the 31st of January 2009 and treated by the primary Danish emergency medical service operator, covering approximately 85% of the population. One hundred and ninety-one cases were eligible for analysis. Follow-up was up to one year or death. Quality of CPR was evaluated using measurements of transthoracic impedance. ResultsThe majority of patients were treated by ambulances with ALS capability (54%). Interruptions in CPR related to loading of the patient into the emergency medical service vehicle were substantial, but independent of whether patients were managed by ALS or BLS capable units (222s versus 224s, P=0.76) as were duration of interruptions during rhythm analysis alone (20s versus 22s, P=0.33) and defibrillation (24s versus 26s, P=0.07). ConclusionsNationwide, routine monitoring of transthoracic impedance is feasible. CPR is hampered by extended interruptions, particularly during loading of the patient into the emergency medical service vehicle, rhythm analysis and defibrillation.

Evaluation of Relocation Strategies for Emergency Medical Service Vehicles

Managers of emergency medical service (EMS) vehicles position their fleets to provide quick response to potential emergencies. Deployment strategies for positioning a fleet, typically static, do not account for variation of demand patterns over time and changes in travel times over the course of a day across the network. Network states can vary significantly and warrant redeployment to serve the entire community better. A relocation strategy that temporarily realigns the EMS fleet in response to these changes can improve system performance. This paper quantifies the benefits of considering relocating EMS vehicles between calls. Because there are costs associated with repositioning the vehicles, trade-offs between improved coverage and cost must be considered. Relocation strategies that consider system uncertainty are compared with static deployment strategies. A real-world analysis is conducted using emergency call data from Montreal, Canada. Practical methodology is proposed to address a real-world optimization problem, including ways to resolve multiple conflicting objectives, analyze systemwide performance probabilistically, and solve large-scale integer programs.

Mass casualty incident management, triage, injury distribution of casualties and rate of arrival of casualties at the hospitals: lessons from a suicide bomber attack in downtown Tel Aviv

Background:Terrorist attacks in Israel cause mass events with varying numbers of casualties. A study was undertaken to analyse the medical response to an event which occurred on 17 April 2006...

Bacterial Pathogens in Ambulances: Results of Unannounced Sample Collection

The concern that the health care environment may harbor a substantial reservoir of infectious agents has been vigorously examined by microbiology andinfectious disease experts. Although universal precautions anddisposable equipment reduces risks to patients andproviders, the ambulance remains vulnerable to bacterial contamination from biological secretions. Additionally, the nature of emergency medical services creates pressures on prehospital care providers. Objective. We hypothesized that a discrepancy exists between the expectation of disinfection of reusable equipment in emergency medical services (EMS) andthe cleaning that actually occurs. Methods. We chose five areas within the ambulance for specimen collection for their reasoned propensity to yield a large spectrum of bacteria. Four first-due ambulances were selected for culturing. The crews did not have advance knowledge of the study or sample collection. Specific identifications with antibiotic susceptibility were completed, identifying three multidrug resistant organisms. Results. Specimens from all four ambulances grew moderate-to-large quantities of environmental andskin flora. Newer, automated microbiological techniques andconcerns regarding multiple-drug-resistant organism prevalence as well as the potential for biological warfare make complete identification more important. Conclusions. This study examined the bacterial pathogens found in EMS vehicles. Four of the seven species isolated were substantial nosocomial pathogens, andthree of these four possess formidable antibiotic resistance patterns. All of the organisms detected are susceptible to the disinfectant agents currently in common use by EMS agencies.

Ambulance location for maximum survival

AbstractThis article proposes new location models for emergency medical service stations. The models are generated by incorporating a survival function into existing covering models. A survival function is a monotonically decreasing function of the response time of an emergency medical service (EMS) vehicle to a patient that returns the probability of survival for the patient. The survival function allows for the calculation of tangible outcome measures—the expected number of survivors in case of cardiac arrests. The survival‐maximizing location models are better suited for EMS location than the covering models which do not adequately differentiate between consequences of different response times. We demonstrate empirically the superiority of the survival‐maximizing models using data from the Edmonton EMS system. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2008

The role of emergency medical services in stroke: a hospital-based study in Kaohsiung, Taiwan.

Emergency medical services (EMS) play an important role in acute stroke therapy. The goal of this study was to investigate the roles and determinants of EMS in stroke in Southern Taiwan, Kaohsiung. We enrolled stroke patients who arrived at emergent department (ED) of the study hospital within 48 hours after the onset of symptoms. Patients were categorized into arriving by EMS or not EMS. Potential determinants of EMS use for stroke were examined by multivariable analyses and the role of EMS in stroke was discussed. Among 197 stroke patients enrolled, only 44 (22%) patients arrived by EMS at ED. Multivariable logistic regression analysis revealed that the determinants of EMS use were stroke severity measured by NIHSS and non-family member who decided to seek help. Using EMS or not was not associated with the earlier presentation after stroke within 2 hours after attack. EMS use was far from sufficient. The transportation time was not the major component of prehospital delay. Both EMS and other vehicles provided prompt delivery. The public should rush to ED either by EMS or other transportation modes when stroke occurred unless use of EMS is proved to provide better outcome in stroke patient in the future study.

Simulation Model for Real-Time Emergency Vehicle Dispatching and Routing

A simulation model for evaluation of a real-time emergency medical service vehicle response system that uses real-time travel time information and that assists the emergency vehicle dispatchers in assigning response vehicles and guiding those vehicles through noncongested routes is developed. Different response strategies are evaluated with this simulation model. These include the first-called, first-served strategy, the nearest-origin assignment strategy, and the flexible assignment strategy that uses real-time travel time information to assign and dispatch response vehicles. Different assumptions and conditions are used to test the sensitivity of the flexible assignment strategy.

Integrated Approach for Emergency Medical Service Location and Assignment Problem

In an emergency medical service (EMS) system, the depot location and fleet assignment greatly affect the average response time, which is the main criterion for measuring system performance. Whereas the EMS depot location problem is a strategic problem, the fleet assignment problem is a tactical one. As such, the EMS depot location and fleet assignment problems are usually solved separately under some simplified assumptions. However, there is a potential for savings in both the average response times and the capital and operating costs if these problems can be solved simultaneously. A simulation model for EMS vehicle dispatching was developed. This model is calibrated with real-world data, and it is incorporated in a genetic algorithm to help solve the EMS depot location and fleet assignment problems simultaneously. Emergency types, their response priorities, and whether or not they require dispatching of multiple units are taken into consideration in the model. The average response time and the capital and operating costs are used as criteria for evaluation.

Implementing a mathematical model for locating EMS vehicles in fayetteville, NC

Emergency medical services (EMS) aims to reduce the elapsed time to respond to an emergency. The number and location of vehicles within the service area, directly affect the attainment of this goal. In this paper, we focus on a mathematical modeling approach for locating/allocating emergency vehicles and facilities in a manner that increases the number of calls that are answered within the 8-min national average. This model was applied to the EMS system in the city of Fayetteville, North Carolina, and results indicate that the average response time can be significantly improved through strategically allocating vehicles throughout the service area.