Ambulance response time is a crucial factor in patient survival. The number of emergency cases (EMS cases) requiring an ambulance is increasing due to changes in population demographics. This is decreasing ambulance response times to the emergency scene. This paper predicts EMS cases for 5-year intervals from 2020, to 2050 by correlating current EMS cases with demographic factors at the level of the census area and predicted population changes. It then applies a modified grouping genetic algorithm to compare current and future optimal locations and numbers of ambulances. Sets of potential locations were evaluated in terms of the (current and predicted) EMS case distances to those locations.
Future EMS demands were predicted to increase by 2030 using the model (R2 = 0.71). The optimal locations of ambulances based on future EMS cases were compared with current locations and with optimal locations modelled on current EMS case data. Optimising the location of ambulance stations locations reduced the average response times by 57 seconds. Current and predicted future EMS demand at modelled locations were calculated and compared.
The reallocation of ambulances to optimal locations improved response times and could contribute to higher survival rates from life-threatening medical events. Modelling EMS case 'demand' over census areas allows the data to be correlated to population characteristics and optimal 'supply' locations to be identified. Comparing current and future optimal scenarios allows more nuanced planning decisions to be made. This is a generic methodology that could be used to provide evidence in support of public health planning and decision making.
Emergency department overcrowding sometimes results in diversion of ambulances to other locations. We sought to determine the resulting prehospital delays for cardiac patients.
Data on consecutive patients with chest pain who were transported to Toronto hospitals by ambulance were obtained for a 4-month period in 1997 and a 4-month period in 1999, which represented periods of low and high emergency department overcrowding respectively. Multivariate analyses were used to model 90th percentile system response (initiation of 9-1-1 call to arrival on scene), on-scene (arrival on scene to departure from scene) and transport (departure from scene to arrival at hospital) intervals. Predictor variables were study period (1997 or 1999), day of the week, time of day, geographic location of the patient, dispatch priority, case severity, return priority and number of other patients with chest pain transported within 2 hours of the index transport.
A total of 3609 patients (mean age 66.3 years, 50.3% female) who met the study criteria were transported by ambulance during the 2 study periods. There were no significant differences in patient characteristics between the 2 periods, despite the fact that more patients were transported during the second period (p < 0.001). The 90th percentile system response interval increased by 11.3% from the first to the second period (9.7 v. 10.8 min, p < 0.001), whereas the on-scene interval decreased by 8.2% (28.0 v. 25.7 min, p < 0.001). The longest delay was in the transport interval, which increased by 28.4% from 1997 to 1999 (13.4 v. 17.2 min, p < 0.001). In multivariate analyses, the study period (1997 v. 1999) remained a significant predictor of longer transport interval (p < 0.001) and total prehospital interval (p = 0.004).
An increase in overcrowding in emergency departments was associated with a substantial increase in the system response interval and the ambulance transport interval for patients with chest pain.
Road traffic injuries (RTIs) are a major public health problem, requiring concerted efforts both for their prevention and a reduction of their consequences. Timely arrival of the Emergency Medical Service (EMS) at the crash scene followed by speedy victim transportation by trained personnel may reduce the RTIs' consequences. The first 60 minutes after injury occurrence - referred to as the "golden hour"- are vital for the saving of lives. The present study was designed to estimate the average of various time intervals occurring during the pre-hospital care process and to examine the differences between these time intervals as regards RTIs on urban and interurban roads.
A retrospective cross-sectional study was designed and various time intervals in relation to pre-hospital care of RTIs identified in the ambulance dispatch centre in Urmia, Iran from 20 March 2005 to 20 March 2007. All cases which resulted in ambulance dispatches were reviewed and those that had complete data on time intervals were analyzed.
In total, the cases of 2027 RTI victims were analysed. Of these, 61.5 % of the subjects were injured in city areas. The mean response time for city locations was 5.0 minutes, compared with 10.6 minutes for interurban road locations. The mean on-scene time on the interurban roads was longer than on city roads (9.2 vs. 6.1 minutes, p < 0.001). Mean transport times from the scene to the hospital were also significantly longer for interurban incidents (17.1 vs. 6.3 minutes, p < 0.001). The mean of total pre-hospital time was 37.2 (+/-17.2) minutes with a median of 32.0. Overall, 72.5% of the response interval time was less than eight minutes.
The response, transport and total time intervals among EMS responding to RTI incidents were longer for interurban roads, compared to the city areas. More research should take place on needs-to and access-for EMS on city and interurban roads. The notification interval seems to be a hidden part of the post-crash events and indirectly affects the "golden hour" for victim management and it needs to be measured through the establishment of the surveillance systems.
Design: Pragmatic controlled trial. Calls identified using priority dispatch protocols as non-serious were allocated to intervention and control groups according to time of call. Ambulance dispatch occurred according to existing procedures. During intervention sessions, nurses or paramedics within the control room used a computerised decision support system to provide telephone assessment, triage and, if appropriate, offer advice to permit estimation of the potential impact on ambulance dispatch.
Setting: Ambulance services in London and the West Midlands.
Subjects: Patients for whom emergency calls were made to the ambulance services between April 1998 and May 1999 during four hour sessions sampled across all days of the week between 0700 and 2300.
Main outcome measures: Triage decision, ambulance cancellation, attendance at an emergency department.
Results: In total, there were 635 intervention calls and 611 controls. Of those in the intervention group, 330 (52.0%) were triaged as not requiring an emergency ambulance, and 119 (36.6%) of these did not attend an emergency department. This compares with 55 (18.1%) of those triaged by a nurse or paramedic as requiring an ambulance (odds ratio 2.62; 95% CI 1.78 to 3.85). Patients triaged as not requiring an emergency ambulance were less likely to be admitted to an inpatient bed (odds ratio 0.55; 95% CI 0.33 to 0.93), but even so 30 (9.2%) were admitted. Nurses were more likely than paramedics to triage calls into the groups classified as not requiring an ambulance. After controlling for age, case mix, time of day, day of week, season, and ambulance service, the results of a logistic regression analysis revealed that this difference was significant with an odds ratio for nurses:paramedics of 1.28 (95% CI 1.12 to 1.47).
Conclusions: The findings indicate that telephone assessment of Category C calls identifies patients who are less likely to require emergency department care and that this could have a significant impact on emergency ambulance dispatch rates. Nurses were more likely than paramedics to assess calls as requiring an alternative response to emergency ambulance despatch, but the extent to which this relates to aspects of training and professional perspective is unclear. However, consideration should be given to the acceptability, reliability, and cost consequences of this intervention before it can be recommended for full evaluation.
To derive and validate a model that accurately predicts ambulance arrival time that could be implemented as a Google Maps web application.
This was a retrospective study of all scene transports in Multnomah County, Oregon, from January 1 through December 31, 2008. Scene and destination hospital addresses were converted to coordinates. ArcGIS Network Analyst was used to estimate transport times based on street network speed limits. We then created a linear regression model to improve the accuracy of these street network estimates using weather, patient characteristics, use of lights and sirens, daylight, and rush-hour intervals. The model was derived from a 50% sample and validated on the remainder. Significance of the covariates was determined by p < 0.05 for a t-test of the model coefficients. Accuracy was quantified by the proportion of estimates that were within 5 minutes of the actual transport times recorded by computer-aided dispatch. We then built a Google Maps-based web application to demonstrate application in real-world EMS operations.
There were 48,308 included transports. Street network estimates of transport time were accurate within 5 minutes of actual transport time less than 16% of the time. Actual transport times were longer during daylight and rush-hour intervals and shorter with use of lights and sirens. Age under 18 years, gender, wet weather, and trauma system entry were not significant predictors of transport time. Our model predicted arrival time within 5 minutes 73% of the time. For lights and sirens transports, accuracy was within 5 minutes 77% of the time. Accuracy was identical in the validation dataset. Lights and sirens saved an average of 3.1 minutes for transports under 8.8 minutes, and 5.3 minutes for longer transports.
An estimate of transport time based only on a street network significantly underestimated transport times. A simple model incorporating few variables can predict ambulance time of arrival to the emergency department with good accuracy. This model could be linked to global positioning system data and an automated Google Maps web application to optimize emergency department resource use. Use of lights and sirens had a significant effect on transport times.
emergency medical services; prehospital emergency care
A methodology and analysis are presented for evaluating response time characteristics of emergency ambulance systems. The methodology is based on a Monte Carlo simulation technique and a heuristic optimal-seeking technique for locating emergency ambulances under several criteria based on response time distribution. Optimization criteria include minimum mean system response time, minimum system fractile response time and minimum level-loaded response time. The evaluation methodology is applied to the metropolitan area of Los Angeles County. Ambulance response characteristics and loads are discussed in detail. From these results alternative dispatch polices can be evaluated. Complementing the analysis is a presentation of a sensitivity analysis and an analysis of existing ambulance sites. Unique to the methodology is the adaption of the heuristic optimal-seeking technique to include any of the three criteria and the effectiveness of the methodology for analyzing small or large ambulance systems.
Unnecessary ambulance use has become a socioeconomic problem in Japan. We investigated the possible relations between socioeconomic factors and medically unnecessary ambulance calls, and we estimated the incremental demand for unnecessary ambulance use produced by socioeconomic factors.
We conducted a self-administered questionnaire-based survey targeting residents of Yokohama, Japan. The questionnaire included questions pertaining to socioeconomic characteristics, dichotomous choice method questions pertaining to ambulance calls in hypothetical nonemergency situations, and questions on the city's emergency medical system. The probit model was used to analyze the data.
A total of 2,029 out of 3,363 targeted recipients completed the questionnaire (response rate, 60.3%). Probit regression analyses showed that several demographic and socioeconomic factors influence the decision to call an ambulance. Male respondents were more apt than female respondents to state that they would call an ambulance in nonemergency situations (p < 0.05). Age was an important factor influencing the hypothetical decision to call an ambulance (p < 0.05); elderly persons were more apt than younger persons to state that they would call an ambulance. Possession of a car and hesitation to use an ambulance negatively influenced the hypothetical decision to call an ambulance (p < 0.05). Persons who do not have a car were more likely than those with a car to state that they would call an ambulance in unnecessary situations.
Results of the study suggest that several socioeconomic factors, i.e., age, gender, household income, and possession of a car, influence a person's decision to call an ambulance in nonemergency situations. Hesitation to use an ambulance and knowledge of the city's primary emergency medical center are likely to be important factors limiting ambulance overuse. It was estimated that unnecessary ambulance use is increased approximately 10% to 20% by socioeconomic factors.
Out-of-hospital cardiac arrest (OHCA) is a frequent and acute medical condition that requires immediate care. We estimate survival rates from OHCA in the area of Stockholm, through developing an analytical tool for evaluating Emergency Medical Services (EMS) system design changes. The study also is an attempt to validate the proposed model used to generate the outcome measures for the study.
Methods and results
This was done by combining a geographic information systems (GIS) simulation of driving times with register data on survival rates. The emergency resources comprised ambulance alone and ambulance plus fire services. The simulation model predicted a baseline survival rate of 3.9 per cent, and reducing the ambulance response time by one minute increased survival to 4.6 per cent. Adding the fire services as first responders (dual dispatch) increased survival to 6.2 per cent from the baseline level. The model predictions were validated using empirical data.
We have presented an analytical tool that easily can be generalized to other regions or countries. The model can be used to predict outcomes of cardiac arrest prior to investment in EMS design changes that affect the alarm process, e.g. (1) static changes such as trimming the emergency call handling time or (2) dynamic changes such as location of emergency resources or which resources should carry a defibrillator.
Out-of-hospital cardiac arrest; Defibrillation; Response time; Survival rate; Geographic information systems; Fire services
For two years doctors from a small village went to the scene of emergency calls received by ambulance control. On 80% of the occasions when the doctor was called at the same time as the ambulance was dispatched the doctor arrived before the ambulance. There were 24 incidents, 16 of which were road traffic accidents. In two cases the doctor established a clear airway in an unconscious patient before the ambulance arrived. Two patients were trapped in their vehicles and were given parenteral analgesics. Four patients required intravenous fluids. The call out system provided first aid for patients before the ambulance arrived and medical assistance to the emergency services at serious accidents. Patients who did not require hospital attention could be examined and treated at the scene, making the ambulance available for other duties and reducing the number of patients taken to the hospital accident and emergency department.
Prehospital management of gunshot-wounded (GW) patients influences injury-induced morbidity and mortality.
To evaluate prehospital management to GW patients emphasizing the protocol of patient transfer to appropriate centers.
Patients and Methods
This prospective study, included all GW patients referred to four major, level-I hospitals in Mashhad, Iran. We evaluated demographic data, triage, transport vehicles of patients, hospitalization time and the outcome.
There were 66 GW patients. The most affected body parts were extremities (60.6%, n = 40); 59% of cases (n = 39) were transferred to the hospitals with vehicles other than an ambulance. Furthermore, 77.3% of patients came to the hospitals directly from the site of event, and 22.7% of patients were referred from other medical centers. EMS action intervals from dispatchers to scene departure was not significantly different from established standards; however, arrival to hospital took longer than optimal standards. Additionally, time spent at emergency wards to stabilize vital signs was significantly less in patients who were transported by EMS ambulances (P = 0.01), but not with private ambulances (P = 0.47). However, ambulance pre-hospital care was not associated with a shorter hospital stay. Injury Severity was the only determinant of hospital stay duration (β = 0.36, P = 0.01) in multivariate analysis.
GW was more frequent in extremities and the most patients were directly transferred from the accident site. EMS (but not private) ambulance transport improved patients' emergency care and standard time intervals were achieved by EMS; however more than a half of the cases were transferred by vehicles other than an ambulance. Nevertheless, ambulance transportation (either by EMS or by private ambulance) was not associated with a shorter hospital stay. This showed that upgrade of ambulance equipment and training of private ambulance personnel may be needed.
Wounds, Gunshot; Triage; Emergency Medical Services; Wounds and Injuries; Iran
The most urgent recommendation expressed by physicians, Red Cross officials, ambulance operators and others polled in this ambulance survey was to make much more emergency medical care training available to ambulance personnel. Very few sick and injured receive first aid before an ambulance arrives. Therefore there is also an urgent need to train and motivate the public to provide first aid at the scene of the emergency. Urban ambulances usually respond within 10 minutes, but often rural ambulances take more than 30 minutes to reach an emergency. It is during this interim that lives which could be saved by prompt first aid are lost. Little use has been made of aircraft as emergency ambulances; in 1968, only one emergency trip in 1500 was made by helicopter. Also, California has fewer ambulances which make fewer emergency trips on a population basis than the country at large.
Communications at all levels need attention. Seventy-eight percent of the ambulance operations serving the public are not listed among the emergency numbers on the inside front page of telephone directories. Less than ten percent of ambulances have direct radio communication with hospitals.
In California most ambulance services are commercially operated and there are formidable financial problems which must be solved before these services can be brought into place as a part of the emergency medical care system.
► We investigated dispatching and relocation decisions of emergency service providers. ► ADP is powerful in solving the underlying stochastic and dynamic optimization problem. ► Average response time can be improved by using more flexible dispatching rules. ► Relocating ambulances proactively improves service quality. ► Essential to take into account time-dependent information.
Emergency service providers are supposed to locate ambulances such that in case of emergency patients can be reached in a time-efficient manner. Two fundamental decisions and choices need to be made real-time. First of all immediately after a request emerges an appropriate vehicle needs to be dispatched and send to the requests’ site. After having served a request the vehicle needs to be relocated to its next waiting location. We are going to propose a model and solve the underlying optimization problem using approximate dynamic programming (ADP), an emerging and powerful tool for solving stochastic and dynamic problems typically arising in the field of operations research. Empirical tests based on real data from the city of Vienna indicate that by deviating from the classical dispatching rules the average response time can be decreased from 4.60 to 4.01 minutes, which corresponds to an improvement of 12.89%. Furthermore we are going to show that it is essential to consider time-dependent information such as travel times and changes with respect to the request volume explicitly. Ignoring the current time and its consequences thereafter during the stage of modeling and optimization leads to suboptimal decisions.
OR in health services; Emergency vehicles; Ambulance location; Approximate dynamic programming; Stochastic optimization
Utilizing a computer algorithm, information from calls to an ambulance service was used to calculate the risk of patients being in a life-threatening condition (life threat risk), at the time of the call. If the estimated life threat risk was higher than 10%, the probability that a patient faced a risk of dying was recognized as very high and categorized as category A+. The present study aimed to review the accuracy of the algorithm.
Data collected for six months from the Yokohama new emergency system was used. In the system, emergency call workers interviewed ambulance callers to obtain information necessary to assess triage, which included consciousness level, breathing status, walking ability, position, and complexion. An emergency patient's life threat risk was then estimated by a computer algorithm applying logistic models. This study compared the estimated life threat risk occurring at the time of the emergency call to the patients' state or severity of condition, i.e. death confirmed at the scene by ambulance crews, resulted in death at emergency departments, life-threatening condition with occurrence of cardiac and/or pulmonary arrest (CPA), life-threatening condition without CPA, serious but not life-threatening condition, moderate condition, and mild condition. The sensitivity, specificity, predictive values, and likelihood ratios of the algorithm for categorizing A+ were calculated.
The number of emergency dispatches over the six months was 73,992. Triage assessment was conducted for 68,692 of these calls. The study targets account for 88.8% of patients who were involved in triage calls. There were 2,349 cases where the patient had died or had suffered CPA. The sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio and negative likelihood ratio of the algorithm at predicting cases that would result in a death or CPA were 80.2% (95% confidence interval: 78.6% - 81.8%), 96.0% (95.8% - 96.1%), 42.6% (41.1% - 44.0%), 99.2% (99.2% - 99.3%), 19.9 (18.8 - 21.1), and 0.21 (0.19 - 0.22), respectively.
A patient's life threat risk was quantitatively assessed at the moment of the emergency call with a moderate level of accuracy.
Effective treatment of stroke is time dependent. Pre-hospital management is an important link in reducing the time from occurrence of stroke symptoms to effective treatment. The aim of this study was to evaluate time used by emergency medical services (EMS) for stroke patients during a five-year period in order to identify potential delays and evaluate the reorganization of EMS in Copenhagen in 2009.
We performed a retrospective analysis of ambulance records from stroke patients suitable for thrombolysis from 1 January 2006 to 7 July 2011. We noted response time from dispatch of the ambulance to arrival at the scene, on-scene time and transport time to the hospital—in total, alarm-to-door time. In addition, we noted baseline characteristics.
We reviewed 481 records (58% male, median age 66 years). The median (IQR) alarm-to-door time in minutes was 41 (33–52), of which 18 (12–24) minutes were spent on scene. Response time was reduced from the period before to the period after reorganization (7 vs. 5 minutes, p <0.001). In a linear multiple regression model, higher patient age and longer distance to the hospital correlated with significantly longer transportation time (p <0.001).
This study shows an unchanged alarm-to-door time of 41 minutes over a five-year period. Response time, but not total alarm-to-door time, was reduced during the five years. On-scene time constituted nearly half of the total alarm-to-door time and is thus a point of focus for improvement.
Stroke; Acute cerebral infarction; Pre-hospital delay; Emergency medical services; Logistics; Thrombolysis; Emergency treatment of stroke
Still picture transmission was performed using a telemedicine system in an Emergency Medical Service (EMS) during a prospective, controlled trial. In this ancillary, retrospective study the quality and content of the transmitted pictures and the possible influences of this application on prehospital time requirements were investigated.
A digital camera was used with a telemedicine system enabling encrypted audio and data transmission between an ambulance and a remotely located physician. By default, images were compressed (jpeg, 640 x 480 pixels). On occasion, this compression was deactivated (3648 x 2736 pixels). Two independent investigators assessed all transmitted pictures according to predefined criteria. In cases of different ratings, a third investigator had final decision competence. Patient characteristics and time intervals were extracted from the EMS protocol sheets and dispatch centre reports.
Overall 314 pictures (mean 2.77 ± 2.42 pictures/mission) were transmitted during 113 missions (group 1). Pictures were not taken for 151 missions (group 2). Regarding picture quality, the content of 240 (76.4%) pictures was clearly identifiable; 45 (14.3%) pictures were considered “limited quality” and 29 (9.2%) pictures were deemed “not useful” due to not/hardly identifiable content. For pictures with file compression (n = 84 missions) and without (n = 17 missions), the content was clearly identifiable in 74% and 97% of the pictures, respectively (p = 0.003). Medical reports (n = 98, 32.8%), medication lists (n = 49, 16.4%) and 12-lead ECGs (n = 28, 9.4%) were most frequently photographed. The patient characteristics of group 1 vs. 2 were as follows: median age – 72.5 vs. 56.5 years, p = 0.001; frequency of acute coronary syndrome – 24/113 vs. 15/151, p = 0.014. The NACA scores and gender distribution were comparable. Median on-scene times were longer with picture transmission (26 vs. 22 min, p = 0.011), but ambulance arrival to hospital arrival intervals did not differ significantly (35 vs. 33 min, p = 0.054).
Picture transmission was used frequently and resulted in an acceptable picture quality, even with compressed files. In most cases, previously existing “paper data” was transmitted electronically. This application may offer an alternative to other modes of ECG transmission. Due to different patient characteristics no conclusions for a prolonged on-scene time can be drawn. Mobile picture transmission holds important opportunities for clinical handover procedures and teleconsultation.
Telemedicine; Teleconsultation; Digital image; Emergency medical service; Picture transmission; Photo transmission
Medical emergency motorcycles (MEM) can be used in time-critical conditions like cardiac arrest and multi-traumatized patients in an attempt to reduce the response time. Other potential benefits with MEM are more efficient patient evaluation, reduction of unnecessary EMS car ambulance missions and reduced cost. The potential benefits have been evaluated in this study. The incidence of accidents when operating the vehicle was also of interest.
A prospective study was performed when MEM was introduced as a trial in an urban ambulance service in Norway.
A total of 703 MEM missions were registered in the period. The mean emergency driving time was significantly shorter for the MEM than for the ambulance car located at the same station (6 min 24 seconds vs. 6 min 54 seconds). In addition to time-critical conditions, the MEM was used to evaluate patients when the need for emergency medical assistance was uncertain, and this practice lead to a reduced number of unnecessary car ambulance missions. No accidents involving the MEM were registered in the study period. The hourly cost of running the MEM was € 29 vs. € 75 for a car ambulance. However, the actual cost benefit is smaller since the weather conditions make it impossible to run a MEM in wintertime.
The small reduction in driving time when using a MEM instead of a car ambulance was statistically significant but probably of little clinical importance. The number of unnecessary car ambulance missions was reduced. It was cheaper to operate a MEM than a car ambulance, but the cost-effectiveness was reduced since the MEM could not operate 12 months a year. The lack of accidents may be contributed to the extensive training of the drivers and the fact that the vehicle was operated in daylight only.
OBJECTIVE--A register of patients with heart attacks in the Nottingham Health District has been maintained since 1973. Data from 1982 to 1984 inclusive, a period before trials of thrombolytic therapy started in Nottingham, were analysed to provide background information for the introduction of a policy of routine thrombolysis for appropriate patients. DESIGN--Data were collected prospectively on all patients transported to hospital in the Nottingham Health District with suspected myocardial infarction in the years 1982-84 and on patients treated at home during that time. SETTING--Two district general hospitals responsible for all emergency admissions in the health district. PATIENTS--6712 patients admitted to hospital with suspected myocardial infarction and 1887 patients found dead on arrival at hospital. Approximately 1500 patients in whom a myocardial infarction was suspected were treated at home, but only 125 were identified who had a definite or probable infarction. RESULTS--Among the patients admitted within 24 hours of the onset of symptoms, the median delay from onset to hospital admission was 174 minutes; 25% of patients were admitted within 91 minutes. The only factor that seemed to affect the time taken was the patient's decision to call a general practitioner or an emergency ambulance. If a general practitioner referred the patient to hospital the median delay was 247 minutes, compared with 100 minutes when the patient summoned an ambulance. Ninety three per cent of all patients were transported by ambulance. The median time from the call for the ambulance to hospital arrival was 29 minutes. Once a patient was admitted to hospital, the time to admission and general practitioner involvement seemed relatively unimportant as predictors of outcome. Patients admitted more than nine hours after onset of symptoms with a diagnosis of definite or probable infarction had a poorer outcome than those admitted earlier (in-hospital mortality 22.4% v 13.1%). The fatality rates of those admitted to a coronary care unit or to an ordinary medical ward are similar. CONCLUSION--Although the introduction of thrombolytic therapy has brought with it an increased awareness of the need to minimise any delay in time to admission, it seems that in a predominantly urban area like Nottingham, patients with a suspected heart attack will continue to be admitted to hospital most quickly if an ambulance crew rather than a general practitioner is called. Because the ambulance crew was in contact with such patients for only a short time it seems unlikely that administration of a thrombolytic drug in the ambulance would be helpful.
OBJECTIVES: To describe the patient characteristics, circumstances and community response in cases of out-of-hospital cardiac arrest; to evaluate the effect on survival of the introduction of prehospital defibrillation; and to identify factors that predict survival. DESIGN: Population-based before-and-after clinical trial. SETTING: Five Ontario communities: London, Sudbury, the Greater Niagara region, Kingston and Ottawa. PATIENTS: A consecutive sample of 1510 primary cardiac arrest patients who were transported to hospital by ambulance over 2 years. INTERVENTION: The use of defibrillators by ambulance attendants. MAIN OUTCOME MEASURES: Patient characteristics (sex and age), circumstances of arrest (place, whether arrest was witnessed and cardiac rhythm), citizen response (whether cardiopulmonary resuscitation [CPR] was started by a bystander, time to access to emergency medical services and time to initiation of CPR), emergency medical services response (ambulance response time, time to initiation of CPR and time to rhythm analysis with defibrillator) and survival rates. MAIN RESULTS: A total of 92.1% of the patients were 50 years of age or older, and 68.3% were men. Overall, 79.6% of the arrests occurred in the home. The average ambulance response time for witnessed cases was 7.8 minutes. The overall survival rate was 2.5%. The survival rates before and after defibrillators were introduced were similar, and the general functional outcome of the survivors did not differ significantly between the two phases. Factors predicting survival included patient's age, ambulance response time and whether CPR was started before the ambulance arrived. CONCLUSIONS: The survival rate was lower than expected. The availability of prehospital defibrillation did not affect survival. To improve survival rates after cardiac arrest ambulance response times must be reduced and the frequency of bystander-initiated CPR increased. Once these changes are in place a beneficial effect from advanced manoeuvres such as prehospital defibrillation may be seen.
OBJECTIVES--To evaluate the handling of potential cardiac emergency calls by dispatchers, to determine their final diagnosis and urgency, and to determine the value of the main complaint in predicting urgency and the ability of the dispatchers to recognise non-urgent conditions. DESIGN--Prospective data collection and recording of main complaint of emergency calls placed via the 06-11 alarm telephone number with follow up to hospital when the patients were transported and the general practitioner when they were not. SETTING--Dispatch centres of the emergency medical services in Amsterdam (urban area) and Enschede (rural area). PATIENTS--1386 consecutive adult subjects of emergency calls placed by citizens about chest problems or unconsciousness not caused by injury. MAIN OUTCOME MEASURES--Frequency of characteristics of the calls, outcome in diagnosis, and assessment of urgency. RESULTS--69 (5%) patients were dead when the ambulance arrived. Diagnosis was established in 1071 patients (77%). The disorders most often reported were cardiac, with acute ischaemia in 15% of all subjects. In 28% of cases and for each presenting complaint no organic explanation was found. Overall 39% of all emergency calls were urgent; the urgency rate was lowest for calls for people with abdominal discomfort. Dispatchers correctly identified 90% of the non-urgent calls, but 55% of the calls that they identified as urgent proved to be non-urgent. CONCLUSION--Currently, direct dialling for an ambulance without the intervention of a general practitioner imposes a high work load on emergency systems and hospitals because triage by dispatchers is not sufficiently accurate. It may be possible to increase the accuracy of triage by developing and testing decision algorithms.
Methods: The first 500 consecutive non-transported patients from 1 March 2000 were identified from the ambulance service command and control data. Epidemiological and clinical data were then obtained from the patient report form completed by the attending ambulance crew and compared with the initial priority dispatch (AMPDS) code that determined the urgency of the ambulance response.
Results: Data were obtained for 498 patients. Twenty six per cent of these calls were assigned an AMPDS delta code (the most urgent category) at the time the call was received. Falls accounted for 34% of all non-transported calls. This group of patients were predominantly elderly people (over 70 years old) and the majority (89%) were identified as less urgent (coded AMPDS alpha or bravo) at telephone triage. The mean time that an ambulance was committed to each non-transported call was 34 minutes.
Conclusions: This study shows that falls in elderly people account for a significant proportion of non-transported 999 calls and are often assigned a low priority when the call is first received. There could be major gains if some of these patients could be triaged to an alternative response, both in terms of increasing the ability of the ambulance service to respond faster to clinically more urgent calls and improving the cost effectiveness of the health service. The AMPDS priority dispatch system has been shown to be sensitive but this study suggests that its specificity may be poor, resulting in rapid responses to relatively minor problems. More research is required to determine whether AMPDS prioritisation can reliably and safely identify 999 calls where an alternative to an emergency ambulance would be a more appropriate response.
Functional decline has been identified as a leading negative outcome of hospitalization for older person. Functional decline is defined as a loss in ability to perform activities of daily living including a loss of independent ambulation. In the hospital literature, a patient’s loss in ability to independently ambulate during the hospital stay varies between 15 and 59%. Lack of ambulation and deconditioning effects of bed rest are one of the most predictable causes of loss of independent ambulation in hospitalized older persons. Nurses have been identified as the professional most capable of promoting walking independence in the hospital setting. However, nurses do not routinely walk patients.
The purpose of this study was to explore the relationship between nurses’ attributions of responsibility for ambulating hospitalized patients and their decisions about whether to ambulate.
A descriptive, secondary analysis of data gathered for a parent study was conducted. Grounded dimensional analysis was used to analyze the data. Participants consisted of 25 registered nurses employed on medical or surgical units from two urban hospitals in the United States.
Nurses fell into two groups: those who claimed ambulation of patients within their responsibility of practice and those who attributed the responsibility to another discipline. Nurses who claimed responsibility for ambulation focused on patient independence and psychosocial well-being. This resulted in actions related to collaborating with physical therapy, determining the appropriateness of activity orders, diminishing the risk and adjusting to resource availability. Nurses who attributed the responsibility deferred decisions about initiating ambulation to either physical therapy or medicine. This resulted in actions related to waiting, which involved, waiting for physical therapy clearance, physician orders, risks to decrease, and resources to improve before ambulating.
Nurses who claimed responsibility for ambulating patients within their domain of practice described actions that promoted patient independent function and were more likely to get patient s up to ambulate.
Hospital; Nursing care; Ambulating; Older patients; Grounded dimensional analysis
To measure the performance of selected Italian emergency medical system (EMS) dispatch centres managing calls for patients suffering from stroke. Data on outcome and on early treatment in the ED were collected.
Prospective data collection for a trimester from interventions for a suspected stroke in 13 EMS dispatch centres over five Italian regions.
Altogether, 1041 calls for a suspected stroke were analysed. Mean intervals of the sequential phases were 2.3±2 minutes between call and ambulance dispatch, 8.4±5.5 minutes to reach the patient, 14.5±8.5 minutes on the scene, and 40.2±16.2 minutes between call and arrival at the ED. Interventions were performed in 56% of cases by a basic life support (BLS) crew, advanced life support (ALS) crews intervened in 28% of cases, and a combination of ALS and BLS in the remaining 16%. Mean diagnostic interval was 99±85 minutes between emergency system call and the first CT scan. This was performed 71±27 minutes after ED admission. Only 1.6% were admitted to a stroke unit. One month outcome according to GCS was good recovery in 32%, moderate disability in 28%, severe disability in 14%, and death in 25% of the patients.
Mean times show a rapid response of the selected EMS dispatch centres to calls for a suspected stroke. Nevertheless, mean times of the ED phase are still unacceptable according to international guidelines such as Brain Attack Coalition and American Stroke Association guidelines. Efforts should be spent to reduce the time between the arrival and the CT scan and more patients should be admitted to a stroke unit.
emergency medicine; prehospital; stroke
To determine the association between ambulance response time and survival from out of hospital cardiopulmonary arrest and to estimate the effect of reducing response times.
Scottish Ambulance Service.
All out of hospital cardiopulmonary arrests due to cardiac disease attended by the Scottish Ambulance Service during May 1991 to March 1998.
Main outcome measures
Survival rate to hospital discharge and potential improvement from reducing response times.
Of 13 822 arrests not witnessed by ambulance crews but attended by them within 15 minutes, complete data were available for 10 554 (76%). Of these patients, 653 (6%) survived to hospital discharge. After other significant covariates were adjusted for, shorter response time was significantly associated with increased probability of receiving defibrillation and survival to discharge among those defibrillated. Reducing the 90th centile for response time to 8 minutes increased the predicted survival to 8%, and reducing it to 5 minutes increased survival to 10-11% (depending on the model used).
Reducing ambulance response times to 5 minutes could almost double the survival rate for cardiac arrests not witnessed by ambulance crews.
What is already known on this topicThree quarters of all deaths from myocardial infarction occur after cardiac arrest in the communitySurvival after out of hospital arrest is much lower in the United Kingdom than the United StatesWhat this study addsAmbulance response times are independently associated with defibrillation and survivalDecreasing the target for response to 90% of calls from 14 minutes to 8 minutes would increase survival from 6% to 8%A response time of 5 minutes would increase survival to 10-11%
OBJECTIVE: To determine the warning time given to accident and emergency (A&E) departments by the ambulance service before arrival of a critically ill or injured patient. To determine if this could be increased by ambulance personnel alerting within five minutes of arrival at scene. METHODS: Use of computerised ambulance control room data to find key times in process of attending a critically ill or injured patient. Modelling was undertaken with a scenario of the first responder alerting the A&E department five minutes after arrival on scene. RESULTS: The average alert warning time was 7 min (range 1-15 min). Mean time on scene was 22 min (range 4-59 min). In trauma patients alone, the average alert time was 7 min, range 2-15 min, with an average on scene time of 23 min, range 4-53 min. There was a potential earlier alert time averaging 25 min (SD 18.6, range 2-59 min) if the alert call was made five minutes after arrival on scene. CONCLUSIONS: A&E departments could be alerted much earlier by the ambulance service. This would allow staff to be assembled and preparations to be made. Disadvantages may be an increased "alert rate" and wastage of staff time while waiting the ambulance arrival.
Effective provision of urgent stroke care relies upon admission to hospital by emergency ambulance and may involve pre-hospital redirection. The proportion and characteristics of patients who do not arrive by emergency ambulance and their impact on service efficiency is unclear. To assist in the planning of regional stroke services we examined the volume, characteristics and prognosis of patients according to the mode of presentation to local services.
Study design and setting
A prospective regional database of consecutive acute stroke admissions was conducted in North East, England between 01/09/10-30/09/11. Case ascertainment and transport mode were checked against hospital coding and ambulance dispatch databases.
Twelve acute stroke units contributed data for a mean of 10.7 months. 2792/3131 (89%) patients received a diagnosis of stroke within 24 hours of admission: 2002 arrivals by emergency ambulance; 538 by private transport or non-emergency ambulance; 252 unknown mode. Emergency ambulance patients were older (76 vs 69 years), more likely to be from institutional care (10% vs 1%) and experiencing total anterior circulation symptoms (27% vs 6%). Thrombolysis treatment was commoner following emergency admission (11% vs 4%). However patients attending without emergency ambulance had lower inpatient mortality (2% vs 18%), a lower rate of institutionalisation (1% vs 6%) and less need for daily carers (7% vs 16%). 149/155 (96%) of highly dependent patients were admitted by emergency ambulance, but none received thrombolysis.
Presentations of new stroke without emergency ambulance involvement were not unusual but were associated with a better outcome due to younger age, milder neurological impairment and lower levels of pre-stroke dependency. Most patients with a high level of pre-stroke dependency arrived by emergency ambulance but did not receive thrombolysis. It is important to be aware of easily identifiable demographic groups that differ in their potential to gain from different service configurations.