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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.

Background

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.

Results

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.

Conclusions

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.

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.

Objective

Emergency department overcrowding sometimes results in diversion of ambulances to other locations. We sought to determine the resulting prehospital delays for cardiac patients.

Methods

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.

Results

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).

Interpretation

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.

Background

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.

Conclusion

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.

Background

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.

Method

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.

Results

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.

Conclusion

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.

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.

Background—Equity of access to appropriate pre-hospital emergency care is a core principle underlying an effective ambulance service. Care must be provided within a timeframe in which it is likely to be effective. A national census of response times to emergency and urgent calls in statutory ambulance services in Ireland was undertaken to assess current service provision.

Methods—A prospective census of response times to all emergency and urgent calls was carried out in the nine ambulance services in the country over a period of one week. The times for call receipt, activation, arrival at and departure from scene and arrival at hospital were analysed. Crew type, location of call and distance from ambulance base were detailed. The type of incident leading to the call was recorded but no further clinical information was gathered.

Results—2426 emergency calls were received by the services during the week. Fourteen per cent took five minutes or longer to activate (range 5–33%). Thirty eight per cent of emergencies received a response within nine minutes (range 10–47%). Only 4.5% of emergency calls originating greater than five miles from an ambulance station were responded to within nine minutes (range 0–10%). Median patient care times for "on call" crews were three times longer than "on duty" crews.

Conclusion—Without prioritised use of available resources, inappropriately delayed responses to critical incidents will continue. Recommendations are made to improve the effectiveness of emergency medical service utilisation.

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.

This retrospective study attempted to identify the pattern of ambulance calls for the past two years at the Hospital Universiti Sains Malaysia (HUSM) and Hospital Kota Bharu (HKB). This study will provide a simple method of acquiring information related to ambulance response time (ART) and to test whether it met the international standards and needs of the client. Additionally, this paper takes into account the management of emergency calls. This included ambulance response time, which was part of Emergency Medical Services (EMS) episode: onset of ART, which started when details like phone number of the caller, exact location of the incident and the nature of the main complaint had been noted. ART ended when the emergency team arrived at the scene of incident. Information regarding ambulance calls from the record offices of HUSM and HKB was recorded for the year 2001 and 2002, tabulated and analyzed. There was a significant difference in the total number of calls managed by HUSM and HKB in the year 2001. It was noted that 645 calls were managed by HUSM while 1069 calls were recorded at HKB. In the year 2002, however, HUSM led with 613 extra numbers of calls as compare to HKB with 1193 numbers of calls. The pattern of ambulance calls observed is thought to possibly be influenced by social activities like local festivities, school holidays and the seasons. Further, it is observed that no studies were previously undertaken to compare the ART at both the HUSM and HKB to that of the international standards. In fact, a literature review undertaken so far showed no similar studies have been done for the whole Malaysia.

Background

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.

Methods

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.

Results

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.

Conclusion

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.

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.

Methods: South Yorkshire Ambulance Service crews and control room staff were interviewed, using South Yorkshire's paramedic practitioner (PP) scheme as a model of an alternative response scheme.

Results: 55 ambulance crew and 17 control staff were interviewed. Most (97%, n = 70) thought that the PP scheme was a good way of dealing with patients who call 999 but may not need urgent transport and hospital treatment. The perceived effect of the PP scheme on traditional ambulance service duties was equally divided between a third who thought there had been no effect, a third who perceived an improvement, and a third a deterioration. Recurrent difficulties with the scheme were found relating to the AMPDS methodology of ambulance dispatch, and ambulance service performance targets.

Conclusions: Flexibility of AMPDS and dispatch targets will need to be reviewed to permit the successful implementation of alternative responses to 999 calls. Careful consideration needs to be given to communicating the aims and value of such schemes to all staff and ensuring a common understanding of, and commitment to, a shared vision. The effect of implementation on the remaining service function must be well planned.

In a Canada-wide survey, CANADIAN FAMILY PHYSICIAN found a startling divergence in provincial standards for ambulance crews and vehicles.

While some provinces had developed a well-integrated ambulance system with central dispatching, rigorous standards for attendants and advanced paramedical training programs, in some the ambulances are run almost entirely by local undertakers.

This article analyses how physicians choose locations of practice in response to spatial competition forces and considers the implications of such choices for public policy to alleviate shortages of practitioners in rural areas. The predicted geographic distribution of physicians, as determined through spatial competition modelling, was compared with the actual distribution of physicians in 1990 among Alberta's 19 census divisions. Physicians were found to respond to spatial competition forces in choosing where to practise, with the qualification that 1 urban patient had a demand weight equal to 2.32 rural patients. A policy to attract more physicians to rural areas by means of income subsidies is technically feasible but expensive. The high cost means that alternative policies such as a bigger and more effective ambulance network to transport patients to medical centres should become the focus of public policies to improve health care in rural areas.

Current efforts to reduce prehospital cardiac mortality focus more on deployment of specially equipped ambulances than on reduction of patient or ambulance delays. To evaluate this strategy, we needed to find a method that would isolate the separate effects of patient delay, ambulance delay, and the resuscitative capability of the ambulance. Using published data, we have generated a mathematical model of death from ventricular fibrillation following myocardial infarction that shows the relationship among these three factors. Analyses based on the model indicate that the potential life saving impact of a defibrillation-equipped ambulance is severely limited due to typical patient response patterns. If the ambulance arrives ten minutes after the onset of infarction, defibrillation capabilities will reduce prehospital mortality from 6 percent to 2 percent. After a more typical delay of 60 minutes, the mortality rises sharply to 13 percent for an unequipped ambulance. With a delay of this length, defibrillation capabilities reduce mortality only to about 12 percent.

Objectives

To quantify the health gains and costs associated with improving ambulance and thrombolysis response times for acute myocardial infarction.

Design

A computer simulation model.

Patients/setting

Patients experiencing acute myocardial infarction in England.

Interventions

Improving the ambulance response time to 75% of calls reached within 8 minutes and the hospital arrival to thrombolysis time interval (door‐to‐needle time) to 75% receiving it within 30 minutes and 20 minutes, compared to best estimates of response times in the mid‐1990s.

Main outcome measures

Deaths prevented, life years saved, and discounted cost per life year saved.

Results

Improving the ambulance response to 75% of calls within 8 minutes resulted in an estimate of 5 deaths prevented or 57 life years saved per million population per year, with a discounted incremental cost per life year saved of £8540 over 20 years. The corresponding benefit of improving the door‐to‐needle time to 75% of myocardial infarction patients within 30 minutes was an estimated 2 deaths prevented and 15 life years saved per million population per year, with a discounted incremental cost per life year saved of between £10 150 to £54 230 over 20 years. Little further gain was associated with reaching the 20 minute target. Combining ambulance and thrombolysis targets resulted in 70 life years saved per million population per year.

Conclusions

Improving ambulance response times appears to be cost effective. Reducing door‐to‐needle time will have a smaller effect at an uncertain cost. Further benefits may be gained from reducing the time from onset of symptoms to starting thrombolysis.

Event processing involves continuous evaluation of queries over streams of events. Response-time optimization is traditionally done over a fixed set of nodes and/or by using metrics measured at query-operator levels. Cloud computing makes it easy to acquire and release computing nodes as required. Leveraging this flexibility, we propose a novel, queueing-theory-based approach for meeting specified response-time targets against fluctuating event arrival rates by drawing only the necessary amount of computing resources from a cloud platform. In the proposed approach, the entire processing engine of a distinct query is modelled as an atomic unit for predicting response times. Several such units hosted on a single node are modelled as a multiple class M/G/1 system. These aspects eliminate intrusive, low-level performance measurements at run-time, and also offer portability and scalability. Using model-based predictions, cloud resources are efficiently used to meet response-time targets. The efficacy of the approach is demonstrated through cloud-based experiments.

Objectives. There are no published studies on the Barbados Emergency Ambulance Service and no assessment of the calls that end in nontransported individuals. We describe reasons for the nontransport of potential clients. Methods. We used the Emergency Medical Dispatch (Medical Priority Dispatch System) instrument, augmented with five local call types, to collect information on types of calls. The calls were categorised under 7 headings. Correlations between call types and response time were calculated. Results. Most calls were from the category medical (54%). Nineteen (19%) percent of calls were in the non-transported category. Calls from call type Cancelled accounted for most of these and this was related to response time, while Refused service was inversely related (P = 0.01). Conclusions. The Barbados Ambulance Service is mostly used by people with a known illness and for trauma cases. One-fifth of calls fall into a category where the ambulance is not used often due to cancellation which is related to response time. Other factors such as the use of alternative transport are also important. Further study to identify factors that contribute to the non-transported category of calls is necessary if improvements in service quality are to be made.

Objectives

Injury related to violent acts is a problem in every society. Although some authors have examined the geography of violent crime, few have focused on the spatio-temporal patterns of violent injury and none have used an ambulance dataset to explore the spatial characteristics of injury. The purpose of this study was to describe the combined spatial and temporal characteristics of violent injury in a large urban centre.

Methodology/Principal Findings

Using a geomatics framework and geographic information systems software, we studied 4,587 ambulance dispatches and 10,693 emergency room admissions for violent injury occurrences among adults (aged 18–64) in Toronto, Canada, during 2002 and 2004, using population-based datasets. We created kernel density and choropleth maps for 24-hour periods and four-hour daily time periods and compared location of ambulance dispatches and patient residences with local land use and socioeconomic characteristics. We used multivariate regressions to control for confounding factors. We found the locations of violent injury and the residence locations of those injured were both closely related to each other and clearly clustered in certain parts of the city characterised by high numbers of bars, social housing units, and homeless shelters, as well as lower household incomes. The night and early morning showed a distinctive peak in injuries and a shift in the location of injuries to a “nightlife” district. The locational pattern of patient residences remained unchanged during those times.

Conclusions/Significance

Our results demonstrate that there is a distinctive spatio-temporal pattern in violent injury reflected in the ambulance data. People injured in this urban centre more commonly live in areas of social deprivation. During the day, locations of injury and locations of residences are similar. However, later at night, the injury location of highest density shifts to a “nightlife” district, whereas the residence locations of those most at risk of injury do not change.

St Bartholomew's Hospital, in the City of London, has for many years run a Coronary Ambulance service, called by the public via the 999 system. During a 9-month period only 55% of 214 cardiac emergencies arriving at St Bartholomew's Hospital came with Coronary Ambulance support, although the service was available if called. In cases where the Coronary Ambulance was summoned, the call-out was inappropriate in 57% of cases. In addition, 153 cardiac emergencies arrived at the Accident and Emergency Department during hours when the Coronary Ambulance was not available. Reasons for breakdowns in the call-out system are discussed and remedies involving the public and London Ambulance Control are suggested.

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.

A model to predict demand for publicly dispatched emergency ambulance service in Los Angeles County is constructed using 1970 census tract and land usage data and 1973 population and utilization data. Although data were not available for many communities within the county, results indicate that the mode, which uses four socioeconomic variables, can accurately explain actual variations in ambulance demand for individual communities in Los Angeles County and for larger regions within the county.

A discrete-event computer simulation was developed using the C programming language to determine the optimal base location for a trauma system helicopter in Maine, a rural area with unevenly distributed population. Ambulance run reports from a one-year period provided input data on the times and places where major injuries occurred. Data from a statewide trauma registry were used to estimate the percentage of cases which would require trauma center care and the locations of functional trauma centers. Climatic data for this region were used to estimate the likelihood that a helicopter could not fly due to bad weather. The incidence of trauma events was modeled as a nonstationary Poisson process, and location of the events by an empirical distribution. For each simulated event, if the injuries were sufficiently severe, if weather permitted flying, if the occurrence were not within 20 miles of a center or outside the range of the helicopter, and if the helicopter were not already in service, then it was used for transportation. 35 simulated years were run for each of 4 proposed locations for the helicopter base. One of the geographically intermediate locations was shown to produce the most frequent utilization of the helicopter. Discrete-event simulation is a potentially useful tool in planning for emergency medical services systems. Further refinements and validation of predictions may lead to wider utilization.