Impact of ambulance diversion policies in urban, suburban, and rural areas of Central Maryland

Association of Ambulance Diversion Policy on EMS Transport and Ambulance Patient Offload Times: A Comparison of Three Strategies

OBJECTIVES

Despite limited supporting data, hospitals continue to apply ambulance diversion (AD). Thus, we examined the impact of three different diversion policies on diversion hours, transport time (TT; leaving scene to arrival at the hospital), and ambulance patient offload time (APOT; arrival at the hospital to patient turnover to hospital staff) for 9-1-1 transports in a 22-hospital county Emergency Medical Services (EMS) system.

METHODS

This retrospective study evaluated metrics during periods of three AD policies, each 27 days long: hospital-initiated (Period 1), complete suspension (Period 2), and County EMS-initiated (Period 3). We described the median transports and diversion hours, and compared the daily average and daily 90th percentile TT and APOT during the three study periods.

RESULTS

Over the study period, there were 50,992 total transports in the county; Period 3 had fewer median transports per day than Period 1 (581 vs 623, p < 0.001), while Period 2 was similar to Period 1 (606 vs 623, p = 0.108). Median average daily diversion hours decreased from 98.1 h during Period 1 to zero hours during both Periods 2 (p < 0.001) and 3 (p < 0.001). Median daily average TT decreased from 18.3 min in Period 1 to 16.9 min in both Periods 2 (p < 0.001) and 3 (p < 0.001). Median daily 90th percentile TT showed a similar decrease from 30.2 min in Period 1 to 27.5 in Period 2 (p < 0.001), and to 28.1 in Period 3 (p = 0.001). Median average daily APOT was 26.0 min during Period 1, similar at 25.2 min during Period 2 (p = 0.826) and decreased to 20.4 min during Period 3 (p < 0.001). The median daily 90th percentile APOT was 53.9 min during Period 1, similar at 51.7 min during Period 2 (p = 0.553) and decreased to 40.3 min during Period 3 (p < 0.001).

CONCLUSIONS

Compared to hospital-initiated AD, enacting no AD or County EMS-initiated AD was associated with less diversion time; TT and APOT showed statistically significant improvement without hospital-initiated AD but were of unclear clinical significance. EMS-initiated AD was difficult to interpret as that period had significantly fewer transports. EMS systems should consider these findings when developing strategies to improve TT, APOT, and system use of diversion.

Centralized Ambulance Diversion Policy Using Rolling-Horizon Optimization Framework to Minimize Patient Tardiness

Ambulance diversion (AD) is a common method for reducing crowdedness of emergency departments by diverting ambulance-transported patients to a neighboring hospital. In a multi-hospital system, the AD of one hospital increases the neighboring hospital's congestion. This should be carefully considered for minimizing patients' tardiness in the entire multi-hospital system. Therefore, this paper proposes a centralized AD policy based on a rolling-horizon optimization framework. It is an iterative methodology for coping with uncertainty, which first solves the centralized optimization model formulated as a mixed-integer linear programming model at each discretized time, and then moves forward for the time interval reflecting the realized uncertainty. Furthermore, the decentralized optimization, decentralized priority, and No-AD models are presented for practical application, which can also show the impact of using the following three factors: centralization, mathematical model, and AD strategy. The numerical experiments conducted based on the historical data of Seoul, South Korea, for 2017, show that the centralized AD policy outperforms the other three policies by 30%, 37%, and 44%, respectively, and that all three factors contribute to reducing patients' tardiness. The proposed policy yields an efficient centralized AD management strategy, which can improve the local healthcare system with active coordination between hospitals.

A review on ambulance offload delay literature

Ambulance offload delay (AOD) occurs when care of incoming ambulance patients cannot be transferred immediately from paramedics to staff in a hospital emergency department (ED). This is typically due to emergency department congestion. This problem has become a significant concern for many health care providers and has attracted the attention of many researchers and practitioners. This article reviews literature which addresses the ambulance offload delay problem. The review is organized by the following topics: improved understanding and assessment of the problem, analysis of the root causes and impacts of the problem, and development and evaluation of interventions. The review found that many researchers have investigated areas of emergency department crowding and ambulance diversion; however, research focused solely on the ambulance offload delay problem is limited. Of the 137 articles reviewed, 28 articles were identified which studied the causes of ambulance offload delay, 14 articles studied its effects, and 89 articles studied proposed solutions (of which, 58 articles studied ambulance diversion and 31 articles studied other interventions). A common theme found throughout the reviewed articles was that this problem includes clinical, operational, and administrative perspectives, and therefore must be addressed in a system-wide manner to be mitigated. The most common intervention type was ambulance diversion. Yet, it yields controversial results. A number of recommendations are made with respect to future research in this area. These include conducting system-wide mitigation intervention, addressing root causes of ED crowding and access block, and providing more operations research models to evaluate AOD mitigation interventions prior implementations. In addition, measurements of AOD should be improved to assess the size and magnitude of this problem more accurately.

An Electronic Dashboard to Monitor Patient Flow at the Johns Hopkins Hospital: Communication of Key Performance Indicators Using the Donabedian Model

Efforts to monitoring and managing hospital capacity depend on the ability to extract relevant time-stamped data from electronic medical records and other information technologies. However, the various characterizations of patient flow, cohort decisions, sub-processes, and the diverse stakeholders requiring data visibility create further overlying complexity. We use the Donabedian model to prioritize patient flow metrics and build an electronic dashboard for enabling communication. Ten metrics were identified as key indicators including outcome (length of stay, 30-day readmission, operating room exit delays, capacity-related diversions), process (timely inpatient unit discharge, emergency department disposition), and structural metrics (occupancy, discharge volume, boarding, bed assignation duration). Dashboard users provided real-life examples of how the tool is assisting capacity improvement efforts, and user traffic data revealed an uptrend in dashboard utilization from May to October 2017 (26 to 148 views per month, respectively). Our main contributions are twofold. The former being the results and methods for selecting key performance indicators for a unit, department, and across the entire hospital (i.e., separating signal from noise). The latter being an electronic dashboard deployed and used at The Johns Hopkins Hospital to visualize these ten metrics and communicate systematically to hospital stakeholders. Integration of diverse information technology may create further opportunities for improved hospital capacity.

Sustaining critical care: using evidence-based simulation to evaluate ICU management policies

Intensive Care Units (ICU) are costly yet critical hospital departments that should be available to care for patients needing highly specialized critical care. Shortage of ICU beds in many regions of the world and the constant fire-fighting to make these beds available through various ICU management policies motivated this study. The paper discusses the application of a generic system dynamics model of emergency patient flow in a typical hospital, populated with empirical evidence found in the medical and hospital administration literature, to explore the dynamics of intended and unintended consequences of such ICU management policies under a natural disaster crisis scenario. ICU management policies that can be implemented by a single hospital on short notice, namely premature transfer from ICU, boarding in ward, and general ward admission control, along with their possible combinations, are modeled and their impact on managerial and health outcome measures are investigated. The main insight out of the study is that the general ward admission control policy outperforms the rest of ICU management policies under such crisis scenarios with regards to reducing total mortality, which is counter intuitive for hospital administrators as this policy is not very effective at alleviating the symptoms of the problem, namely high ED and ICU occupancy rates that are closely monitored by hospital management particularly in times of crisis. A multivariate sensitivity analysis on parameters with diverse range of values in the literature found the superiority of the general ward admission control to hold true in every scenario.

The Impact of Ambulance and Patient Diversion on Crowdedness of Multiple Emergency Departments in a Region

Emergency department (ED) overcrowding threatens healthcare quality. Ambulance diversion (AD) may relieve ED overcrowding; however, diverting patients from an overcrowded ED will load neighboring EDs with more patients and may result in regional overcrowding. The purpose of this study was to evaluate the impact of different diversion strategies on the crowdedness of multiple EDs in a region. The importance of regional coordination was also explored. A queuing model for patient flow was utilized to develop a computer program for simulating AD among EDs in a region. Key parameters, including patient arrival rates, percentages of patients of different acuity levels, percentage of patients transported by ambulance, and total resources of EDs, were assigned based on real data. The crowdedness indices of each ED and the regional crowdedness index were assessed to evaluate the effectiveness of various AD strategies. Diverting patients equally to all other EDs in a region is better than diverting patients only to EDs with more resources. The effect of diverting all ambulance-transported patients is similar to that of diverting only low-acuity patients. To minimize regional crowdedness, ambulatory patients should be sent to proper EDs when AD is initiated. Based on a queuing model with parameters calibrated by real data, patient flows of EDs in a region were simulated by a computer program. From a regional point of view, randomly diverting ambulatory patients provides almost no benefit. With regards to minimizing the crowdedness of the whole region, the most promising strategy is to divert all patients equally to all other EDs that are not already crowded. This result implies that communication and coordination among regional hospitals are crucial to relieve overall crowdedness. A regional coordination center may prioritize AD strategies to optimize ED utility.

The effect of an ambulance diversion ban on emergency department length of stay and ambulance turnaround time

STUDY OBJECTIVE

Massachusetts became the first state in the nation to ban ambulance diversion in 2009. It was feared that the diversion ban would lead to increased emergency department (ED) crowding and ambulance turnaround time. We seek to characterize the effect of a statewide ambulance diversion ban on ED length of stay and ambulance turnaround time at Boston-area EDs.

METHODS

We conducted a retrospective, pre-post observational analysis of 9 Boston-area hospital EDs before and after the ban. We used ED length of stay as a proxy for ED crowding. We compared hospitals individually and in aggregate to determine any changes in ED length of stay for admitted and discharged patients, ED volume, and turnaround time.

RESULTS

No ED experienced an increase in ED length of stay for admitted or discharged patients or ambulance turnaround time despite an increase in volume for several EDs. There was an overall 3.6% increase in ED volume in our sample, a 10.4-minute decrease in length of stay for admitted patients, and a 2.2-minute decrease in turnaround time. When we compared high- and low-diverting EDs separately, neither saw an increase in length of stay, and both saw a decrease in turnaround time.

CONCLUSION

After the first statewide ambulance diversion ban, there was no increase in ED length of stay or ambulance turnaround time at 9 Boston-area EDs. Several hospitals actually experienced improvements in these outcome measures. Our results suggest that the ban did not worsen ED crowding or ambulance availability at Boston-area hospitals.

Managing emergency department overcrowding via ambulance diversion: a discrete event simulation model

BACKGROUND/PURPOSE

Ambulance diversion (AD) is considered one of the possible solutions to relieve emergency department (ED) overcrowding. Study of the effectiveness of various AD strategies is prerequisite for policy-making. Our aim is to develop a tool that quantitatively evaluates the effectiveness of various AD strategies.

METHODS

A simulation model and a computer simulation program were developed. Three sets of simulations were executed to evaluate AD initiating criteria, patient-blocking rules, and AD intervals, respectively. The crowdedness index, the patient waiting time for service, and the percentage of adverse patients were assessed to determine the effect of various AD policies.

RESULTS

Simulation results suggest that, in a certain setting, the best timing for implementing AD is when the crowdedness index reaches the critical value, 1.0 - an indicator that ED is operating at its maximal capacity. The strategy to divert all patients transported by ambulance is more effective than to divert either high-acuity patients only or low-acuity patients only. Given a total allowable AD duration, implementing AD multiple times with short intervals generally has better effect than having a single AD with maximal allowable duration.

CONCLUSION

An input-throughput-output simulation model is proposed for simulating ED operation. Effectiveness of several AD strategies on relieving ED overcrowding was assessed via computer simulations based on this model. By appropriate parameter settings, the model can represent medical resource providers of different scales. It is also feasible to expand the simulations to evaluate the effect of AD strategies on a community basis. The results may offer insights for making effective AD policies.

Ambulance diversion as a proxy for emergency department crowding: the effect on pediatric mortality in a metropolitan area

OBJECTIVES

The objective was to determine the prevalence of emergency department (ED) ambulance diversion among Houston pediatric hospitals and its association with mortality of pediatric patients.

METHODS

Hospital diversion and patient data between August 2002 and December 2004 were used to examine the impact of diversion on mortality of children under age 18 years. Patients were assumed to be exposed to ED crowding if diversion and admission or ED arrival times overlapped. Univariate and logistic regression were performed to determine if diversion was associated with mortality while controlling for age, illness severity, injury, and transfer status.

RESULTS

Mean hospital diversion hours as a percentage of operating hours were 10.58 (standard deviation [SD] +/- 9). Overall, of 63,780 admissions, there were 4,095 (6.4%) children admitted during diversion. Fewer severely ill patients were admitted during diversion than nondiversion times (odds ratio [OR] = 0.72; 95% confidence interval [CI] = 0.66 to 0.78). The presence of diversion was protective for mortality (OR = 0.51; 95% CI = 0.34 to 0.77) in bivariate analysis. Mortality was associated with presence of major or extreme illness (OR = 60.7; 95% CI = 45.2 to 81.5), injury (OR=1.7; 95% CI = 1.4 to 2.1), and transfer status (OR = 6.3; 95% CI = 5.4 to 7.3). Using conditional logistic regression, major or extreme illness (OR = 50.7; 95% CI = 37.7 to 68.3), injury (OR 3.7; 95% CI = 2.9 to 4.7), and transfer (OR = 2.7; 95% CI = 2.2, 3.2) were associated with mortality, but diversion did not show any association with mortality. After combining ED and inpatient deaths, no association between diversion and mortality was observed.

CONCLUSIONS

Hospital diversion due to ED crowding is common in pediatrics. The authors found no evidence of an association between diversion and ED and inpatient pediatric mortality.

Systematic review of emergency department crowding: causes, effects, and solutions

Emergency department (ED) crowding represents an international crisis that may affect the quality and access of health care. We conducted a comprehensive PubMed search to identify articles that (1) studied causes, effects, or solutions of ED crowding; (2) described data collection and analysis methodology; (3) occurred in a general ED setting; and (4) focused on everyday crowding. Two independent reviewers identified the relevant articles by consensus. We applied a 5-level quality assessment tool to grade the methodology of each study. From 4,271 abstracts and 188 full-text articles, the reviewers identified 93 articles meeting the inclusion criteria. A total of 33 articles studied causes, 27 articles studied effects, and 40 articles studied solutions of ED crowding. Commonly studied causes of crowding included nonurgent visits, "frequent-flyer" patients, influenza season, inadequate staffing, inpatient boarding, and hospital bed shortages. Commonly studied effects of crowding included patient mortality, transport delays, treatment delays, ambulance diversion, patient elopement, and financial effect. Commonly studied solutions of crowding included additional personnel, observation units, hospital bed access, nonurgent referrals, ambulance diversion, destination control, crowding measures, and queuing theory. The results illustrated the complex, multifaceted characteristics of the ED crowding problem. Additional high-quality studies may provide valuable contributions toward better understanding and alleviating the daily crisis. This structured overview of the literature may help to identify future directions for the crowding research agenda.

The impact of ambulance diversion on EMS resource availability

OBJECTIVE

Ambulance diversion has been proposed as a solution to emergency department overcrowding and waiting room deaths. For ethical and legal reasons, it remains highly controversial. The impact on EMS resources is not known. This study seeks to determine how diversion impacts the availability of ambulance resources, specifically transport time, hospital turnaround, and total out-of-service time.

METHODS

All emergency ambulance responses in 2002 while one of the city's hospitals was on diversion were collected, including those responses during the hour of the diversion and 30 minutes before and after. The time intervals for these responses were time and date matched to 2001, if no hospital was on diversion. Total out-of-service time (911 to availability for another call), time from departure from scene to arrival at hospital (transport interval), and time from arrival at hospital to availability for another call (turnaround time) were compared by using a t-test.

RESULTS

The 1,563 instances of diversion were included, with 1,403 controls. Interim analysis allowed calculation of a sample size of 1,049 in each group to show a 2-minute difference in turnaround time and 330 calls in each for a 5-minute difference in total out-of-service time (0.25 SD). Transport, hospital turnaround, and total out-of-service times were not different between diversion and control time periods. This relies on the accuracy of the status button system and may not generalize to systems with different geography, diversion policy, number of hospitals, or handling of interfacility transfers.

CONCLUSION

The availability of EMS resources is maintained during times of ambulance diversion. Diversion avoids potential delays associated with sending ambulances to overwhelmed emergency departments.

Likelihood of reroute during ambulance diversion periods in central Maryland

OBJECTIVES

To determine the proportion of patients rerouted during ambulance diversion periods and factors associated with reroute.

METHODS

A retrospective cohort design was used to examine reroute practices of prehospital providers in central Maryland in 2000. Ambulance transport and diversion data were merged to identify transports that occurred during diversion periods. The proportion of patients rerouted when the closest hospital was on diversion was determined. Generalized estimating equation modeling identified patient, transport, and hospital factors that influenced the likelihood of reroute.

RESULTS

Central Maryland hospitals were on diversion 25% of the time in 2000, although it varied by hospital (range of 1-34%). There were 128,165 transports during the study period, of which 18,633 occurred when the closest hospital was on diversion. Of these, only 23% were rerouted. More than half of all transports during a diversion period (53%) occurred when multiple neighboring hospitals were also on diversion. The factors that influenced the likelihood of reroute the most were hospital-related factors. Large volume hospitals and hospitals that spent more time on diversion were less likely to have transports rerouted to them.

CONCLUSIONS

Rerouted transports more frequently go to lower volume, less busy hospitals. However, only a small proportion of patients were rerouted. Prehospital providers have limited options because often when one hospital is on diversion, other nearby hospitals are as well. Although ambulance diversion may be an important signal of hospital distress, in this region it infrequently resulted in its intended outcome, rerouting patients to less crowded facilities.

The effects of minimizing ambulance diversion hours on emergency departments

This study explores the effects of minimizing Emergency Department (ED) bypass on individual hospital's ED census, ambulance transports, and admissions. Five hospitals in a geographic area collected data over 3 weeks. The first and third week represented controls, whereas the second week hospitals minimized their usage of bypass. Data collected included hours on bypass, ED census, ambulance runs, hospital admissions, and inter-facility transfers. The total number of hours on bypass for all hospitals for pre-trial, trial, and post-trial weeks were 112.2, 0.3, and 47, respectively. There were several statistical shifts in the proportion of ambulance runs and admissions seen by individual hospitals. Clinically, these shifts in patients were minor and within ED capacity. Hospitals in a given geographic area may successfully reduce the number of hours on bypass with possible minor shifting in the number of ambulance runs and admissions that are within ED capacity.

The effects of ambulance diversion: a comprehensive review

OBJECTIVES

To review the current literature on the effects of ambulance diversion (AD).

METHODS

The authors performed a systematic review of AD and its effects. PubMed, EMBASE, the Cochrane database, societal meeting abstracts, and references from relevant articles were searched. All articles were screened for relevance to AD.

RESULTS

The authors examined 600 citations and reviewed the 107 articles relevant to AD. AD is a common occurrence that is increasing in frequency. AD is associated with periods of emergency department (ED) crowding (Mondays, mid-afternoon to early evening, influenza season, and when hospitals are at capacity). Interventions that redesign the AD process or that provide additional hospital or ED resources reduce diversion frequency. AD is associated with increased patient transport times and time to thrombolytics but not with mortality. AD is associated with loss of estimated hospital revenues. Short of anecdotal or case reports, no studies measured the effect of AD on ED crowding, morbidity, patient and provider satisfaction, or EMS resource utilization.

CONCLUSIONS

Despite its common use, there is a relative paucity of studies on the effects of AD. Further research into these effects should be performed so that we may understand the role of AD in the health system.

Facilitating EMS turnaround intervals at hospitals in the face of receiving facility overcrowding

The escalating national problem of oversaturated hospital beds and emergency departments (EDs) has resulted in serious operational impediments within patient-receiving facilities. It has also had a growing impact on the 9-1-1 emergency care system. Beyond the long-standing difficulties arising from ambulance diversion practices, many emergency medical services (EMS) crews are now finding themselves detained in EDs for protracted periods, unable to transfer care of their transported patients to ED staff members. Key factors have included a lack of beds or stretcher space, and, in some cases, EMS personnel are used transiently for ED patient care services. In other circumstances, ED staff members no longer prioritize rapid turnaround of EMS-transported patients because of the increasing volume and acuity of patients already in their care. The resulting detention of EMS crews confounds concurrent ambulance availability problems, creates concrete risks for delayed EMS responses to impending critical cases, and incurs regulatory jeopardy for hospitals. Communities should take appropriate steps to ensure that delivery intervals (time elapsing from entry into the hospital to physical transfer of patient care to ED staff) remain extremely brief (less than a few minutes) and that they rarely exceed 10 minutes. While recognizing that the root causes of these issues will require far-reaching national health care policy changes, EMS and local government officials should still maintain ongoing dialogues with hospital chief administrators to mitigate this mutual crisis of escalating service demands. Federal and state health officials should also play an active role in monitoring progress and compliance.

Emergency Department Diversion and Trauma Mortality: Evidence From Houston, Texas

BACKGROUND

This study examined the relation between trauma death rates and hospital diversion in the Houston emergency medical service area.

METHODS

A risk analysis and logistic regression were performed comparing death rates for trauma patients hospitalized on significant emergency department diversion days, defined as days when both of two level 1 hospitals were on diversion for more than 8 hours, and on nonsignificant diversion days, defined as one or both hospitals on diversion for fewer than 8 hours or not on diversion at all.

RESULTS

The percentage of deaths among all trauma patients, transfers, and nontransfers admitted on significant diversion days was consistently higher than on nonsignificant diversion days, but the difference was not statistically significant. A higher mortality rate, approaching statistical significance, was found for one subgroup of the most severe trauma patients who had been transferred from another hospital.

CONCLUSIONS

A possible association between emergency department diversion and death rates in Houston trauma hospitals was found, particularly among the most severe trauma patients transferred from lower-level hospitals. A follow-up study is needed for further investigation of this relation.

Emergency department crowding and thrombolysis delays in acute myocardial infarction

STUDY OBJECTIVE

We estimate the effect of emergency department (ED) crowding on door-to-needle time for patients given intravenous thrombolysis for suspected acute myocardial infarction.

METHODS

This was a retrospective observational study of patients thrombolyzed in the ED for suspected acute myocardial infarction in 1998 to 2000 in 25 community and teaching hospital EDs in Ontario. EDs located close together and sharing a common ambulance diversion system were grouped into networks consisting of 2 to 5 hospitals each. At patient registration in an ED, the ambulance diversion status of all EDs in the network was determined. Network crowding was calculated as the percentage of EDs that were diverting ambulances on patient registration, categorized as none (0%), moderate (<60%), and high (> or =60%). Door-to-needle time was defined as time from ED registration to drug administration. Multivariable quantile regression and logistic regression were carried out; covariates included age, sex, ECG characteristics, previous acute myocardial infarction, vital signs, time of presentation, and hospital type.

RESULTS

A total of 3,452 thrombolysis patients were included: mean age was 62.9 years, and 73% were male patients. Overall median door-to-needle time was 43 minutes (interquartile ratio 27 to 80). Median door-to-needle time was 40, 45, and 47 minutes in conditions of none, moderate, and high network crowding, respectively ( P <.001). The adjusted odds ratios for door-to-needle time delay (>30 minutes) and major delay (>60 minutes) were 1.32 (95% confidence interval [CI] 0.98 to 1.79) and 1.40 (95% CI 1.12 to 1.75), respectively, for high network crowding compared with none, and 1.21 (95% CI 0.89 to 1.63) and 1.06 (95% CI 0.86 to 1.29), respectively, for moderate crowding compared with none. In multivariate analyses, moderate and high crowding conditions were associated with increased median door-to-needle time (3.0 minutes [95% CI 0.1 to 6.0] and 5.8 minutes [95% CI 2.7 to 9.0], respectively).

CONCLUSION

ED crowding is associated with increased door-to-needle times for patients with suspected acute myocardial infarction and may represent a barrier to improving cardiac care in EDs.

Community influenza outbreaks and emergency department ambulance diversion

STUDY OBJECTIVE

Influenza has been linked to emergency department (ED) crowding, yet few studies have examined this association. We describe the relationship between ED crowding and influenza outbreaks.

METHODS

A retrospective time series analysis was conducted in Toronto from January 1996 to April 1999 (n=170 weeks). We obtained weekly data on laboratory-confirmed influenza and other respiratory virus cases in the community, ED ambulance diversion, and visits to all city EDs (n=20). The main outcome was ambulance diversion, measured as the mean number of hours per week in which EDs were forced to divert all ambulances.

RESULTS

A mean of 10,936 ED visits occurred weekly (average age of patients 39.9 years; 51% female patients). EDs diverted ambulances an average of 3.4 hours per week (range 0.3 to 15 hours). Four influenza seasons occurred, lasting between 18 and 30 weeks each, with weekly influenza case counts ranging from 0 to 236. There were fewer than 10 cases per week in 119 of 170 weeks (70%). In time-series models, influenza was independently associated with ED ambulance diversion (P<.0001). For every 100 cases of influenza in the community in a given week, ED ambulance diversion would be expected to increase by 2.5 h/wk at the average ED (95% confidence interval [CI] 1.2 to 3.9 h/wk). During influenza seasons, 24.3% (95% CI 11.3% to 37.2%) of observed weekly ambulance diversion was attributable to influenza.

CONCLUSION

Influenza seasons are associated with increased ED ambulance diversion. The impact is substantial but brief because there is little or no influenza activity most of each year.

Approach to decreasing emergency department ambulance diversion hours

Analysis between two local Emergency Departments (EDs) suggested an oscillatory phenomenon for ambulance diversion: When one hospital went on diversion it led to a disproportionate flow of ambulance traffic to a neighboring facility that subsequently was forced to go on divert. We hypothesized if one hospital could avoid diversion status, the need for diversion could be averted in the neighboring facility. ED A secured additional resources and made a commitment to no diversion for 1 week. No changes in operations occurred in hospital B. We found no differences in ambulance runs or ED census at either facility comparing the week before, during, and after the trial. There was a dramatic decline in diversion hours from 19.7 to 1.4 and 27.7 to 0 at hospitals A and B, respectively, during the trial period (p < 0.05) compared to the weeks before and after. We conclude that reciprocating effects can be decreased with one institution's commitment to avoid diversion, thus decreasing the need for diversion at a neighboring facility.

When the safety net is unsafe: real-time assessment of the overcrowded emergency department

Although much work has been done evaluating causes for increased demand for emergency department (ED) services, few ways are available to help determine that an individual ED is overcrowded. Four calculations are proposed using real-time data for accurately diagnosing an ED with potential for failing both as a safety net and as a source for quality health care. The bed ratio (BR) accounts for the number of patients in relation to the available treatment spaces. The BR is obtained by adding the current number of ED patients to the predicted arrivals minus the predicted departures and dividing the result by the total number of treatment spaces. The acuity ratio (AR) measures the relative burden of illness in the ED. The AR is the average triage category of all patients in the ED. The provider ratio (PR) determines the volume of patients that can be evaluated and treated by the physician providers. The PR is found by dividing the arrivals per hour by the sum of the average patients per hour usually disposed for each provider on duty. From these ratios, the demand value (DV) is calculated, which gives an overall measure of current demand. The DV is found by taking the sum of the BR and PR and multiplying by the AR. A DV of more than 7 should initiate a specific assessment of the individual ratios in order to accurately diagnose the problem and institute action. Based on the values, predetermined processes can be instituted to help remedy the overcrowded situation. Trended over time, the ratios can provide the data needed for better resource assessment, planning, and allocation.