Impact Of Ambulance Diversion: Black Patients With Acute Myocardial Infarction Had Higher Mortality Than Whites

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.

Implications of Bias in Artificial Intelligence: Considerations for Cardiovascular Imaging

PURPOSE OF REVIEW

Bias in artificial intelligence (AI) models can result in unintended consequences. In cardiovascular imaging, biased AI models used in clinical practice can negatively affect patient outcomes. Biased AI models result from decisions made when training and evaluating a model. This paper is a comprehensive guide for AI development teams to understand assumptions in datasets and chosen metrics for outcome/ground truth, and how this translates to real-world performance for cardiovascular disease (CVD).

RECENT FINDINGS

CVDs are the number one cause of mortality worldwide; however, the prevalence, burden, and outcomes of CVD vary across gender and race. Several biomarkers are also shown to vary among different populations and ethnic/racial groups. Inequalities in clinical trial inclusion, clinical presentation, diagnosis, and treatment are preserved in health data that is ultimately used to train AI algorithms, leading to potential biases in model performance. Despite the notion that AI models themselves are biased, AI can also help to mitigate bias (e.g., bias auditing tools). In this review paper, we describe in detail implicit and explicit biases in the care of cardiovascular disease that may be present in existing datasets but are not obvious to model developers. We review disparities in CVD outcomes across different genders and race groups, differences in treatment of historically marginalized groups, and disparities in clinical trials for various cardiovascular diseases and outcomes. Thereafter, we summarize some CVD AI literature that shows bias in CVD AI as well as approaches that AI is being used to mitigate CVD bias.

Racial and ethnic disparities in emergency department transfers to public hospitals

OBJECTIVE

To examine racial/ethnic differences in emergency department (ED) transfers to public hospitals and factors explaining these differences.

DATA SOURCES AND STUDY SETTING

ED and inpatient data from the Healthcare Cost and Utilization Project for Florida (2010-2019); American Hospital Association Annual Survey (2009-2018).

STUDY DESIGN

Logistic regression examined race/ethnicity and payer on the likelihood of transfer to a public hospital among transferred ED patients. The base model was controlled for patient and hospital characteristics and year fixed effects. Models II and III added urbanicity and hospital referral region (HRR), respectively. Model IV used hospital fixed effects, which compares patients within the same hospital. Models V and VI stratified Model IV by payer and condition, respectively. Conditions were classified as emergency care sensitive conditions (ECSCs), where transfer is protocolized, and non-ECSCs. We reported marginal effects at the means.

DATA COLLECTION/EXTRACTION METHODS

We examined 1,265,588 adult ED patients transferred from 187 hospitals.

PRINCIPAL FINDINGS

Black patients were more likely to be transferred to public hospitals compared with White patients in all models except ECSC patients within the same initial hospital (except trauma). Black patients were 0.5-1.3 percentage points (pp) more likely to be transferred to public hospitals than White patients in the same hospital with the same payer. In the base model, Hispanic patients were more likely to be transferred to public hospitals compared with White patients, but this difference reversed after controlling for HRR. Hispanic patients were - 0.6 pp to -1.2 pp less likely to be transferred to public hospitals than White patients in the same hospital with the same payer.

CONCLUSIONS

Large population-level differences in whether ED patients of different races/ethnicities were transferred to public hospitals were largely explained by hospital market and the initial hospital, suggesting that they may play a larger role in explaining differences in transfer to public hospitals, compared with other external factors.

Emergency department condition acuity, length of stay, and revisits among deaf and hard-of-hearing patients: A retrospective chart review

OBJECTIVE

Deaf and hard-of-hearing (DHH) patients are understudied in emergency medicine health services research. Theory and limited evidence suggest that DHH patients are at higher risk of emergency department (ED) utilization and poorer quality of care. This study assessed ED condition acuity, length of stay (LOS), and acute ED revisits among DHH patients. We hypothesized that DHH patients would experience poorer ED care outcomes.

METHODS

We conducted a retrospective chart review of a single health care system using data from a large academic medical center in the southeast United States. Data were received from the medical center's data office, and we sampled patients and encounters from between June 2011 and April 2020. We compared DHH American Sign Language (ASL) users (n = 108), DHH English speakers (n = 358), and non-DHH English speakers (n = 302). We used multilevel modeling to assess the differences among patient segments in outcomes related to ED use and care.

RESULTS

As hypothesized, DHH ASL users had longer ED LOS than non-DHH English speakers, on average 30 min longer. Differences in ED condition acuity, measured through Emergency Severity Index and triage pain scale, were not statistically significant. DHH English speakers represented a majority (61%) of acute ED revisit encounters.

CONCLUSIONS

Our study identified that DHH ASL users have longer ED LOS than non-DHH English speakers. Additional research is needed to further explain the association between DHH status and ED care outcomes (including ED LOS and acute revisit), which may be used to identify intervention targets to improve health equity.

Ambulance diversion and ED destination by race/ethnicity: evaluation of Massachusetts' ambulance diversion ban

Background

The impact of ambulance diversion on potentially diverted patients, particularly racial/ethnic minority patients, is largely unknown. Treating Massachusetts’ 2009 ambulance diversion ban as a natural experiment, we examined if the ban was associated with increased concordance in Emergency Medical Services (EMS) patients of different race/ethnicity being transported to the same emergency department (ED).

Methods

We obtained Medicare Fee for Service claims records (2007–2012) for enrollees aged 66 and older. We stratified the country into patient zip codes and identified zip codes with sizable (non-Hispanic) White, (non-Hispanic) Black and Hispanic enrollees. For a stratified random sample of enrollees from all diverse zip codes in Massachusetts and 18 selected comparison states, we identified EMS transports to an ED. In each zip code, we identified the most frequent ED destination of White EMS-transported patients (“reference ED”). Our main outcome was a dichotomous indicator of patient EMS transport to the reference ED, and secondary outcome was transport to an ED serving lower-income patients (“safety-net ED”). Using a difference-in-differences regression specification, we contrasted the pre- to post-ban changes in each outcome in Massachusetts with the corresponding change in the comparison states.

Results

Our study cohort of 744,791 enrollees from 3331 zip codes experienced 361,006 EMS transports. At baseline, the proportion transported to the reference ED was higher among White patients in Massachusetts and comparison states (67.2 and 60.9%) than among Black (43.6 and 46.2%) and Hispanic (62.5 and 52.7%) patients. Massachusetts ambulance diversion ban was associated with a decreased proportion transported to the reference ED among White (− 2.7 percentage point; 95% CI, − 4.5 to − 1.0) and Black (− 4.1 percentage point; 95% CI, − 6.2 to − 1.9) patients and no change among Hispanic patients. The ban was associated with an increase in likelihood of transport to a safety-net ED among Hispanic patients (3.0 percentage points, 95% CI, 0.3 to 5.7) and a decreased likelihood among White patients (1.2 percentage points, 95% CI, − 2.3 to − 0.2).

Conclusion

Massachusetts ambulance diversion ban was associated with a reduction in the proportion of White and Black EMS patients being transported to the most frequent ED destination for White patients, highlighting the role of non-proximity factors in EMS transport destination.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08358-8.

Association between race/ethnicity and income on the likelihood of coronary revascularization among postmenopausal women with acute myocardial infarction: Women's health initiative study

BACKGROUND

Historically, race, income, and gender were associated with likelihood of receipt of coronary revascularization for acute myocardial infarction (AMI). Given public health initiatives such as Healthy People 2010, it is unclear whether race and income remain associated with the likelihood of coronary revascularization among women with AMI.

METHODS

Using the Women's Health Initiative Study, hazards ratio (HR) of revascularization for AMI was compared for Black and Hispanic women vs White women and among women with annual income <$20,000/year vs ≥$20,000/year over median 9.5 years follow-up(1993-2019). Proportional hazards models were adjusted for demographics, comorbidities, and AMI type. Results were stratified by revascularization type: percutaneous coronary intervention and coronary artery bypass grafting(CABG). Trends by race and income were compared pre- and post-2010 using time-varying analysis.

RESULTS

Among 5,284 individuals with AMI (9.5% Black, 2.8% Hispanic, and 87.7% White; 23.2% <$20,000/year), Black race was associated with lower likelihood of receiving revascularization for AMI compared to White race in fully adjusted analyses [HR:0.79(95% Confidence Interval:[CI]0.66,0.95)]. When further stratified by type of revascularization, Black race was associated with lower likelihood of percutaneous coronary intervention for AMI compared to White race [HR:0.72(95% CI:0.59,0.90)] but not for CABG [HR:0.97(95%CI:0.72,1.32)]. Income was associated with lower likelihood of revascularization [HR:0.90(95%CI:0.82,0.99)] for AMI. No differences were observed for other racial/ethnic groups. Time periods (pre/post-2010) were not associated with change in revascularization rates.

CONCLUSION

Black race and income remain associated with lower likelihood of revascularization among patients presenting with AMI. There is a substantial need to disrupt the mechanisms contributing to race, sex, and income disparities in AMI management.

Structural Discrimination in Emergency Care: How a Sick System Affects Us All

Drawing on evidence of socioeconomic disparities in emergency care, we show how structural discrimination is the most pervasive driver of these disparities, largely because of an inequitable distribution of healthcare services and unequal benefits derived from scientific advancement. We analyze how the market-based healthcare system in the U.S. has created a scenario in which the allocation of emergency care resources does not match community demand for emergency care, resulting in disproportionately poor access, treatment, and outcomes among historically underserved populations. Without fundamental reform, there is little hope for decreasing the health outcome gaps between the "haves" and "have-nots" in the United States.

Racial and neighborhood disparities in mortality among hospitalized COVID-19 patients in the United States: An analysis of the CDC case surveillance database

BACKGROUND

Black and Hispanic populations have higher overall COVID-19 infection and mortality odds compared to Whites. Some state-wide studies conducted in the early months of the pandemic found no in-hospital racial disparities in mortality.

METHODS

We performed chi-square and logistic regression analyses on the CDC COVID-19 Case Surveillance Restricted Database. The primary outcome of the study was all-cause in-hospital mortality. The primary exposures were racial group (White, Black, Hispanic and Others) and neighborhood type (low vulnerability, moderate vulnerability, high vulnerability, very high vulnerability).

FINDINGS

The overall unadjusted mortality rate was 33% and was lowest among Hispanics. In the fully adjusted models, Blacks and Hispanics had higher overall odds of dying [OR of 1.20 (95% CI 1.15, 1.25) and 1.23 (95% CI 1.17, 1.28) respectively] compared with White patients, and patients from neighborhoods with very high vulnerability had the highest mortality odds in the Northeast, Midwest and overall [Adjusted OR 2.08 (95% CI 1.91, 2.26)]. In the Midwest, Blacks and Hispanics had higher odds of mortality compared with Whites, but this was not observed in other regions.

INTERPRETATION

Among hospitalized COVID-19 patients, Blacks and Hispanics were more likely to die compared to Whites in the Midwest. Patients from highly vulnerable neighborhoods also had the highest likelihood of death in the Northeast and Midwest. These results raise important questions on our efforts to curb healthcare disparities and structural racism in the healthcare setting.

Conceptual Model of Emergency Department Utilization among Deaf and Hard-of-Hearing Patients: A Critical Review

Deaf and hard-of-hearing (DHH) populations are understudied in health services research and underserved in healthcare systems. Existing data indicate that adult DHH patients are more likely to use the emergency department (ED) for less emergent conditions than non-DHH patients. However, the lack of research focused on this population’s ED utilization impedes the development of health promotion and quality improvement interventions to improve patient health and quality outcomes. The purpose of this study was to develop a conceptual model describing patient and non-patient (e.g., community, health system, provider) factors influencing ED utilization and ED care processes among DHH people. We conducted a critical review and used Andersen’s Behavioral Model of Health Services Use and the PRECEDE-PROCEED Model to classify factors based on their theoretical and/or empirically described role. The resulting Conceptual Model of Emergency Department Utilization Among Deaf and Hard-of-Hearing Patients provides predisposing, enabling, and reinforcing factors influencing DHH patient ED care seeking and ED care processes. The model highlights the abundance of DHH patient and non-DHH patient enabling factors. This model may be used in quality improvement interventions, health services research, or in organizational planning and policymaking to improve health outcomes for DHH patients.

Potential bypassing of nearest emergency department by EMS transports

OBJECTIVE

Guidelines recommend emergency medical services (EMS) patients to be transported to the nearest appropriate emergency department (ED). Our objective was to estimate the prevalence of EMS transport to an ED other than the nearest ED ("potential bypassing").

DATA SOURCES

Illinois Prehospital Patient Care Report Data of EMS transports (July 2019 to December 2019).

DATA COLLECTION/EXTRACTION METHODS

We identified all EMS ground transports with an advanced life-support (ALS) paramedic to an ED for patients aged 21 years and older. Using street address of incident location, we performed geocoding and driving route analyses and obtained estimated driving distance and time to the destination ED and alternative EDs.

MAIN OUTCOME AND MEASURES

Our main outcomes were dichotomous indicators of potential bypassing of the nearest ED based on distance and time. As secondary outcomes we examined potential bypassing indicators based on excess driving distance and time.

STUDY DESIGN

We used Poisson regression models to obtain adjusted relative rates of potential bypassing indicators by acuity level, primary impression, patient demographics and geographic characteristics.

PRINCIPAL FINDINGS

Our study cohort of 361,051 EMS transports consisted of 5.8% critical, 37.2% emergent and 57.0% low acuity cases transported to 222 EDs. The observed rate of potential bypassing was approximately 34% of cases for each acuity level. Treating the cardiovascular primary impression code group as the reference case, we found small to no differences in potential bypassing rates across other primary impression code groups of all acuity levels, with the exception of critical acuity trauma cases for which potential bypassing rate was 64% higher (incidence rate ratio = 1.64, 95% confidence interval, 1.54-1.74). Compared to zip codes with one ED within a 5-mile vicinity, potential bypassing was higher in areas with no ED or multiple EDs within a 5-mile vicinity.

CONCLUSION

Approximately one-third of EMS transports potentially bypassed the nearest ED. EMS transport destination may be motivated by factors other than proximity.

Balancing Efficiency and Access: Discouraging Emergency Department Boarding in a Global Budget System

Reducing cost without sacrificing quality of patient care is an important yet challenging goal for healthcare professionals and policymakers alike. This challenge is at the forefront in the United States, where per capita healthcare costs are much higher than in similar countries around the world. The state of Maryland is unique in the hospital financing landscape due to its “capitation” payment system (also known as “global budget”), in which revenue for hospital-based services is set at the beginning of the year. Although Maryland’s system has yielded many benefits, including reduced Medicare spending, it also has had unintentional adverse consequences. These consequences, such as increased emergency department boarding and ambulance diversion, constrain Maryland hospitals’ ability to fulfill their role as emergency care providers and act as a safety net for vulnerable patient populations. In this article, we suggest policy remedies to mitigate the unintended consequences of Maryland’s model that should also prove instructive for a variety of emerging alternative payment mechanisms.

The association of Medicaid expansion and racial/ethnic inequities in access, treatment, and outcomes for patients with acute myocardial infarction

Introduction

After having an acute myocardial infarction (AMI), racial and ethnic minorities have less access to care, decreased rates of invasive treatments such as percutaneous coronary intervention (PCI), and worse outcomes compared with white patients. The objective of this study was to determine whether the Affordable Care Act’s expansion of Medicaid eligibility was associated with changes in racial disparities in access, treatments, and outcomes after AMI.

Methods

Quasi-experimental, difference-in-differences-in-differences analysis of non-Hispanic white and minority patients with acute myocardial infarction in California and Florida from 2010–2015, using linear regression models to estimate the difference-in-differences. This population-based sample included all Medicaid and uninsured patients ages 18–64 hospitalized with acute myocardial infarction in California, which expanded Medicaid through the Affordable Care Act beginning as early as July 2011 in certain counties, and Florida, which did not expand Medicaid. The main outcomes included rates of admission to hospitals capable of performing PCI, rates of transfer for patients who first presented to hospitals that did not perform PCI, rates of PCI during hospitalization and rates of early (within 48 hours of admission) PCI, rates of readmission to the hospital within 30 days, and rates of in-hospital mortality.

Results

A total of 55,991 hospital admissions met inclusion criteria, 32,540 of which were in California and 23,451 were in Florida. Among patients with AMI who initially presented to a non-PCI hospital, the likelihood of being transferred increased by 12 percentage points (95% CI 2 to 21) for minority patients relative to white patients after the Medicaid expansion. The likelihood of undergoing PCI increased by 3 percentage points (95% CI 0 to 5) for minority patients relative to white patients after the Medicaid expansion. We did not find an association between the Medicaid expansion and racial disparities in overall likelihood of admission to a PCI hospital, hospital readmissions, or in-hospital mortality.

Conclusions

The Medicaid expansion was associated with a decrease in racial disparities in transfers and rates of PCI after AMI. We did not find an association between the Medicaid expansion and admission to a PCI hospital, readmissions, and in-hospital mortality. Additional factors outside of insurance coverage likely continue to contribute to disparities in outcomes after AMI. These findings are crucial for policy makers seeking to reduce racial disparities in access, treatment and outcomes in AMI.

Inequality Set in Concrete: Physical Resources Available for Care at Hospitals Serving People of Color and Other U.S. Hospitals

Racial inequities in health outcomes are widely acknowledged. This study seeks to determine whether hospitals serving people of color in the United States have lesser physical assets than other hospitals. With data on 4,476 Medicare-participating hospitals in the United States, we defined those in the top decile of the share of black and Hispanic Medicare inpatients as “black-serving” and “Hispanic-serving,” respectively. Using 2017 Medicare cost reports and American Hospital Association data, we compared the capital assets (value of land, buildings, and equipment), as well as the availability of capital-intensive services at these and other hospitals, adjusted for other hospital characteristics. Hospitals serving people of color had lower capital assets: for example, US$5,197/patient-day (all dollar amounts in U.S. dollars) at black-serving hospitals, $5,763 at Hispanic-serving hospitals, and $8,325 at other hospitals ( P < .0001 for both comparisons). New asset purchases between 2013 and 2017 averaged $1,242, $1,738, and $3,092/patient-day at black-serving, Hispanic-serving, and other hospitals, respectively ( P < .0001). In adjusted models, hospitals serving people of color had lower capital assets (−$215,121/bed, P < .0001) and recent purchases (−$83,608/bed, P < .0001). They were also less likely to offer 19 of 27 specific capital-intensive services. Our results show that hospitals that serve people of color are substantially poorer in assets than other hospitals and suggest that equalizing investments in hospital facilities in the United States might attenuate racial inequities in care.

Emergency Department Closures And Openings: Spillover Effects On Patient Outcomes In Bystander Hospitals

High-occupancy hospitals may be sensitive to neighboring emergency department (ED) closures and openings, as they already operate at or near capacity. We conducted a retrospective analysis using data for the period 2001-13 to examine outcomes of and treatment received by patients with acute myocardial infarction at so-called bystander EDs that had been exposed to nearby ED closures or openings. We used changes in driving time between an ED and the next-closest one as a proxy for a closure or opening: If driving time increased, for instance, it meant that a nearby ED had closed. When a high-occupancy ED was exposed to a closure that resulted in increased driving time of thirty minutes or more to the next-closest ED, one-year mortality and thirty-day readmission rates increased by 2.39 and 2.00 percentage points, respectively, while the likelihood of receiving percutaneous coronary intervention (PCI) declined by 2.06 percentage points. Exposure to ED openings that resulted in decreased driving times of thirty minutes or more was associated with reductions in thirty-day mortality at bystander hospitals and an increased likelihood of receiving PCI. Our findings suggest that limited resources at high-occupancy bystander hospitals make them sensitive to changes in the availability of emergency care in neighboring communities.

Effects of Medicaid expansion on access, treatment and outcomes for patients with acute myocardial infarction

INTRODUCTION

Uninsured patients have decreased access to care, lower rates of percutaneous coronary intervention (PCI), and worse outcomes after acute myocardial infarction (AMI). The aim of this study was to determine whether expanding insurance coverage through the Affordable Care Act's expansion of Medicaid eligibility affected access to PCI hospitals, rates of PCI, 30-day readmissions, and in-hospital mortality after AMI.

METHODS

Quasi-experimental, difference-in-differences analysis of Medicaid and uninsured patients with acute myocardial infarction in California, which expanded Medicaid through the Affordable Care Act, and Florida, which did not, from 2010-2015. This study accounts for the early expansion of Medicaid in certain California counties that began as early as July 2011. Main outcomes included rates of admission to PCI hospitals, rates of transfer for patients who initially presented to non-PCI hospitals, rates of PCI, rates of early PCI defined as within 48 hours of hospital admission, in-hospital mortality, and 30-day readmission.

RESULTS

55,991 hospital admissions between 2010-2015 met inclusion criteria. Of these, 32,540 were in California, which expanded Medicaid, and 23,451 were in Florida, which did not. 30-day readmission rates after AMI decreased by an absolute difference of 1.22 percentage points after the Medicaid expansion (95% CI -2.14 to -0.30, P < 0.01). This represented a relative decrease in readmission rates of 9.5% after AMI. No relationship between the Medicaid expansion and admission to PCI hospitals, transfer to PCI hospitals, rates of PCI, rates of early PCI, or in-hospital mortality were observed.

CONCLUSIONS

Hospital readmissions decreased by 9.5% after the Affordable Care Act expanded Medicaid eligibility, although there was no association found between Medicaid expansion and access to PCI hospitals or treatment with PCI. Better understanding the ways that Medicaid expansion might affect care for vulnerable populations with AMI is important for policymakers considering whether to expand Medicaid eligibility in their state.

Ambulance diversions following public hospital emergency department closures

OBJECTIVE

To examine whether hospitals are more likely to temporarily close their emergency departments (EDs) to ambulances (through ambulance diversions) if neighboring diverting hospitals are public vs private.

DATA SOURCES/STUDY SETTING

Ambulance diversion logs for California hospitals, discharge data, and hospital characteristics data from California's Office of Statewide Health Planning and Development and the American Hospital Association (2007).

STUDY DESIGN

We match public and private (nonprofit or for-profit) hospitals by distance and size. We use random-effects models examining diversion probability and timing of private hospitals following diversions by neighboring public vs matched private hospitals.

DATA COLLECTION/EXTRACTION METHODS

N/A.

PRINCIPAL FINDINGS

Hospitals are 3.6 percent more likely to declare diversions if neighboring diverting hospitals are public vs private (P < 0.001). Hospitals declaring diversions have lower ED occupancy (P < 0.001) after neighboring public (vs private) hospitals divert. Hospitals have 4.2 percent shorter diversions if neighboring diverting hospitals are public vs private (P < 0.001). When the neighboring hospital ends its diversion first, hospitals terminate diversions 4.2 percent sooner if the neighboring hospital is public vs private (P = 0.022).

CONCLUSIONS

Sample hospitals respond differently to diversions by neighboring public (vs private) hospitals, suggesting that these hospitals might be strategically declaring ambulance diversions to avoid treating low-paying patients served by public hospitals.

Another Look at the Persistent Moral Problem of Emergency Department Crowding

This article revisits the persistent problem of crowding in US hospital emergency departments (EDs). It begins with a brief review of origins of this problem, terms used to refer to ED crowding, proposed definitions and measures of crowding, and causal factors. The article then summarizes recent studies that document adverse moral consequences of ED crowding, including poorer patient outcomes; increased medical errors; compromises in patient physical privacy, confidentiality, and communication; and provider moral distress. It describes several organizational strategies implemented to relieve crowding and implications of ED crowding for individual practitioners. The article concludes that ED crowding remains a morally significant problem and calls on emergency physicians, ED and hospital leaders, emergency medicine professional associations, and policymakers to collaborate on solutions.

Statewide Method of Measuring Ambulance Patient Offload Times

OBJECTIVE

Ambulance patient offload time (APOT) also known colloquially as "Wall time" has been described in various jurisdictions but seems to be highly variable. Any attempt to improve APOT requires the use of common definitions and standard methodology to measure the extent of the problem.

METHODS

An Ambulance Offload Delay Task Force in California developed a set of standard definitions and methodology to measure APOT for transported 9-1-1 patients. It is defined as the time "interval between the arrival of an ambulance at an emergency department and the time that the patient is transferred to an ED gurney, bed, chair or other acceptable location and the ED assumes responsibility for care of the patient." Local EMS agencies voluntarily reported data according to the standard methodology to the California EMS Authority (State agency).

RESULTS

Data were reported for 9-1-1 transports during 2017 from 9 of 33 local EMS Agencies in California that comprise 37 percent of the state population. These represent 830,637 ambulance transports to 126 hospitals. APOT shows significant variation by EMS agency with half of the agencies demonstrating significant delays. Offload times vary markedly by hospital as well as by region. Three-fourths of hospitals detained EMS crews more than one hour, 40% more than two hours, and one-third delayed EMS return to service by more than three hours.

CONCLUSION

This first step to address offload delays in California consists of standardized definitions for data collection to address the significant variability inherent in obtaining data from 33 local agencies, hundreds of EMS provider agencies, and 320 acute care hospital Emergency Departments that receive 9-1-1 ambulance transports. The first year of standardized data collection of ambulance patient offload times revealed significant ambulance patient offload time delays that are not distributed uniformly, resulting in a substantial financial burden for some EMS providers in California.

Closure simulation for reduction of emergency patient diversion: a discrete agent-based simulation approach to minimizing ambulance diversion

Background

The city of Munich uses web-based information system IVENA to promote exchange of information regarding hospital offerings and closures between the integrated dispatch center and hospitals to support coordination of the emergency medical services. Hospital crowding resulting in closures and thus prolonged transportation time poses a major problem. An innovative discrete agent model simulates the effects of novel policies to reduce closure times and avoid crowding.

Methods

For this analysis, between 2013 and 2017, IVENA data consisting of injury/disease, condition, age, estimated arrival time and assigned hospital or hospital-closure statistics as well as underlying reasons were examined. Two simulation experiments with three policy variations are performed to gain insights on the influence of diversion policies onto the outcome variables.

Results

A total of 530,000+ patients were assigned via the IVENA system and 200,000+ closures were requested during this time period. Some hospital units request a closure on more than 50% of days. The majority of hospital closures are not triggered by the absolute number of patient arrivals, but by a sudden increase within a short time period. Four of the simulations yielded a specific potential for shortening of overall closure time in comparison to the current status quo.

Conclusion

Effective solutions against crowding require common policies to limit closure status periods based on quantitative thresholds. A new policy in combination with a quantitative arrival sensor system may reduce closing hours and optimize patient flow.