Ambulance diversions following public hospital emergency department closures

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.

Association of emergency department crowding with inpatient outcomes

OBJECTIVE

To examine the association of higher emergency department (ED) census with inpatient outcomes on the day of discharge (inpatient length of stay, in-hospital mortality, ED revisits, and readmissions).

DATA SOURCES AND STUDY SETTING

All-payer ED and inpatient discharge data and hospital characteristics data from all non-federal, general, and acute care hospitals in the state of California from October 1, 2015 to December 31, 2017.

STUDY DESIGN

In retrospective data analysis, we examined whether ED census was associated with inpatient outcomes for all inpatients, including those not admitted through the ED. The main predictor variable was ED census on day of discharge, categorized based on hospital year and day of week. Separate linear regression models with robust SEs and hospital fixed effects examined the association of ED census on inpatient outcomes (length of stay, 3-day ED revisit, 30-day all-cause readmission, in-hospital mortality), controlling for patient and visit-level factors. We stratified analyses by whether admission was elective or unscheduled.

EXTRACTION METHODS

Inpatient discharges in non-federal, general medical hospitals with EDs.

PRINCIPAL FINDINGS

We examined 5,784,253 discharges. The adjusted model showed that, compared to when the ED was below the median, higher ED census on the day of discharge was associated with longer inpatient length of stay, lower readmissions, and higher in-hospital mortality (90th percentile for length of stay: +0.8% [95% confidence interval, CI: +0.6% to +1.1%]; readmissions: -0.59 percentage points [or -5.6%] [95% CI: -0.0071 to -0.0048]; mortality: +0.14 percentage points [or +5.4%] [95% CI: +0.0009 to +0.0018]). [Correction added on 18 November 2022, after first online publication: '[odds rato, OR -5.6%]' and '[OR +5.4%]' of the preceding sentence have been corrected to '[or -5.6%]' and '[or +5.4%]', respectively, in this version.] Results for length of stay were primarily driven by patients with elective admissions, while results for readmissions and in-hospital mortality were primarily driven by patients with unscheduled admissions.

CONCLUSIONS

This study suggests that ED crowding may affect inpatients throughout the hospital, even patients who are already admitted to the hospital.

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.

Title: advancing urban health equity in the United States in an age of health care gentrification: a framework and research agenda

Background

Access to health care has traditionally been conceptualized as a function of patient socio-demographic characteristics (i.e., age, race/ethnicity, education, health insurance status, etc.) and/or the system itself (i.e., payment structures, facility locations, etc.). However, these frameworks typically do not take into account the broader, dynamic context in which individuals live and in which health care systems function.

Purpose

The growth in market-driven health care in the U.S. alongside policies aimed at improving health care delivery and quality have spurred health system mergers and consolidations, a shift toward outpatient care, an increase in for-profit care, and the closure of less profitable facilities. These shifts in the type, location and delivery of health care services may provide increased access for some urban residents while excluding others, a phenomenon we term “health care gentrification.“ In this commentary, we frame access to health care in the United States in the context of neighborhood gentrification and a concurrent process of changes to the health care system itself.

Conclusions

We describe the concept of health care gentrification, and the complex ways in which both neighborhood gentrification and health care gentrification may lead to inequitable access to health care. We then present a framework for understanding health care gentrification as a function of dynamic and multi-level systems, and propose ways to build on existing models of health care access and social determinants of health to more effectively measure and address this phenomenon. Finally, we describe potential strategies applied researchers might investigate that could prevent or remediate the effects of health care gentrification in the United States.

Evaluation of the American Hospital Association Annual Survey for health services research in emergency medicine

Objectives

Emergency department (ED) data are often used to address questions about access to and quality of emergency care. Our objective was to compare one of the most commonly used data sources for national ED information, the American Hospital Association (AHA) Annual Survey, with a criterion database: the National Emergency Department Inventory (NEDI)–USA data set.

Methods

We compared the 2015 and 2016 AHA surveys to the following 3 criterion standards: (1) the 2015 and 2016 NEDI‐USA databases, which have information about all US EDs, including merged data from (2) Council of Teaching Hospitals (COTH) and (3) the Critical Access Hospital (CAH) program. We present descriptive results about the number of EDs in each data set; total and median visit volumes; locations in rural areas; and COTH, CAH, and freestanding ED (FSED) status.

Results

The AHA survey identified 3893 US EDs in 2015. These EDs had a total annual visit volume of 129,197,493 visits, with a median of 22,772 visits (interquartile range, 8311–47,938). Compared with the NEDI‐USA, the AHA included 1433 fewer EDs (−27%; 95% confidence interval [CI], −28% to −26%) and 23,615,163 (−15%) fewer visits. Specifically, AHA was missing 245 (−22%; 95% CI, −24% to −19%) of those located in rural areas, 268 (−20%; 95% CI, −22% to −18%) in a CAH, and 240 (−47%; 95% CI, −51% to −42%) FSEDs. We saw similar results using 2016 data.

Conclusions

Although several aggregated results were similar between the compared data sources, the AHA data set excluded many US EDs, including many rural EDs and FSEDs. Consequently, the AHA underreported total ED visits by 15%. We encourage data users to be cautious when interpreting results from any 1 ED data source, including the AHA.

Universal SARS-CoV-2 Testing of Emergency Department Admissions Increases Emergency Department Length of Stay

Study objective

Our institution experienced a change in SARS-CoV-2 testing policy as well as substantial changes in local COVID-19 prevalence, allowing for a unique examination of the relationship between SARS-CoV-2 testing and emergency department (ED) length of stay.

Methods

This was an observational interrupted time series of all patients admitted to an academic health system between March 15, 2020, and September 30, 2020. Given testing limitations from March 15 to April 24, all patients receiving SARS-CoV-2 tests were symptomatic. On April 24, testing was expanded to all ED admissions. The primary and secondary outcomes were ED length of stay and number needed to test to obtain a positive, respectively.

Results

A total of 70,856 patients were cared for in the EDs during the 7-month period. The testing change increased admission length of stay by 1.89 hours (95% confidence interval 1.39 to 2.38). The number needed to test was 2.5 patients and was highest yield on April 1, 2020, when the state positivity rate was 39.7%; however, the number needed to test exceeded 170 patients by Sept 1, 2020, at which point the state positivity rate was 0.5%.

Conclusion

Although universal SARS-CoV-2 testing of ED admissions may meaningfully support mitigation and containment efforts, the clinical cost of testing all admissions amid low community positivity is notable. In our system, universal ED SARS-CoV-2 testing was associated with a 24% increase in admission length of stay alongside the detection of only 1 positive case every other day. Given the known harms and risks of ED boarding and crowding, solutions must be developed to support regular operational flow while balancing infection prevention needs.

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.