Introduction: Understanding the cause of patients’ symptoms often requires identifying a pathological diagnosis. A single-center study found that many patients discharged from the emergency department (ED) do not receive a pathological diagnosis. We analyzed 17 years of data from the National Hospital Ambulatory Medical Care Survey (NHAMCS) to identify the proportion of patients who received a pathological diagnosis at ED discharge. We hypothesized that many patients do not receive a pathological diagnosis, and that the proportion of pathological diagnoses increased between 1993 and 2009.

Methods: Using the NHAMCS data from 1993-2009, we analyzed visits of patients age ≥18 years, discharged from the ED, who had presented with the three most common chief complaints: chest pain, abdominal pain, and headache. Discharge diagnoses were coded as symptomatic versus pathological based on a pre-defined coding system. We compared weighted annual proportions of pathological discharge diagnoses with 95% CIs and used logistic regression to test for trend. 

Results: Among 299,919 sampled visits, 44,742 met inclusion criteria, allowing us to estimate that there were 164 million adult ED visits presenting with the three chief complaints and then discharged home. Among these visits, the proportions with pathological discharge diagnosis were 55%, 71%, and 70% for chest pain, abdominal pain, and headache, respectively. The total proportion of those with a pathological discharge diagnosis decreased between 1993 and 2009, from 72% (95% CI, 69-75%) to 63% (95% CI, 59-66%). In the multivariable logistic regression model, those more likely to receive pathological diagnoses were females, African-American as compared to Caucasian, and self-pay patients. Those more likely to receive a symptomatic diagnosis were patients aged 30-79 years, with visits to EDs in the South or West regions, and seen by a physician in the ED.

Conclusion: In this analysis of a nationally-representative database of ED visits, many patients were discharged from the ED without a pathological diagnosis that explained the likely cause of their symptoms. Despite advances in diagnostic testing, the proportion of pathological discharge diagnoses decreased. Future studies should investigate reasons for not providing a pathological diagnosis and how this may affect clinical outcomes. [West J Emerg Med. 2015;16(1):–0.]

Objective: Use of bedside emergency department (ED) ultrasound has become increasingly important for the clinical practice of emergency medicine (EM). We sought to evaluate differences in the availability of immediate bedside ultrasound based on basic ED characteristics and physician staffing.

Methods: We surveyed ED directors in all 351 EDs in Colorado, Georgia, Massachusetts, and Oregon between January and April 2009. We assessed access to bedside ED ultrasound by the question: “Is bedside ultrasound available immediately in the ED?” ED characteristics included location, visit volume, admission rate, percent uninsured, total emergency physician full-time equivalents and proportion of EM board-certified (BC) or EM board-eligible (BE) physicians. Data analysis used chi-square tests and multivariable logistical regression to compare differences in access to bedside ED ultrasound by ED characteristics and staffing.

Results: We received complete responses from 298 (85%) EDs. Immediate access to bedside ultrasound was available in 175 (59%) EDs. ED characteristics associated with access to bedside ultrasound were: location (39% for rural vs. 71% for urban, P20%] rates, P<0.001); and EM BC/BE physicians (26% for EDs with a low percentage [0-20%] vs.74% for EDs with a high percentage [≥80%], P<0.001).

Conclusion: U.S. EDs differ significantly in their access to immediate bedside ultrasound. Smaller, rural EDs and those staffed by fewer EM BC/BE physicians more frequently lacked access to immediate bedside ultrasound in the ED. [West J Emerg Med. 2011;12(1):96-99.]

Introduction: In the United States, more chronic and preventive healthcare is being delivered in the emergency department (ED) setting. Understanding the availability of preventive health services in the ED setting is crucial. Our goal was to understand the availability of a subset of preventive health services in US EDs and explore how that has changed over time.

Methods: In 2022–2023, using the National Emergency Department Inventory (NEDI)-USA, we surveyed a random 20% (1,064) sampling of all 5,613 US EDs. We asked directors of these EDs about the availability of and preference for 12 preventive health services, social worker availability, self-reported percentage of uninsured ED patients, and measures of ED crowding. We also asked about perceptions of barriers to implementing preventive health services in the ED. We used unadjusted and multivariable logistic regression models to compare service frequency in 2022–2023 to prior findings from 2008–2009 that represented a 5.7% random sampling of all EDs.

Results: Among 302 responders to the 2022–2023 survey (5.4% random sampling, 28.4% response rate), 94% reported offering at least one preventive health service, with a median of five services. The most common service offered was intimate partner violence screening (83%), while the least common was routine HIV screening (19%). Seven services (eg, intimate partner violence, alcohol risk, and smoking cessation screening) had a higher odds of being offered in 2022–2023 than in 2008–2009; findings were unchanged in sensitivity analyses. A small proportion of directors opposed offering preventive health services. However, many expressed concerns that preventive health services in the ED would lead to longer lengths of stay (56%), increased costs to their ED (58%), a diversion of staff time from providing acute care (50%), or that their patients would not have access to adequate follow-up (49%).

Conclusion: Nearly all EDs offer at least one preventive health service. Many offer multiple services; rates were higher than those identified in 2008–2009, in both unadjusted and multivariable models. Although limited by the response rate, this work provides the most recent and comprehensive snapshot of the type and frequency of a subset of preventive health services currently offered in US EDs.

Introduction: Although bronchiolitis is a common reason for infant hospitalization, significant heterogeneity persists in its management. The American Academy of Pediatrics currently recommends that inhaled albuterol not be used in routine care of children with bronchiolitis. Our objective was to identify factors associated with pre-admission (e.g., emergency department or primary care) use of albuterol among infants hospitalized for bronchiolitis.

Methods: We analyzed data from a 17-center observational study of 1,016 infants (age <1 year) hospitalized with bronchiolitis between 2011-2014. Pre-admission albuterol use was ascertained by chart review, and data were available for 1,008 (99%) infants. We used multivariable logistic regression to identify infant characteristics independently associated with pre-admission albuterol use.

Results: Half of the infants (n=508) received at least one albuterol treatment before admission. Across the 17 hospitals, pre-admission albuterol use ranged from 23-84%. In adjusted analysis, independent predictors of albuterol use were the following: age ≥2 months (age 2.0-5.9 months [odds ratio (OR) 2.09, 95% confidence interval (CI) {1.45-3.01}] and age 6.0-11.9 months [OR 2.89, 95% CI {1.99-4.19}]); prior use of a bronchodilator (OR 1.89, 95% CI [1.24-2.90]); and presence of wheezing documented in pre-admission chart (OR 3.94, 95% CI [2.61-5.93]). By contrast, albuterol use was less likely among those with ≥7 days since the start of breathing problem (OR 0.66, 95% CI [0.44-1.00]) and parent-reported fever (OR 0.75, 95% CI [0.58-0.96]).

Conclusion: Variation in pre-admission albuterol use suggests that local practice had a strong influence on use, but that patient characteristics also influenced the decision. While we agree with current guidelines in recommending against albuterol for all infants with bronchiolitis, our understanding of possible subgroups of responders may improve through investigation of infants with the identified characteristics.

Introduction

In June 2016, the American College of Emergency Physicians (ACEP) Emergency Quality Network began its Reduce Avoidable Imaging Initiative, designed to “reduce testing and imaging with low risk patients through the implementation of Choosing Wisely recommendations”. However, it is unknown whether New England Emergency Departments (EDs) have already implemented evidence-based interventions to improve adherence to ACEP Choosing Wisely recommendations related to imaging after their initial release in 2013.  Our objective was to determine this, as well as whether provider-specific audit-and-feedback for imaging had been implemented in these EDs.

Methods

This survey study was exempt from Institutional Review Board review. In 2015, we mailed surveys to 195 hospital-affiliated EDs in all six New England states to determine whether they had implemented Choosing Wisely-focused interventions in 2014. Initial mailings included cover letters denoting the endorsement of each state’s ACEP chapter, and were followed-up twice with repeat mailings to non-responders. Data analysis included descriptive statistics and a comparison of state differences using Fisher’s exact test.

Results

A total of 169/195 (87%) of New England EDs responded, with all individual state response rates >80%. Overall, 101 (60%) of responding EDs had implemented an intervention for at least one Choosing Wisely imaging scenario; 57% reported implementing a specific guideline/policy/clinical pathway, 40% had implemented provider-specific audit-and-feedback, and 28% reported implementing a computerized decision support system. The most common interventions were for chest CT in patients at low-risk of pulmonary embolism (47% of EDs) and head CT in patients with minor trauma (45% of EDs). In addition, 40% of EDs had implemented provider-specific audit-and-feedback, without significant interstate variation (range: 29-55%).

Conclusion

One year after release of the ACEP Choosing Wisely recommendations, most New England EDs had a guideline/policy/clinical pathway related to at least one of the recommendations. However, only a minority were using provider-specific audit-and-feedback or computerized decision support. Few EDs have embraced the opportunity to implement the multiple evidence-based interventions likely to advance the national goals of improving patient-centered and resource-efficient care.

Introduction: Telemedicine connects emergency departments (ED) with resources necessaryfor patient care; its use has not been characterized nationally, or even regionally. Our primaryobjective was to describe the prevalence of telemedicine use in New England EDs and theclinical applications of use. Secondarily, we aimed to determine if telemedicine use wasassociated with consultant availability and to identify ED characteristics associated withtelemedicine use.

Methods: We analyzed data from the National Emergency Department Inventory-New Englandsurvey, which assessed basic ED characteristics in 2014. The survey queried directors of everyED (n=195) in the six New England states (excluding federal hospitals and college infirmaries).Descriptive statistics characterized ED telemedicine use; multivariable logistic regressionidentified independent predictors of use.

Results: Of the 169 responding EDs (87% response rate), 82 (49%) reported usingtelemedicine. Telemedicine EDs were more likely to be rural (18% of users vs. 7% of nonusers,p=0.03); less likely to be academic (1% of users vs. 11% of non-users, p=0.01); andless likely to have 24/7 access to neurology (p<0.001), neurosurgery (p<0.001), orthopedics(p=0.01), plastic surgery (p=0.01), psychiatry (p<0.001), and hand surgery (p<0.001)consultants. Neuro/stroke (68%), pediatrics (11%), psychiatry (11%), and trauma (10%) were themost commonly reported applications. On multivariable analysis, telemedicine was more likely inrural EDs (odds ratio [OR] 4.39, 95% confidence interval [CI] 1. 30-14.86), and less likely in EDswith 24/7 neurologist availability (OR 0.21, 95% CI [0.09-0.49] ), and annual volume <20,000 (OR0.24, 95% CI [0.08-0.68]).

Conclusion: Telemedicine is commonly used in New England EDs. In 2014, use was morecommon among rural EDs and EDs with limited neurology consultant availability. In contrast,telemedicine use was less common among very low-volume EDs.

Introduction: The American Hospital Association (AHA) has hospital-level data, while the Centers for Medicare & Medicaid Services (CMS) has patient-level data. Merging these with other distinct databases would permit analyses of hospital-based specialties, units, or departments, and patient outcomes. One distinct database is the National Emergency Department Inventory (NEDI), which contains information about all EDs in the United States. However, a challenge with merging these databases is that NEDI lists all US EDs individually, while the AHA and CMS group some EDs by hospital network. Consolidating data for this merge may be preferential to excluding grouped EDs. Our objectives were to consolidate ED data to enable linkage with administrative datasets and to determine the effect of excluding grouped EDs on ED-level summary results.

Methods: Using the 2014 NEDI-USA database, we surveyed all New England EDs. We individually matched NEDI EDs with corresponding EDs in the AHA and CMS. A “group match” was assigned when more than one NEDI ED was matched to a single AHA or CMS facility identification number. Within each group, we consolidated individual ED data to create a single observation based on sums or weighted averages of responses as appropriate.

Results: Of the 195 EDs in New England, 169 (87%) completed the NEDI survey. Among these, 130 (77%) EDs were individually listed in AHA and CMS, while 39 were part of groups consisting of 2-3 EDs but represented by one facility ID. Compared to the individually listed EDs, the 39 EDs included in a “group match” had a larger number of annual visits and beds, were more likely to be freestanding, and were less likely to be rural (all P<0.05). Two grouped EDs were excluded because the listed ED did not respond to the NEDI survey; the remaining 37 EDs were consolidated into 19 observations. Thus, the consolidated dataset contained 149 observations representing 171 EDs; this consolidated dataset yielded summary results that were similar to those of the 169 responding EDs.

Conclusion: Excluding grouped EDs would have resulted in a non-representative dataset. The original vs consolidated NEDI datasets yielded similar results and enabled linkage with large administrative datasets. This approach presents a novel opportunity to use characteristics of hospital-based specialties, units, and departments in studies of patient-level outcomes, to advance health services research.

Introduction: Social risks, or adverse social conditions associated with poor health, are prevalent in emergency department (ED) patients, but little is known about how the prevalence of social risk compares to a patient’s reported social need, which incorporates patient preference for intervention. The goal of this study was to describe the relationship between social risk and social need, and identify factors associated with differential responses to social risk and social need questions.

Methods: We conducted a cross-sectional study with 48 hours of time-shift sampling in a large urban ED. Consenting patients completed a demographic questionnaire and assessments of social risk and social need. We applied descriptive statistics to the prevalence of social risk and social need, and multivariable logistic regression to assess factors associated with social risk, social need, or both.

Results: Of the 269 participants, 100 (37%) reported social risk, 83 (31%) reported social need, and 169 (63%) reported neither social risk nor social need. Although social risk and social need were significantly associated (p < 0.01), they incompletely overlapped. Over 50% in each category screened positive in more than one domain (eg, housing instability, food insecurity). In multivariable models, those with higher education (adjusted odds ratio [aOR] 0.44 [95% confidence interval {CI}, 0.24-0.80]) and private insurance (aOR 0.50 [95% CI, 0.29-0.88]) were less likely to report social risk compared to those with lower education and state/public insurance, respectively. Spanish-speakers (aOR 4.07 [95% CI, 1.17-14.10]) and non-Hispanic Black patients (aOR 5.00 [95% CI, 1.91-13.12]) were more likely to report social need, while those with private insurance were less likely to report social need (private vs state/public: aOR 0.13 [95% CI, 0.07-0.26]).

Conclusion: Approximately one-third of patients in a large, urban ED screened positive for at least one social risk or social need, with over half in each category reporting risk/need across multiple domains. Different demographic variables were associated with social risk vs social need, suggesting that individuals with social risks differ from those with social needs, and that screening programs should consider including both assessments.