122 research outputs found

    Rural-Urban Disparities in Emergency Department Intimate Partner Violence Resources

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    Objective: Little is known about availability of resources for managing intimate partner violence (IPV) at rural hospitals. We assessed differences in availability of resources for IPV screening and management between rural and urban emergency departments (EDs) in Oregon. Methods: We conducted a standardized telephone interview of Oregon ED directors and nurse managers on six IPV-related resources: official screening policies, standardized screening tools, public displays regarding IPV, on-site advocacy, intervention checklists and regular clinician education. We used chi-square analysis to test differences in reported resource availability between urban and rural EDs. Results: Of 57 Oregon EDs, 55 (96%) completed the survey. A smaller proportion of rural EDs, compared to urban EDs, reported official screening policies (74% vs. 100%, p=0.01), standardized screening instruments (21% vs. 55%, p=0.01), clinician education (38% vs. 70%, p=0.02) or on-site violence advocacy (44% vs. 95%, p<0.001). Twenty-seven percent of rural EDs had none or one of the studied resources, 50% had two or three, and 24% had four or more (vs. 0%, 35%, and 65% in urban EDs, p=0.003). Small, remote rural hospitals had fewer resources than larger, less remote rural hospitals or urban hospitals. Conclusion: Rural EDs have fewer resources for addressing IPV. Further work is needed to identify specific barriers to obtaining resources for IPV management that can be used in all hospital settings. [West J Emerg Med. 2011;12(2):178-183.

    The Association between Emergency Department Resources and Diagnosis of Intimate Partner Violence

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    Objective: There is little information about which intimate partner violence (IPV) policies and services assist in the identification of IPV in the emergency department (ED). The objective of this study was to examine the association between a variety of resources and documented IPV diagnoses. Methods: Using billing data assembled from 21 Oregon EDs from 2001 to 2005, we identified patients assigned a discharge diagnosis of IPV. We then surveyed ED directors and nurse managers to gain information about IPV-related policies and services offered by participating hospitals. We combined billing data, survey results and hospital-level variables. Multivariate analysis assessed the likelihood of receiving a diagnosis of IPV depending on the policies and services available. Results: In 754,597 adult female ED visits, IPV was diagnosed 1,929 times. Mandatory IPV screening and victim advocates were the most commonly available IPV resources. The diagnosis of IPV was independently associated with the use of a standardized intervention checklist (OR 1.71, 95% CI 1.04-2.82). Public displays regarding IPV were negatively associated with IPV diagnosis (OR 0.56, 95% CI 0.35-0.88). Conclusions: IPV remains a rare documented diagnosis. Most common hospital-level resources did not demonstrate an association with IPV diagnoses; however, a standardized intervention checklist may play a role in clinicians\u27 likelihood diagnosing IPV

    Mechanism of injury and special considerations as predictive of serious injury: A systematic review.

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    Objectives: The Centers for Disease Control and Prevention\u27s field triage guidelines (FTG) are routinely used by emergency medical services personnel for triaging injured patients. The most recent (2011) FTG contains physiologic, anatomic, mechanism, and special consideration steps. Our objective was to systematically review the criteria in the mechanism and special consideration steps that might be predictive of serious injury or need for a trauma center. Methods: We conducted a systematic review of the predictive utility of mechanism and special consideration criteria for predicting serious injury. A research librarian searched in Ovid Medline, EMBASE, and the Cochrane databases for studies published between January 2011 and February 2021. Eligible studies were identified using a priori inclusion and exclusion criteria. Studies were excluded if they lacked an outcome for serious injury, such as measures of resource use, injury severity scores, mortality, or composite measures using a combination of outcomes. Given the heterogeneity in populations, measures, and outcomes, results were synthesized qualitatively focusing on positive likelihood ratios (LR+) whenever these could be calculated from presented data or adjusted odds ratios (aOR

    Unconditional care in academic emergency departments

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    Recent news stories have explicitly stated that patients with symptoms of COVID-19 were "turned away" from emergency departments. This commentary addresses these serious allegations, with an attempt to provide the perspective of academic emergency departments (EDs) around the Nation. The overarching point we wish to make is that academic EDs never deny emergency care to any person

    Emergency Department Pediatric Readiness Among US Trauma Centers: A Machine Learning Analysis of Components Associated With Survival.

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    OBJECTIVE: We used machine learning to identify the highest impact components of emergency department (ED) pediatric readiness for predicting in-hospital survival among children cared for in US trauma centers. BACKGROUND: ED pediatric readiness is associated with improved short-term and long-term survival among injured children and part of the national verification criteria for US trauma centers. However, the components of ED pediatric readiness most predictive of survival are unknown. METHODS: This was a retrospective cohort study of injured children below 18 years treated in 458 trauma centers from January 1, 2012, through December 31, 2017, matched to the 2013 National ED Pediatric Readiness Assessment and the American Hospital Association survey. We used machine learning to analyze 265 potential predictors of survival, including 152 ED readiness variables, 29 patient variables, and 84 ED-level and hospital-level variables. The primary outcome was in-hospital survival. RESULTS: There were 274,756 injured children, including 4585 (1.7%) who died. Nine ED pediatric readiness components were associated with the greatest increase in survival: policy for mental health care (+8.8% change in survival), policy for patient assessment (+7.5%), specific respiratory equipment (+7.2%), policy for reduced-dose radiation imaging (+7.0%), physician competency evaluations (+4.9%), recording weight in kilograms (+3.2%), life support courses for nursing (+1.0%-2.5%), and policy on pediatric triage (+2.5%). There was a 268% improvement in survival when the 5 highest impact components were present. CONCLUSIONS: ED pediatric readiness components related to specific policies, personnel, and equipment were the strongest predictors of pediatric survival and worked synergistically when combined

    Pretest probability assessment derived from attribute matching

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    BACKGROUND: Pretest probability (PTP) assessment plays a central role in diagnosis. This report compares a novel attribute-matching method to generate a PTP for acute coronary syndrome (ACS). We compare the new method with a validated logistic regression equation (LRE). METHODS: Eight clinical variables (attributes) were chosen by classification and regression tree analysis of a prospectively collected reference database of 14,796 emergency department (ED) patients evaluated for possible ACS. For attribute matching, a computer program identifies patients within the database who have the exact profile defined by clinician input of the eight attributes. The novel method was compared with the LRE for ability to produce PTP estimation <2% in a validation set of 8,120 patients evaluated for possible ACS and did not have ST segment elevation on ECG. 1,061 patients were excluded prior to validation analysis because of ST-segment elevation (713), missing data (77) or being lost to follow-up (271). RESULTS: In the validation set, attribute matching produced 267 unique PTP estimates [median PTP value 6%, 1(st)–3(rd )quartile 1–10%] compared with the LRE, which produced 96 unique PTP estimates [median 24%, 1(st)–3(rd )quartile 10–30%]. The areas under the receiver operating characteristic curves were 0.74 (95% CI 0.65 to 0.82) for the attribute matching curve and 0.68 (95% CI 0.62 to 0.77) for LRE. The attribute matching system categorized 1,670 (24%, 95% CI = 23–25%) patients as having a PTP < 2.0%; 28 developed ACS (1.7% 95% CI = 1.1–2.4%). The LRE categorized 244 (4%, 95% CI = 3–4%) with PTP < 2.0%; four developed ACS (1.6%, 95% CI = 0.4–4.1%). CONCLUSION: Attribute matching estimated a very low PTP for ACS in a significantly larger proportion of ED patients compared with a validated LRE

    THE AFFORDABLE CARE ACT AND AMBULANCE RESPONSE TIMES

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    This study contributes to the literature on supply-side adjustments to insurance expansions by examining the effect of the Affordable Care Act (ACA) on ambulance response times. Exploiting temporal and geographic variation in the implementation of the ACA as well as pre-treatment differences in uninsured rates, we estimate that the expansions of private and Medicaid coverage under the ACA combined to slow ambulance response times by an average of 19%. We conclude that, through extending coverage to individuals who, in its absence, would not have availed themselves of emergency medical services, the ACA added strain to emergency response systems
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