Nontrauma Hospitals Research Articles

Geography of the Underserved: The Contribution of Rural Non-Trauma Hospitals to Trauma Care.

To determine the proportion and characteristics of injured rural residents treated at urban trauma centers (TCs), urban non-trauma centers (NTCs), rural TCs, and rural NTCs. Timely treatment at a designated trauma center improves outcomes for patients with serious injuries, but rural residents have limited access to designated trauma centers. Rural non-trauma centers may constitute an underrecognized source of trauma care. We used the National Emergency Department Sample to conduct a retrospective, pooled cross-sectional study of ED visits among rural residents with injury severity score (ISS) ≥ 9 (indicating at least moderate injury). Hospitals were designated as a trauma (TC) or non-trauma center (NTC) and as rural or urban. We compared management, disposition, and outcomes among hospital types. Of 748,587 injured rural residents from 2016-2020, 384,113 (51.3%) were treated in rural NTCs, 232,845 (31.1%) in urban TCs, 116,493 (15.6%) in urban NTCs, and 15,137 (2.0%) in rural TCs. Injuries treated at rural NTCs were moderate in severity (ISS 9-15) in 76.6% of visits, severe (ISS 16-25) in 15.7%, and very severe (ISS > 25) in 1.1%. Urban TCs saw the highest proportion of very severe injuries (17.3%). Rural NTCs managed 77.5% of visits definitively, discharging 72.8%. They transferred 21.9% of patients. Length of stay was longest and hospital charges highest for patients treated in urban TCs, which also performed the most procedures. Rural NTCs had the shortest length of stay and lowest mean charges. Rural non-trauma centers provided initial care for more than half of injured rural residents, including 2 in 5 of those with the most severe injuries, and managed more than 3 in 4 definitively. These hospitals may be an under-recognized component of the US trauma system.

72103 - Undertriage of severely injured patients at one non-trauma center hospital in Stockholm

72103 - Undertriage of severely injured patients at one non-trauma center hospital in Stockholm

Implementation of the Modified Brain Injury Guidelines Might Be Feasible and Cost-Effective Even in a Nontrauma Hospital

The modified Brain Injury Guideline (mBIG) is a framework to stratify traumatic brain injury (TBI) patients based on clinical and radiographic factors in level 1 and 2 trauma centers. Approximately 75% of all US hospitals do not carry any trauma designation yet may also benefit from these guidelines. This is the first report of applying the mBIG protocol in a community hospital without any trauma designation. All adult patients with a TBI in a single center during the years 2020-2022 were retrospectively classified into mBIG categories. Primary outcomes included neurological deterioration, progression on head CT, and surgical intervention. Additional outcomes included hospital costs incurred by mBIG 1 and mBIG 2 groups. In the 116 included patients, 35 patients (30%) would have stratified into mBIG 1, 23 (20%) into mBIG 2, and 58 (50%) into mBIG 3. No patient in mBIG 1 had a decline in neurological exam, progression on head CT, or required neurosurgical intervention. Three patients in mBIG 2 had radiographic progression and one required surgical decompression. Two patients in mBIG 3 demonstrated a neurological decline and six had radiographic progression. 20/21 patients that received surgical intervention were stratified into mBIG 3. Implementation of the mBIG protocol could have reduced cost by over $250,000 over a two-year period. The mBIG protocol can safely stratify patients in a non-trauma hospital. Since non-trauma centers tend to see more minor TBI patients, implementation may have significant cost savings, reduce unnecessary hospital/ICU resources, and transfer to a tertiary institution.

(404) National Trends of Penile Fracture Encounters 2016-2019

Abstract Introduction Penile Fracture (PF) is an acute urological emergency resulting from the rupture of the tunica albuginea and one or both of the corpus cavernosa. Immediate surgical intervention is crucial in avoiding long-term complications, however the epidemiology and treatment patterns remain understudied, especially with the introduction of the 10th Revision of the International Classification of Diseases (ICD-10). Objective To evaluate national trends of PF encounters as well as predictive factors of inpatient admission from the emergency department (ED). Methods All patients admitted to the ED for PF between 2016-2019 were extracted from the NEDS using the ICD-10 Diagnosis Code S39.840 and its modifiers. Multivariable logistic regression was performed to identify predictors of this inpatient admission. Results Between 2016-2019, there were an estimated 7,091 weighted encounters related to PF in the US with an overall 13% increase in cases (Figure 1). About 20.8% (1,477) of these encounters led to inpatient admission. The average age of a patient presenting with PF was 41 years old. The majority of encounters took place in the South (44.12%) at non-trauma center rural hospitals (63.99%) and involved private insurance holders (44.42%). For those admitted to inpatient service, the average length of stay was 1.44 days, with a maximum of 26 days. The average total charge for patients discharged from the ED was $11,224 USD and those admitted were faced with charges averaging $33,474 USD. Predictors of inpatient admission included an Elixhauser Comorbidity Score > 1, encounters in the Northeast, Midwest, and Western states, and being covered by Medicaid (p < .05). Conclusions Penile fractures have seen a small increase in incidence from 2016-2019. Although inpatient admissions are less common, they carry significantly higher costs. Further studies of treatments and regional analysis may be warranted to decrease the amount of inpatient admissions. Disclosure No.

Implementation evaluation of tiered tele-triage pathways for burn center consultations and transfers.

Early transfer to specialized centers improves trauma and burn outcomes; however, overtriage can result in unnecessary burdens to patients, providers, and health systems. Our institution developed novel burn triage pathways in 2016 to improve resource allocation. We evaluated the implementation of these pathways, analyzing trends in adoption, resource optimization, and pathway reliability after implementation. Triage pathways consist of transfer nurses (RNs) triaging calls based on review of burn images and clinical history: green pathway for direct outpatient referral, blue pathway for discussion with the on-call provider, red pathway for confirmation of transfer as requested by referring provider, and black pathway for the rapid transfer of severe burns. We used the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework to evaluate implementation. These pathways affected all acute burn referrals to our center from January 2017 to December 2019 (reach). Outcomes of interest were pathway assignment over time (adoption), changes to burn provider call volume (effectiveness), and the concordance of pathway assignment with final disposition (implementation reliability). Transfer RNs triaged 5,272 burn referrals between 2017 and 2019. By January 2018, >98% of referrals were assigned a pathway. In 2018-2019, green pathway calls triaged by RNs reduced calls to burn providers by a mean of 40 (SD, 11) per month. Patients in green/blue pathways were less likely to be transferred, with >85% receiving only outpatient follow-up ( p < 0.001). Use of the lower acuity pathways increased over time, with a concordant decrease in use of the higher acuity pathways. Younger adults, patients referred from Level III to Level V trauma centers and nontrauma hospitals, and patients referred by APPs were less likely to be triaged to higher acuity pathways. Implementation of highly adopted, reliable triage pathways can optimize existing clinical resources by task-shifting triage of lower acuity burns to nursing teams. Prognostic and Epidemiological; Level III.

Domestic Violence-Related Ocular Injuries Among Adult Patients: Data from the Nationwide Emergency Department Sample, 2008–2017

ABSTRACT Purpose To investigate domestic violence (DV)-related ocular injuries among adult emergency department (ED) patients in the US. Methods This was a retrospective, cross-sectional study of patients with a diagnosis of DV and diagnosis of ocular injury in the Nationwide Emergency Department Sample (NEDS) from 2008–2017. We identified patient- and hospital-level variables associated with DV-related ocular injuries. We calculated annual incidence rates using US Census data. Adjusting for inflation using the Consumer Price Index, we calculated mean and total charges. Results From 2008–2017, there were 26,215 ED visits for ocular injuries related to DV with an average incidence of 1.09 per 100,000 adult population (female patients, 84.5%; mean age [SE], 34.3 [0.2]). DV-related ocular injuries were most prevalent among patients in the lowest income quartile (39.1%) and on Medicaid (37.4%). Most ED visits presented to metropolitan teaching (55.4%), non-trauma (46.7%), and south regional (30.5%) hospitals. The most common ocular injury was contusion of eye/adnexa (61.1%). The hospital admission rate was 5.2% with a mean hospital stay of 2.9 [0.2]. The inflation-adjusted mean cost for medical services was $38,540 [2,310.8] per encounter with an average increase of $2,116 per encounter, annually. The likelihood of hospital admission increased for patients aged ≥60 years old, on Medicare, and with open globes or facial/orbital fractures (all p < .05). Conclusion Contusion of the eye/adnexa was the most common ocular injury among patients with DV-related ED visits. To better facilitate referrals to social services, ophthalmologists should utilize DV screenings, especially towards women and patients of less privileged socioeconomic status.

Patients with breast cancer and the threat of septicemia.

e18622 Background: A very dangerous complication that can occur in breast cancer patients is septicemia. However, there are not many large scale studies that have demonstrated patient and hospital factors associated with higher risk of this complication in breast cancer patients. Methods: We utilized the 2006-2012 Nationwide Emergency Department Sample to identify breast cancer patients that presented to the emergency department (ED) with a primary diagnosis of septicemia. A multivariate logistic regression was used to identify characteristics that were significantly associated with a higher chance of septicemia. A p-value less than 0.05 was considered significant. Results: Between 2006 and 2012, 2,160,701 breast cancer patients presented to the ED. Out of these patients, 39,164 (1.8%) presented to the ED with a primary diagnosis of septicemia. Most patients were at least 80 years old (61.5%), female (98.9%), Medicare beneficiaries (73.8%), of the highest income quartile (28.6%), living in the South (34.3%), presented to non-trauma hospitals (51.5%), and presented to metropolitan non-teaching hospitals (46.0%). Factors associated with the highest risk of septicemia in breast cancer patients are the following: Medicaid patients (odds ratio (OR): 2.0, 95% Confidence Interval (CI): 1.6-2.6, p &lt; 0.001), Medicare patients (OR: 2.0, 95% CI: 1.6-2.5, p &lt; 0.001), private insurance patients (OR: 1.7, 95% CI: 1.4-2.1, p &lt; 0.001), living in the West (OR: 1.5, 95% CI: 1.3-1.7, p &lt; 0.001), living in the Northeast (OR: 1.3, 95% CI: 1.1-1.5, p &lt; 0.001), presenting to a metropolitan non-teaching hospital (OR: 1.2, 95% CI: 1.1-1.4, p = 0.03), and presenting to a metropolitan teaching hospital (OR: 1.3, 95% CI: 1.1-1.5, p = 0.003). Almost all breast cancer patients with septicemia were admitted (97.6%), discharged the same day (1.0%), or transferred to a short-term hospital (0.7%). Amongst patients that were admitted, most patients were discharged (34.4%), transferred to a skilled nursing facility or intermediate care facility (29.8%), or died (16.2%). Risk factors associated with increased risk of dying in septicemia patients are the following: living in the Northeast (OR: 1.4, 95% CI: 1.2-1.8, p = 0.001), presenting to a metropolitan teaching hospital (OR: 1.3, 95% CI: 1.0-1.7, p = 0.046), and living in the South (OR: 1.2, 95% CI: 1.0-1.5, p = 0.045). Conclusions: After correcting for patient and hospital characteristics, a patient’s insurance status, the hospital’s region, and the hospital’s teaching status are intimately related to a breast cancer patient's risk to develop septicemia. Furthermore, hospital region and teaching status are also associated with a breast cancer patient’s risk of dying from septicemia. This suggests that a patient’s access to resources is critical for their risk of developing cancer-related complications.

Elucidating the connection between pneumonia and melanoma: Risk factors and outcomes for patients with melanoma.

e21561 Background: Pneumonia is a common cause of morbidity and mortality in patients with melanoma and leads to many ED visits per year in the US. However, there is no national-level study that has assessed factors that increase risk for melanoma patients to present to the ED with a primary diagnosis of pneumonia. Methods: We utilized the 2006-2012 Nationwide Emergency Department Sample to identify melanoma patients that presented to the emergency department (ED) with a primary diagnosis of pneumonia. A multivariate logistic regression was used to identify characteristics that were significantly associated with a higher chance of pneumonia. A p-value less than 0.05 was considered significant. Results: Between 2006 and 2012, 239,956 melanoma patients presented to the ED. Amongst these patients, 3.1% presented to the ED with a primary diagnosis of pneumonia. The majority of patients were at least 80 years old (64.3%), male (61.5%), Medicare beneficiaries (73.1%), of the highest income quartile (28.7%), living in the South (35.7%), presented to non-trauma hospitals (53.1%), and presented to metropolitan non-teaching hospitals (44.9%). Factors associated with the highest risk of pneumonia in melanoma patients are the following: Medicaid patients (odds ratio (OR): 2.5, 95% Confidence Interval (CI): 1.4-4.4, p=0.003), Medicare patients (OR: 2.3, 95% CI: 1.4-3.0, p=0.002), private insurance patients (OR: 2.1, 95% CI: 1.3-3.5, p=0.005), non-metropolitan teaching hospitals (OR: 1.6, 95% CI: 1.3-1.9, p&lt;0.001), living in the Northeast (OR: 1.3, 95% CI: 1.3-3.5, p=0.005), being male (OR: 1.3, 95% CI: 1.1-1.4,p&lt;0.001) a high Charlson Comorbidity Index (OR: 1.3, 95% CI: 1.2-1.3, p&lt;0.001). The majority of patients were either admitted (86.4%) or discharged home the same day (11.1%). Amongst the patients that were admitted, most patients were discharged (59.0%), transferred to a skilled nursing facility or intermediate care facility (19.2%), or given home health care (15.8%). Only 4.0% of admitted patients died in the hospital. Conclusions: A melanoma patient’s risk for developing pneumonia is depending on insurance status, the region of their hospital, their biological sex, and the presence of comorbidities. Clinicians should be aware of these risk factors to minimize the risk of pneumonia occurring in this at-risk population.

Complicating breast cancer treatment: Reasons patients present to the ED.

e13668 Background: Breast cancer is a very common cancer that provides a significant amount of stress on patients’ lives. These patients can have many cancer-related complications, which lead them to present to the ED. However, few studies have identified common reasons for these patients to present to the ED and factors associated with high risk of admission. Methods: We utilized the 2006-2012 Nationwide Emergency Department Sample to identify the common primary diagnoses of breast cancer patients in the ED. A multivariate logistic regression was used to identify characteristics that were significantly associated with a higher chance of inpatient admission. A p-value less than 0.05 was considered significant. Results: Between 2006 and 2012, 2,160,701 breast cancer patients presented to the ED. Most patients were at least 80 years old (53.0%), female (99.1%), Medicare beneficiaries (64.4%), of the highest income quartile (26.2%), living in the South (36.8%), presented to non-trauma hospitals (52.7%), and presented to metropolitan non-teaching hospitals (44.8%). Most patients were admitted (53.1%). The most common primary diagnoses of breast cancer patients were chest pain (5.4%), urinary tract infection (3.3%), pneumonia (3.1%), secondary malignancy (3.0%), and cardiac arrhythmia (3.0%). The primary diagnoses associated with the highest risk of inpatient admission are the following: septicemia (odds ratio: 39.4, 95% confidence interval (CI): 33.8-45.9,p &lt; 0.001), femur fracture (OR:19.1, 95% CI: 16.6-22.0,p &lt; 0.001), secondary malignancy (OR:17.7, 95% CI: 16.2-19.4,p &lt; 0.001), acute cerebrovascular disease (OR:5.8, 95% CI:5.3-6.3,p &lt; 0.001), pneumonia (OR:4.9, 95% CI:4.7-5.2,p &lt; 0.001), and complication of previous surgical or medical therapy (OR:2.2, 95% CI:2.0-2.3,p &lt; 0.001). Primary diagnoses associated with a lower risk of admission are the following: contusion (OR:0.06, 95% CI:0.06-0.07,p &lt; 0.001), abdominal pain (OR:0.14, 95% CI:0.13-0.15,p &lt; 0.001), and connective tissue disorder (OR:0.17, 95% CI:0.16-0.19,p &lt; 0.001). Interestingly, patients that paid with Medicaid (OR:0.84, 95% CI:0.79-0.89,p &lt; 0.001) or private insurance (OR:0.89, 95% CI:0.86-0.93,p &lt; 0.001) were less likely to be admitted. Furthermore, uninsured patients were also less likely to be admitted (OR:0.52, 95% CI:0.48-0.57, p &lt; 0.001). Conclusions: Breast cancer patients frequently present to the ED for many reasons, with septicemia and femur being the most severe diagnoses. Physicians should keep these risk factors in mind to prevent these complications and reduce patient stress.

Association of patient age and insurance status with in-hospital mortality for patients with lung cancer.

e13669 Background: In 2022, the National Cancer Institute estimated that more than 240,000 individuals will be diagnosed with lung cancer. Furthermore, over 130,000 patients will die. To help minimize this death rate, it is important to identify death risk factors. Methods: We utilized the 2006-2012 Nationwide Emergency Department Sample to identify risk risk factors for death in lung cancer patients. A multivariate logistic regression was used to identify patient and hospital characteristics that were significantly associated with a higher chance of in-hospital death. The top 20 primary diagnoses of these patients were included in the analysis to take into account the reason to visit the ED. A p-value less than 0.05 was considered significant. Results: During this time period, 1,344,817 lung cancer patients presented to the emergency departments (ED) across the US. The majority of patients at least 70 years old (50.8%), male (51.1%), Medicare beneficiaries (67.5%), of the lowest income quartile (28.1%), living in the South (40.3%), presented to non-trauma hospitals (54.3%), and presented to metropolitan non-teaching hospitals (43.3%). Out of the 1,344,817 lung cancer patients that presented to the ED, 6.1% died in the hospital. The primary diagnoses associated with increased mortality are the following: respiratory failure (odds ratio (OR): 9.05, 95% confidence interval (CI): 8.47-9.67, p &lt; 0.001), septicemia (OR: 8.46, 95% CI: 7.98-8.97,p &lt; 0.001), acute cerebrovascular disease (OR: 3.04, 95% CI: 2.71-3.35,p &lt; 0.001), secondary malignancy (OR: 2.00, 95% CI: 1.88-2.13,p &lt; 0.001), pulmonary heart disease (OR: 1.97, 95% CI: 1.75-2.20,p &lt; 0.001), and pneumonia (OR: 1.90, 95% CI: 1.80-2.01, p &lt; 0.001). Patients at least 70 years old (OR: 3.09, 95% CI: 1.72-5.53, p &lt; 0.001), males (OR: 1.28, 95% CI: 1.24-1.32,p &lt; 0.001), and uninsured patients (OR: 1.29, 95% CI: 1.15-1.46, p &lt; 0.001) are patient groups at higher risk for in-hospital mortality. 5 primary diagnoses associated with decreased risk of death are the following: fluid/electrolyte disorder (OR: 0.81, 95% CI:0.70-0.93), p = 0.003), central nervous system disease (OR: 0.76, 95% CI: 0.640.91, p = 0.002), arrhythmia (OR: 0.74, 0.65-0.83, p &lt; 0.001), anemia (OR:0.68, 95% CI: 0.55-0.83, &lt; 0.001), complication related to previous surgery of medical therapy (OR:0.64, 95% CI:0.51-0.80, &lt; 0.001), and chronic obstructive pulmonary disease (OR: 0.45, 95% CI: 0.39-0.62, p &lt; 0.001). Conclusions: Older, uninsured, and male lung cancer patients are at high risk for in-hospital mortality. Patients presenting to the ED with respiratory failure and septicemia are at the highest risk for mortality.

Data in brief: Factors associated with in-patient admission among stroke patients (P1-5.024)

<h3>Objective:</h3> To estimate the probability of admission among patients with stroke evaluated in the emergency department. <h3>Background:</h3> Misuse of inpatient resources is a central problem to the healthcare system. Elucidating certain trends behind inpatient admission in patients with a cerebral infarction may reveal opportunities to improve safe and effective stroke triage and throughput. <h3>Design/Methods:</h3> We retrospectively queried the 2019 National Emergency Department Sample Database for patients who had a cerebral infarction. Disposition from the emergency department was classified into one of several categories: routine discharge, discharge against medical advice, transfer to short term hospital, home care, death, and admission to the inpatient setting. The primary endpoint was inpatient admission versus all other dispositions and was assessed using multivariable logistic regression after adjustment for key patient characteristics, hospital teaching and trauma status, geographic regions, insurance status. <h3>Results:</h3> Of the 598,818 patients diagnosed with acute cerebral infarction, 471,464 (78.7%) were admitted to an inpatient acute care facility. Patients with private insurance (OR 0.85, 95%CI 0.78–0.93) or self-pay (OR 0.80, 95%CI 0.70–0.91) had lower odds of being admitted, compared to Medicare patients. Compared to Metropolitan Non-Teaching hospitals, Metropolitan teaching hospitals (OR 1.59, 95%CI 1.27–1.97) had a higher odds of admission, whereas non-metropolitan hospitals (OR 0.35, 95%CI 0.27–0.44) had a lower odds of admission. Additionally, compared to non-trauma hospitals, patients evaluated at level 1 trauma centers (OR 3.17, 95%CI 2.48–4.05) had higher odds of admission. In addition, hyperlipidemia (OR 2.25, 95%CI 2.09–2.42), overweight (OR 2.15, 95%CI 1.90–2.42), and hypertension (OR 1.55, 95%CI 1.47–1.63) were independently associated with a higher odds of admission. <h3>Conclusions:</h3> Optimization of certain high-risk comorbidities may not only reduce stroke incidence, but they may reduce inpatient utilization. Further, differences in admission based on patient-level socioeconomic factors warrant greater exploration to minimize disparities in access to acute care. <b>Disclosure:</b> Mr. Wolfe has nothing to disclose. Karan Patel has nothing to disclose. Mr. Taneja has nothing to disclose. Mr. Oak has nothing to disclose. The institution of Dr. Favilla has received research support from National Institutes of Health. The institution of Dr. Favilla has received research support from American Heart Association. The institution of Dr. Favilla has received research support from OpenWater, Inc.. An immediate family member of Dr. Thon has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Horizon. An immediate family member of Dr. Thon has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Genentech. An immediate family member of Dr. Thon has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Genentech. Dr. Thon has received personal compensation in the range of $500-$4,999 for serving as a Focus group participant with Alexion. Dr. Siegler has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Ceribell. Dr. Siegler has received personal compensation in the range of $10,000-$49,999 for serving on a Speakers Bureau for AstraZeneca.

Abstract 4378: Risk factors for death in the emergency department for melanoma patients

Abstract Introduction: Many cancer deaths are related to melanoma. While there have been many studies that have identified risk factors for death in these patients, very few of them have analyzed the risk factors for death in melanoma patients in the emergency department (ED). Methods: We utilized the 2006-2012 Nationwide Emergency Department Sample to characterize melanoma patients who die in the ED. Multivariate logistic regression was used to identify patient and hospital characteristics that were significantly associated with a higher chance of death. A p-value ≤0.05 was considered significant. Results: From 2006 to 2012, 239,956 melanoma patients presented to the ED, and 2.1% of these melanoma patients died. Most melanoma patients who died in the ED were over the age of 70 years (60.0%), male (63.8%), Medicare beneficiaries (65.6%), of the highest income quartile (31.0%), presenting to a hospital in the South (35.3%), presenting to non-trauma hospitals (48.3%), and presenting to metropolitan non-teaching hospitals (43.4%). The most common reasons for patients who died upon presentation to the ED were a secondary malignancy (20.7%), septicemia (10.8%), acute cerebrovascular disease (7.5%), pneumonia (5.2%), and congestive heart failure (2.6%). The top 3 factors associated with high risk of death were septicemia (odds ratio (OR)=7.39, 95% confidence interval (CI)=5.79-9.43; p&amp;lt;0.001), acute cerebrovascular disease (OR=3.44, 95%CI=2.62-4.51; p&amp;lt;0.001), and age &amp;gt;70 years (OR=2.50, 95%CI=1.24-5.03; p=0.010). Table 1 lists all risk factors associated with a higher risk of death. Conclusion: Melanoma patients over the age of 70, with septicemia, acute cerebrovascular disease, or pneumonia, and of male sex are at higher risk for death in the ED. Clinicians should be aware of these risk factors when melanoma patients present to the ED. Risk Factors Associated with Death for Melanoma Patients in the Emergency Department Risk Factor Odds Ratio (95% Confidence Interval) p-value Septicemia 7.39 (5.79-9.43) &amp;lt;0.001 Acute Cerebrovascular Disease 3.44 (2.62-4.51) &amp;lt;0.001 Age &amp;gt;70 2.50 (1.24-5.03) 0.010 Charlson Comorbidity Index of 3 or More 2.32 (1.89-2.84) &amp;lt;0.001 Pneumonia 1.76 (1.27-2.45) 0.001 Charlson Comorbidity Index of 1 1.64 (1.40-1.93) &amp;lt;0.001 Charlson Comorbidity Index of 2 1.63 (1.31-2.03) &amp;lt;0.001 Medicaid 1.63 (1.19-2.23) 0.002 Metropolitan Teaching Hospital 1.33 (1.05-1.68) 0.017 Citation Format: Jayla Hsiung, Kamil Taneja, Karan Patel, Michael Diaz, Jared Wolfe, Eric M. Toloza. Risk factors for death in the emergency department for melanoma patients. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4378.

Abstract 3215: Analysis of emergency department patients with known limb bone malignancies

Abstract Introduction: Malignant neoplasms of the limb bones are rare. To our knowledge, there are few studies that analyze characteristics of these patients and reasons why they present to an emergency department (ED). Methods: We utilized the 2006-2012 Nationwide Emergency Department Sample to characterize primary diagnoses and outcomes of limb bone cancer patients presenting to an ED. Multivariate logistic regression was used to identify factors associated with high chance of inpatient admission. A p-value ≤0.05 was significant. Results: In this period, 4,020 limb bone cancer patients presented to the ED. Most patients were between ages of 18 and 29 (30.3%), male (58.1%), covered by private insurance (35.5%), in the second income quartile (26.3%), living in the South (35.3%), presenting to non-trauma hospitals (42.3%), and presenting to metropolitan teaching hospitals (53.0%). Most patients were admitted (64.9%) or discharged (29.1%). Most common primary diagnoses of the ED visit were white blood cell (WBC) disorders (8.6%), secondary malignancies (7.4%), pathologic disorder (5.9%), septicemia (4.8%), and central nervous system disorders (3.7%). Primary diagnoses associated with highest risk of inpatient admission were WBC disorder (odds ratio (OR)=21.1, 95% confidence interval (CI)=7.1-63.2; p&amp;lt;0.001), pneumonia (OR=13.2, 95%CI=1.5-118.5, p=0.022), secondary malignancy (OR=11.1, 95%CI=3.4-36.3, p&amp;lt;0.001), pathological fracture (OR=5.2, 95%CI=2.3-11.7, p&amp;lt;0.001), and complication due to previous surgery or medical treatment (OR=3.9, 95%CI=1.4-11.4, p=0.012). Table 1 lists risks of inpatient admission associated with the 20 most common primary diagnoses. Conclusion: Patients with limb bone cancers are young patients who present to the ED with WBC disorders, secondary malignancies, pathologic bone fractures, and infections. Clinicians should keep these conditions in mind when treating these patients. Risk of Inpatient Admission Based on Primary Diagnosis in the Emergency Department Primary Diagnosis Odds Ratio (95% Confidence Interval) p-value White Blood Cell Disorder 21.1 (7.1-63.2) &amp;lt;0.001 Pneumonia 13.2 (1.5-118.5) 0.022 Secondary Malignancy 11.1 (3.4-36.3) &amp;lt;0.001 Pathologic Fracture 5.2 (2.3-11.7) &amp;lt;0.001 Complication of Surgery or Medical Treatment 3.9 (1.36-11.4) 0.012 Complication of Device or Graft 3.8 (1.65-8.6) 0.002 Urinary Tract Infection 3.3 (1.14-9.6) 0.027 Anemia 3.0 (1.19-7.6) 0.020 Pleurisy or Pneumothorax 1.61 (0.33-7.8) 0.554 Arrhythmia 1.46 (0.39-5.5) 0.575 Skin Infection 1.13 (0.4-3.6) 0.829 Nervous System Disorder 1.10 (0.5-2.5) 0.826 Nausea or Vomiting 0.92 (0.32-2.6) 0.869 Fluid or Electrolyte Disorder 0.57 (0.14-2.3) 0.438 Fever 0.43 (0.15-1.19) 0.102 Chest Pain 0.23 (0.06-0.84 0.026 Connective Tissue Damage 0.11 (0.03-0.41) 0.001 Joint Disorder 0.10 (0.02-0.46) 0.003 Septicemia Not Available: All Admitted - Respiratory Failure Not Available: All Admitted - Citation Format: Lauren C. Ladehoff, Kamil Taneja, Karan Patel, Jeeyong Shin, Sahas Chandragiri, Hailey Hsiung, Michael Diaz, Eric M. Toloza. Analysis of emergency department patients with known limb bone malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3215.

Feasibility for Immediate Targeted Muscle Reinnervation Based on Lower Extremity Amputations Trends

De-identified data over a five-year period for all patients undergoing lower extremity amputation were collected. The data gathered included the specialty performing the amputation, weekly distribution of cases, start time, and end time, among others. A total of 1549 lower extremity amputations were performed. There was no statistically significant difference in average number of below-the-knee amputations (172.8) and above-the-knee amputations (137.4) per year. Top specialties performing amputations were vascular surgery (47.8%), orthopedic surgery (34.5%), and general surgery (13.85%). No significant difference was noted in the average number of amputations across the week, per year. Most cases started between 6 am and 6 pm (96.4%). The average length of stay after surgery was 8.26 days. In a large, nontrauma hospital system, most lower extremity amputations are performed during typical working hours and are evenly distributed throughout the week. Understanding peak timing of amputations may allow for targeted muscle reinnervation to be performed concurrently with amputation procedure. Data presented will be a first step to optimizing amputation scheduling for patients in a large nontrauma health system.

Comparison of survival outcomes among older adults with major trauma after trauma center versus non-trauma center care in the United States.

To compare level 1 and 2 trauma centers with similarly sized non-trauma centers on survival after major trauma among older adults. We used claims of 100% of 2012-2017 Medicare fee-for-service beneficiaries who received hospital care after major trauma. Survival differences were estimated after applying propensity-score-based overlap weights. Subgroup analyses were performed for ambulance-transported patients and by external cause. We assessed the roles of prehospital care, hospital quality, and volume. Data were obtained from the Centers for Medicare and Medicaid Services. Thirty-day mortality was higher overall at level 1 versus non-trauma centers by 2.2 (95% confidence interval [CI]: 1.8, 2.6) percentage points (pp). Thirty-day mortality was higher at level 1 versus non-trauma centers by 2.3 (95% CI: 1.9, 2.8) pp for falls and 2.3 (95% CI: 0.2, 4.4) pp for motor vehicle crashes. Differences persisted at 1 year. Level 1 and 2 trauma centers had similar outcomes. Hospital quality and volume did not explain these differences. In the ambulance-transported subgroup, after adjusting for prehospital variables, no statistically significant differences remained. Trauma centers may not provide longer survival than similarly sized non-trauma hospitals for severely injured older adults.

Factors Associated with Length of Stay and Cost among Pediatric Hospitalizations with a Primary Ophthalmic Diagnosis

ABSTRACT Purpose To investigate factors associated with prolonged length of stay and high cost among pediatric hospitalizations with a primary ophthalmic diagnosis. Methods This retrospective, cross-sectional study utilized data on pediatric admissions with a primary ophthalmic diagnosis from the multicenter 2016 Kids’ Inpatient Database. Multivariable logistic regression models adjusted for demographic, hospital, and admission characteristics were used to evaluate factors associated with prolonged stay and high cost, defined as exceeding the 75th percentile (>4 days and $12,642, respectively). Results An estimated 6,811 pediatric hospitalizations with a primary ophthalmic diagnosis in the United States in 2016 were included. On adjusted analysis, a prolonged length of stay was more likely with Medicaid (vs. private insurance, OR = 1.19, 95% CI: [1.02, 1.40], p = .03), non-trauma (vs. trauma, OR = 2.77, 95% CI: [2.12, 3.63], p < .001) and urban teaching hospitals (vs. rural, OR = 3.48, 95% CI: [1.04, 11.69], p = .04). A high cost of stay was more likely with higher income levels (Quartile 3 vs. 1, OR = 1.30, 95% CI: [1.02, 1.67], p = .04; Quartile 4 vs. 1, OR = 1.49, 95% CI: [1.08, 2.05], p = .02), private insurance (vs. Medicaid, OR = 1.26, 95% CI: [1.04, 1.53], p = .02), Western hospitals (vs. South, OR = 2.74, 95% CI: [1.83, 4.12], p < .001), and trauma (vs. non-trauma, OR = 3.29, 95% CI: [2.57, 4.21], p < .001). Children and young adults had higher odds of prolonged stay, while adolescents and young adults had higher odds of high cost compared to toddlers (p < .05 for all). Conclusions Additional work addressing the factors associated with higher resource utilization may help promote the delivery of quality inpatient pediatric eye care.

Exploring Factors That Influence Injured Patients’ Outcomes following Road Traffic Crashes: A Multi-Site Feasibility Study

Background: Injuries arising from Road Traffic Crashes (RTCs) are a major health problem in Saudi Arabia (SA). The purpose of the study was to determine the feasibility of conducting a multi-center research study to explore factors that influence the mortality of RTC-related trauma patients in SA. Methods: A multi-center observational study was undertaken involving both prospective and retrospective data collected from three hospitals. In-hospital patient mortality thirty days post-crash was the primary outcome variable. The feasibility of the study methods including the quality of data were evaluated and pilot results pertaining to factors predicting mortality were examined. Results: The overall mortality rate (n = 572 RTC victims) was (7.5%). A logistic regression model identified four independent predictors of mortality following an RTC: treatment at a non-trauma center-based hospital, SBP ≤ 90 mmHg, GCS ≤ 8, and ISS ≥ 20. With respect to the assessment of the study method’s feasibility, missing data was problematic, especially for variables pertaining to crash characteristics and prehospital care. Conclusions: Collecting multi-center injury data in SA has logistic challenges, predominantly associated with the comparability and completeness of data sets as well as the need for manual screening and data collection at some institutions. Despite these limitations, this study has demonstrated the feasibility of a method that could be utilized in further large nationwide studies to understand and examine the factors that influence injured patients’ outcomes following RTCs.

Under-Triage and Over-Triage Using the Field Triage Guidelines for Injured Patients: A Systematic Review

Objectives The Field Triage Guidelines (FTG) are used across North America to identify seriously injured patients for transport to appropriate level trauma centers, with a goal of under-triaging no more than 5% and over-triaging between 25% and 35%. Our objective was to systematically review the literature on under-triage and over-triage rates of the FTG. Methods We conducted a systematic review of the FTG performance. Ovid Medline, EMBASE, and the Cochrane databases were searched for studies published between January 2011 and February 2021. Two investigators dual-reviewed eligibility of abstracts and full-text. We included studies evaluating under- or over-triage of patients using the FTG in the prehospital setting. We excluded studies not reporting an outcome of under- or over-triage, studies evaluating other triage tools, or studies of triage not in the prehospital setting. Two investigators independently assessed the risk of bias for each included article. The primary accuracy measures to assess the FTG were under-triage, defined as seriously injured patients transported to non-trauma hospitals (1-sensitivity), and over-triage, defined as non-injured patients transported to trauma hospitals (1-specificity). Due to heterogeneity, results were synthesized qualitatively. Results We screened 2,418 abstracts, reviewed 315 full-text publications, and identified 17 studies that evaluated the accuracy of the FTG. Among eight studies evaluating the entire FTG (steps 1–4), under-triage rates ranged from 1.6% to 72.0% and were higher for older (≥55 or ≥65 years) adults (20.1–72.0%) and pediatric (<15 years) patients (15.9–34.8%) compared to all ages (1.6–33.8%). Over-triage rates ranged from 9.9% to 87.4% and were higher for all ages (12.2–87.4%) compared to older (≥55 or ≥65 years) adults (9.9–48.2%) and pediatric (<15 years) patients (28.0–33.6%). Under-triage was lower in studies strictly applying the FTG retrospectively (1.6–34.8%) compared to as-practiced (10.5–72.0%), while over-triage was higher retrospectively (64.2–87.4%) compared to as-practiced (9.9–48.2%). Conclusions Evidence suggests that under-triage, while improved if the FTG is strictly applied, remains above targets, with higher rates of under-triage in both children and older adults.

Fracture liaison services in Ireland-how do we compare to international standards?

Fragility/low-trauma fractures are a global concern, whose incidence is rising as the population ages. Many are preventable, and people with a prior fragility fracture are at particularly high risk of further fractures. This patient group is the target of the International Osteoporosis Foundation (IOF) Capture the Fracture campaign, advocating global adoption of fracture liaison services (FLS), with the aim of preventing secondary fragility fractures. We wished to determine the current availability and standards of an FLS in Ireland, ahead of the launch of a National FLS database. We devised a questionnaire encompassing the thirteen IOF standards for an FLS and asked all 16 public hospitals with an orthopaedic trauma unit in Ireland, to complete for the calendar year 2019 in patients aged ≥ 50years. All sites returned the questionnaire, i.e. 100% response rate. Nine hospitals stated that they have an FLS, additionally one non-trauma hospital running a FLS responded, and were included. These 10 FLS had identified and managed 3444 non-hip fractures in the year 2019. This figure represents 19% of the expected non-hip fragility fracture numbers occurring annually in Ireland. Implementation of the IOF standards was very variable. All sites reported being inadequately resourced to provide a high-quality service necessary to be effective. The existence and functioning of FLS in Ireland are heterogeneous and suboptimal. A national policy to support the implementation of this programme in line with international standards of patient care is urgently needed.

Extending Trauma Quality Improvement Beyond Trauma Centers: Hospital Variation in Outcomes Among Nontrauma Hospitals.

The American College of Surgeons (ACS) conducts a robust quality improvement program for ACS-verified trauma centers, yet many injured patients receive care at non-accredited facilities. This study tested for variation in outcomes across non-trauma hospitals and characterized hospitals associated with increased mortality. The study included state trauma registry data of 37,670 patients treated between January 1, 2013, and December 31, 2015. Clinical data were supplemented with data from the American Hospital Association and US Department of Agriculture, allowing comparisons among 100 nontrauma hospitals. Using Bayesian techniques, risk-adjusted and reliability-adjusted rates of mortality and interfacility transfer, as well as Emergency Departments length-of-stay (ED-LOS) among patients transferred from EDs were calculated for each hospital. Subgroup analyses were performed for patients ages >55 years and those with decreased Glasgow coma scores (GCS). Multiple imputation was used to address missing data. Mortality varied 3-fold (0.9%-3.1%); interfacility transfer rates varied 46-fold (2.1%-95.6%); and mean ED-LOS varied 3-fold (81-231 minutes). Hospitals that were high and low statistical outliers were identified for each outcome, and subgroup analyses demonstrated comparable hospital variation. Metropolitan hospitals were associated increased mortality [odds ratio (OR) 1.7, P = 0.004], decreased likelihood of interfacility transfer (OR 0.7, P ≤ 0.001), and increased ED-LOS (coef. 0.1, P ≤ 0.001) when compared with nonmetropolitan hospitals and risk-adjusted. Wide variation in trauma outcomes exists across nontrauma hospitals. Efforts to improve trauma quality should include engagement of nontrauma hospitals to reduce variation in outcomes of injured patients treated at those facilities.