Comparison of Clinical Characteristics and Biomarkers in Culture-Positive and Culture-Negative Sepsis Patients.

OBJECTIVES: Sepsis is one of the leading causes of morbidity and mortality worldwide, and culture-negative sepsis, despite its prevalence, is largely understudied. The current study intends to examine clinical characteristics and biomarkers in culture-positive and culture-negative sepsis, focusing on 30-day mortality and duration of hospital stay in both groups.  Materials and methods: A prospective observational comparative cohort study was done on 150 patients admitted to the intensive care unit (ICU) and wards of Jaipur Golden Hospital. Patients with documented fungal, viral, or parasitic infections, as well as those who had undergone surgery or experienced trauma, were excluded.  Results: The mean age of the patients was 51.31±18.94 years. Of 150 patients, 95 (63.3%) were culture-negative, whereas 55 (36.7%) were culture-positive, with more men in the former and more women in the latter. Patients with negative cultures had fewer comorbidities. The levels of procalcitonin (PCT), C-reactive protein (CRP), and serum lactate were within the prescribed limit for both culture-negative and positive patients. A higher proportion (87.3%) of the organisms isolated from culture-positive individuals were gram-negative, with Escherichia coli (E. coli) having the highest prevalence (27.3%), followed by Klebsiella (20%). There were 12.7% gram-positive isolates. The culture-negative patients had significantly better outcomes (P=0.003) as well as the duration of hospital stay (P<0.001) than the culture-positive patients. Culture-positive patients had a more severe illness, a higher incidence of septic shock, and a higher fatality rate than culture-negative patients. CONCLUSION: It can be concluded that CRP and PCT can be used as clinically reliable sepsis biomarkers in both culture-positive and culture-negative patients. The study found that culture-negative sepsis is more prevalent and that there are substantial differences between culture-negative and culture-positive sepsis, with the former group having fewer comorbidities, less severe illness, a shorter duration of hospital stays, lower death rates, and better outcomes.

Geriatric Emergency Medication Safety Recommendations (GEMS-Rx): Modified Delphi Development of a High-Risk Prescription List for Older Emergency Department Patients.

STUDY OBJECTIVE: Half of emergency department (ED) patients aged 65 years and older are discharged with new prescriptions. Potentially inappropriate prescriptions contribute to adverse drug events. Our objective was to develop an evidence- and consensus-based list of high-risk prescriptions to avoid among older ED patients. METHODS: We performed a modified, 3-round Delphi process that included 10 ED physician experts in geriatrics or quality measurement and 1 pharmacist. Consensus members reviewed all 35 medication categories from the 2019 American Geriatrics Society Beers Criteria and ranked each on a 5-point Likert scale (5=highest) for overall priority for avoidance (Round 1), risk of short-term adverse events and avoidability (Round 2), and reasonable medical indications for high-risk medication use (Round 3). RESULTS: For each round, questionnaire response rates were 91%, 82%, and 64%, respectively. After Round 1, benzodiazepines (mean, 4.60 [SD, 0.70]), skeletal muscle relaxants (4.60 [0.70]), barbiturates (4.30 [1.06]), first-generation antipsychotics (4.20 [0.63]) and first-generation antihistamines (3.70 [1.49]) were prioritized for avoidance. In Rounds 2 and 3, hypnotic "Z" drugs (4.29 [1.11]), metoclopramide (3.89 [0.93]), and sulfonylureas (4.14 [1.07]) were prioritized for avoidability, despite lower concern for short-term adverse events. All 8 medication classes were included in the final list. Reasonable indications for prescribing high-risk medications included seizure disorders, benzodiazepine/ethanol withdrawal, end of life, severe generalized anxiety, allergic reactions, gastroparesis, and prescription refill. CONCLUSION: We present the first expert consensus-based list of high-risk prescriptions for older ED patients (GEMS-Rx) to improve safety among older ED patients.

The Clinical Emergency Data Registry: Structure, Use, and Limitations for Research.

The Clinical Emergency Data Registry (CEDR) is a qualified clinical data registry that collects data from participating emergency departments (EDs) in the United States for quality measurement, improvement, and reporting purposes. This article aims to provide an overview of the data collection and validation process, describe the existing data structure and elements, and explain the potential opportunities and limitations for ongoing and future research use. CEDR data are primarily collected for quality reporting purposes and are obtained from diverse sources, including electronic health records and billing data that are de-identified and stored in a secure, centralized database. The CEDR data structure is organized around clinical episodes, which contain multiple data elements that are standardized using common data elements and are mapped to established terminologies to enable interoperability and data sharing. The data elements include patient demographics, clinical characteristics, diagnostic and treatment procedures, and outcomes. Key limitations include the limited generalizability due to the selective nature of participating EDs and the limited validation and completeness of data elements not currently used for quality reporting purposes, including demographic data. Nonetheless, CEDR holds great potential for ongoing and future research in emergency medicine due to its large-volume, longitudinal, near real-time, clinical data. In 2021, the American College of Emergency Physicians authorized the transition from CEDR to the Emergency Medicine Data Institute, which will catalyze investments in improved data quality and completeness for research to advance emergency care.

Leveraging a Learning Collaborative Model to Develop and Pilot Quality Measures to Improve Opioid Prescribing in the Emergency Department.

The American College of Emergency Physicians (ACEP) Emergency Medicine Quality Network (E-QUAL) Opioid Initiative was launched in 2018 to advance the dissemination of evidence-based resources to promote the care of emergency department (ED) patients with opioid use disorder. This virtual platform-based national learning collaborative includes a low-burden, structured quality improvement project, data benchmarking, tailored educational content, and resources designed to support a nationwide network of EDs with limited administrative and research infrastructure. As a part of this collaboration, we convened a group of experts to identify and design a set of measures to improve opioid prescribing practices to provide safe analgesia while reducing opioid-related harms. We present those measures here, alongside initial performance data on those measures from a sample of 370 nationwide community EDs participating in the 2019 E-QUAL collaborative. Measures include proportion of opioid administration in the ED, proportion of alternatives to opioids as first-line treatment, proportion of opioid prescription, opioid pill count per prescription, and patient medication safety education among ED visits for atraumatic back pain, dental pain, or headache. The proportion of benzodiazepine and opioid coprescribing for ED visits for atraumatic back pain was also evaluated. This project developed and effectively implemented a collection of 6 potential measures to evaluate opioid analgesic prescribing across a national sample of community EDs, representing the first feasibility assessment of opioid prescribing-related measures from rural and community EDs.

Neural ordinary differential equations with irregular and noisy data.

Measurement noise is an integral part of collecting data of a physical process. Thus, noise removal is necessary to draw conclusions from these data, and it often becomes essential to construct dynamical models using these data. We discuss a methodology to learn differential equation(s) using noisy and irregularly sampled measurements. In our methodology, the main innovation can be seen in the integration of deep neural networks with the neural ordinary differential equations (ODEs) approach. Precisely, we aim at learning a neural network that provides (approximately) an implicit representation of the data and an additional neural network that models the vector fields of the dependent variables. We combine these two networks by constraints using neural ODEs. The proposed framework to learn a model describing the vector field is highly effective under noisy measurements. The approach can handle scenarios where dependent variables are unavailable at the same temporal grid. Moreover, a particular structure, e.g. second order with respect to time, can easily be incorporated. We demonstrate the effectiveness of the proposed method for learning models using data obtained from various differential equations and present a comparison with the neural ODE method that does not make any special treatment to noise. Additionally, we discuss an ensemble approach to improve the performance of the proposed approach further.

An Outcome Comparison Between Geriatric and Nongeriatric Emergency Departments.

STUDY OBJECTIVE: We sought to describe diagnosis rates and compare common process outcomes between geriatric emergency departments (EDs) and nongeriatric EDs participating in the American College of Emergency Physicians Clinical Emergency Data Registry (CEDR). METHODS: We conducted an observational study of ED visits in calendar year 2021 within the CEDR by older adults. The analytic sample included 6,444,110 visits at 38 geriatric EDs and 152 matched nongeriatric EDs, with the geriatric ED status determined based on linkage to the American College of Emergency Physicians' Geriatric ED Accreditation program. Stratified by age, we assessed diagnosis rates (X/1000) for 4 common geriatric syndrome conditions and a set of common process outcomes including the ED length of stay, discharge rates, and 72-hour revisit rates. RESULTS: Across all age categories, geriatric EDs had higher diagnosis rates than nongeriatric EDs for 3 of the 4 following geriatric syndrome conditions of interest: urinary tract infection, dementia, and delirium/altered mental status. The median ED site-level length of stay for older adults was lower at geriatric EDs compared with that at nongeriatric EDs, whereas 72-hour revisit rates were similar across all age categories. Geriatric EDs exhibited a median discharge rate of 67.5% for adults aged 65 to 74 years, 60.8% for adults aged 75 to 84 years, and 55.6% for adults aged >85 years. Comparatively, the median discharge rate at nongeriatric ED sites was 69.0% for adults aged 65 to 74 years, 64.2% for adults aged 75 to 84 years, and 61.3% for adults aged >85 years. CONCLUSION: Geriatric EDs had higher geriatric syndrome diagnosis rates, lower ED lengths of stay, and similar discharge and 72-hour revisit rates when compared with nongeriatric EDs in the CEDR. These findings provide the first benchmarks for emergency care process outcomes in geriatric EDs compared with nongeriatric EDs.

Clinical Performance Measures for Emergency Department Care for Adults With Intracranial Hemorrhage.

Though select inpatient-based performance measures exist for the care of patients with nontraumatic intracranial hemorrhage, emergency departments lack measurement instruments designed to support and improve care processes in the hyperacute phase. To address this, we propose a set of measures applying a syndromic (rather than diagnosis-based) approach informed by performance data from a national sample of community EDs participating in the Emergency Quality Network Stroke Initiative. To develop the measure set, we convened a workgroup of experts in acute neurologic emergencies. The group considered the appropriate use case for each proposed measure: internal quality improvement, benchmarking, or accountability, and examined data from Emergency Quality Network Stroke Initiative-participating EDs to consider the validity and feasibility of proposed measures for quality measurement and improvement applications. The initially conceived set included 14 measure concepts, of which 7 were selected for inclusion in the measure set after a review of data and further deliberation. Proposed measures include 2 for quality improvement, benchmarking, and accountability (Last 2 Recorded Systolic Blood Pressure Measurements Under 150 and Platelet Avoidance), 3 for quality improvement and benchmarking (Proportion of Patients on Oral Anticoagulants Receiving Hemostatic Medications, Median ED Length of Stay for admitted patients, and Median Length of Stay for transferred patients), and 2 for quality improvement only (Severity Assessment in the ED and Computed Tomography Angiography Performance). The proposed measure set warrants further development and validation to support broader implementation and advance national health care quality goals. Ultimately, applying these measures may help identify opportunities for improvement and focus quality improvement resources on evidence-based targets.

A Quality Framework to Address Racial and Ethnic Disparities in Emergency Department Care.

The emergency department serves as a vital source of health care for residents in the United States, including as a safety net. However, patients from minoritized racial and ethnic groups have historically experienced disproportionate barriers to accessing health care services and lower quality of services than White patients. Quality measures and their application to quality improvement initiatives represent a critical opportunity to incentivize health care systems to advance health equity and reduce health disparities. Currently, there are no nationally recognized quality measures that track the quality of emergency care delivery by race and ethnicity and no published frameworks to guide the development and prioritization of quality measures to reduce health disparities in emergency care. To address these gaps, the American College of Emergency Physicians (ACEP) convened a working group of experts in quality measurement, health disparities, and health equity to develop guidance on establishing quality measures to address racial and ethnic disparities in the provision of emergency care. Based on iterative discussion over 3 working group meetings, we present a summary of existing emergency medicine quality measures that should be adapted to track racial and ethnic disparities, as well as a framework for developing new measures that focus on disparities in access to emergency care, care delivery, and transitions of care.

Pediatric mental health visits with prolonged length of stay in community emergency departments during COVID-19.

Objectives: To characterize trends in pediatric mental health visit counts, including visits for prolonged length of stay (LOS), in a sample of emergency departments (EDs) from 29 states during COVID-19. Methods: We performed a secondary analysis of the Clinical Emergency Data Registry from January 2020 through December 2021. We reported trends in pediatric mental health visit counts overall and for those with prolonged ED LOS. We reported incident rate ratios (IRRs) for monthly counts compared to January 2020. Among visits with LOS >24 hours, we reported on the most common diagnostic categories. Results: There were 107 EDs from 29 states with available complete data in 2020 and 2021. Pediatric mental health visit counts resulting in a LOS greater than 6, 12, and 24 hours were higher for much of 2021. At their peak, there were 604 visits with LOS >12 hours (IRR, 2.14; 95% confidence interval [CI], 1.86-2.47) and 262 visits (IRR, 2.46; 95% CI, 1.97-3.09) with LOS >24 hours in April 2021. Pediatric mental health visits with LOS >12 hours and >24 hours made up 20.9% and 7.3% of pediatric mental health visits overall, respectively. For visits with ED LOS >24 hours, the most common diagnostic categories were suicide or self-injury, depressive disorders, and mental health syndrome. Conclusions: In this sample of 107 EDs in 29 states, visit counts with prolonged LOS >24 hours more than doubled in some months since the arrival of COVID-19. These findings are indicative of an increasingly strained emergency and mental health system.

Development and testing of data infrastructure in the American College of Emergency Physicians' Clinical Emergency Data Registry for opioid-related research.

Objective: Prior research has identified gaps in the capacity of electronic health records (EHRs) to capture the intricacies of opioid-related conditions. We sought to enhance the opioid data infrastructure within the American College of Emergency Physicians' Clinical Emergency Data Registry (CEDR), the largest national emergency medicine registry, through data mapping, validity testing, and feasibility assessment. Methods: We compared the CEDR data dictionary to opioid common data elements identified through prior environmental scans of publicly available data systems and dictionaries used in national informatics and quality measurement of policy initiatives. Validity and feasibility assessments of CEDR opioid-related data were conducted through the following steps: (1) electronic extraction of CEDR data meeting criteria for an opioid-related emergency care visit, (2) manual chart review assessing the quality of the extracted data, (3) completion of feasibility scorecards, and (4) qualitative interviews with physician reviewers and informatics personnel. Results: We identified several data gaps in the CEDR data dictionary when compared with prior environmental scans including urine drug testing, opioid medication, and social history data elements. Validity testing demonstrated correct or partially correct data for >90% of most extracted CEDR data elements. Factors affecting validity included lack of standardization, data incorrectness, and poor delimitation between emergency department (ED) versus hospital care. Feasibility testing highlighted low-to-moderate feasibility of date and social history data elements, significant EHR platform variation, and inconsistency in the extraction of common national data standards (eg, Logical Observation Identifiers Names and Codes, International Classification of Diseases, Tenth Revision codes). Conclusions: We found that high-priority data elements needed for opioid-related research and clinical quality measurement, such as demographics, medications, and diagnoses, are both valid and can be feasibly captured in a national clinical quality registry. Future work should focus on implementing structured data collection tools, such as standardized documentation templates and adhering to data standards within the EHR that would better characterize ED-specific care for opioid use disorder and related research.

Improving Sepsis Management Through the Emergency Quality Network Sepsis Initiative.

BACKGROUND: Public reporting of the Centers for Medicare & Medicaid (CMS) SEP-1 sepsis quality measure is often too late and without the data granularity to inform real-time quality improvement (QI). In response, the American College of Emergency Physicians (ACEP) Emergency Quality Network (E-QUAL) Sepsis Initiative sought to support QI efforts through benchmarking of preliminary draft SEP-1 scores for emergency department (ED) patients. This study sought to determine the anticipatory value of these preliminary SEP-1 benchmarking scores and publicly reported performance. METHODS: Cross-sectional analysis was performed on QI data collected from hospital-based ED sites participating in the E-QUAL Sepsis Collaborative in 2017 and 2018. Participating EDs submitted SEP-1 benchmarking scores semiannually, which were compared to publicly reported CMS SEP-1 data. EDs also reported implementation data on a variety of sepsis-related QI activities for comparison based on SEP-1 performance. RESULTS: Among 220 EDs participating in E-QUAL, SEP-1 benchmarking scores showed weak but statistically significant correlation with CMS SEP-1 scores (r = 0.189, p = 0.01). Mean E-QUAL SEP-1 benchmarking scores were higher than mean CMS SEP-1 scores (74.1% vs. 57.2%), with 83.2% of sites reporting a benchmarking score higher than the CMS SEP-1 score. EDs with SEP-1 scores in the bottom 20% reported completion of more sepsis-related QI activities than EDs with average or top 20% SEP-1 scores. CONCLUSION: Preliminary benchmarking results demonstrate a weak, statistically significant correlation with subsequent publicly reported CMS SEP-1 scores and suggest that ED performance in sepsis care may exceed overall hospital performance inclusive of all inpatients. Sepsis quality measurement and sepsis QI efforts may be best guided by separating ED sepsis cases from in-hospital sepsis cases as is done for other acute time-sensitive conditions.

A survey of stroke-related capabilities among a sample of US community emergency departments.

Objectives: Most acute stroke research is conducted at academic and larger hospitals, which may differ from many non-academic (ie, community) and smaller hospitals with respect to resources and consultant availability. We describe current emergency department (ED) and hospital-level stroke-related capabilities among a sample of community EDs participating in the Emergency Quality Network (E-QUAL) stroke collaborative. Methods: Among E-QUAL-participating EDs, we conducted a survey to collect data on ED and hospital stroke-related structural and process capabilities associated with quality of stroke care delivery and patient outcomes. EDs submitted data using a web-based submission portal. We present descriptive statistics of self-reported capabilities. Results: Of 154 participating EDs in 30 states, 97 (63%) completed the survey. Many were rural (33%); most (82%) were not certified stroke centers. Although most reported having stroke protocols (67%), many did not include hemorrhagic stroke or transient ischemic attack (45% and 57%, respectively). Capability to perform emergent head computed tomography and to administer thrombolysis were not universal (absent in 4% and 5%, respectively). Access to neurologic consultants varied; 18% reported no 24/7 availability onsite or remotely. Of those with access, 48% reported access through telemedicine only. Admission capabilities also varied with patient transfer commonly performed (79%). Conclusion: Stroke-related capabilities vary substantially between community EDs and are different from capabilities typically found in larger stroke centers. These data may be valuable for identifying areas for future investment. Additionally, the design of stroke quality improvement interventions and metrics to evaluate emergency stroke care delivery should account for these key structural differences.

Discovery of nonlinear dynamical systems using a Runge-Kutta inspired dictionary-based sparse regression approach.

In this work, we blend machine learning and dictionary-based learning with numerical analysis tools to discover differential equations from noisy and sparsely sampled measurement data of time-dependent processes. We use the fact that given a dictionary containing large candidate nonlinear functions, dynamical models can often be described by a few appropriately chosen basis functions. As a result, we obtain parsimonious models that can be better interpreted by practitioners, and potentially generalize better beyond the sampling regime than black-box modelling. In this work, we integrate a numerical integration framework with dictionary learning that yields differential equations without requiring or approximating derivative information at any stage. Hence, it is utterly effective for corrupted and sparsely sampled data. We discuss its extension to governing equations, containing rational nonlinearities that typically appear in biological networks. Moreover, we generalized the method to governing equations subject to parameter variations and externally controlled inputs. We demonstrate the efficiency of the method to discover a number of diverse differential equations using noisy measurements, including a model describing neural dynamics, chaotic Lorenz model, Michaelis-Menten kinetics and a parameterized Hopf normal form.

The future of value-based emergency care: Development of an emergency medicine MIPS value pathway framework.

The Centers for Medicare & Medicaid Services (CMS) implemented the Merit-based Incentive Payment System (MIPS) to accelerate the transition of physician payment toward value-based care models and away from traditional fee-for-service payment programs. In recent years, CMS has sought to modify the program by developing a MIPS Value Pathway (MVP) framework intended to use existing and future physician quality and cost measures to reward value-based care delivery. This article describes the multi-step process of the MVP Task Force, convened by the American College of Emergency Physicians (ACEP) to develop an emergency medicine-specific MVP proposal informed by diverse stakeholder perceptions regarding: (1) which existing quality measures reflect high quality emergency care, and (2) the degree to which emergency clinicians can impact clinical outcomes and cost for the care domains captured by existing quality measures. The MVP Task Force synthesized stakeholder feedback and underwent a consensus-building approach to develop the "Adopting Best Practices and Promoting Patient Safety within Emergency Medicine" MVP, recently reviewed and approved by CMS for national implementation starting in 2023. Our process and findings have broad implications for clinicians, administrators, and policymakers navigating the continued transition to value-based care in conjunction with CMS's implementation of the MVP framework.

Emergency department utilization for substance use disorders and mental health conditions during COVID-19.

BACKGROUND: As the emergency department (ED) has evolved into the de-facto site of care for a variety of substance use disorder (SUD) presentations, trends in ED utilization are an essential public health surveillance tool. Changes in ED visit patterns during the COVID-19 pandemic may reflect changes in access to outpatient treatment, changes in SUD incidence, or the unintended effects of public policy to mitigate COVID-19. We use a national emergency medicine registry to describe and characterize trends in ED visitation for SUDs since 2019. METHODS: We included all ED visits identified in a national emergency medicine clinical quality registry, which included 174 sites across 33 states with data from January 2019 through June 2021. We defined SUD using ED visit diagnosis codes including: opioid overdose and opioid use disorder (OUD), alcohol use disorders (AUD), and other SUD. To characterize changes in ED utilization, we plotted the 3-week moving average ratio of visit counts in 2020 and 2021 as compared to visit counts in 2019. FINDINGS: While overall ED visits declined in the early pandemic period and had not returned to 2019 baseline by June 2021, ED visit counts for SUD demonstrated smaller declines in March and April of 2020, so that the proportion of overall ED visits that were for SUD increased. Furthermore, in the second half of 2020, ED visits for SUD returned to baseline, and increased above baseline for OUD ever since May 2020. CONCLUSIONS: We observe distinct patterns in ED visitation for SUDs over the course of the COVID-19 pandemic, particularly for OUD for which ED visitation barely declined and now exceeds previous baselines. These trends likely demonstrate the essential role of hospital-based EDs in providing 24/7/365 care for people with SUDs and mental health conditions. Allocation of resources must be directed towards the ED as a de-facto safety net for populations in crisis.

Emergency department visits for emergent conditions among older adults during the COVID-19 pandemic.

BACKGROUND/OBJECTIVE: Emergency department (ED) visits have declined while excess mortality, not attributable to COVID-19, has grown. It is not known whether older adults are accessing emergency care differently from their younger counterparts. Our objective was to determine patterns of ED visit counts for emergent conditions during the COVID-19 pandemic for older adults. DESIGN: Retrospective, observational study. SETTING: Observational analysis of ED sites enrolled in a national clinical quality registry. PARTICIPANTS: One hundred and sixty-four ED sites in 33 states from January 1, 2019 to November 15, 2020. MAIN OUTCOME AND MEASURES: We measured daily ED visit counts for acute myocardial infarction (AMI), stroke, sepsis, fall, and hip fracture, as well as deaths in the ED, by age categories. We estimated Poisson regression models comparing early and post-early pandemic periods (defined by the Centers for Disease Control and Prevention) to the pre-pandemic period. We report incident rate ratios to summarize changes in visit incidence. RESULTS: For AMI, stroke, and sepsis, the older (75-84) and oldest old (85+ years) had the greatest decline in visit counts initially and the smallest recovery in the post-early pandemic periods. For falls, visits declined early and partially recovered uniformly across age categories. In contrast, hip fractures exhibited less change in visit rates across time periods. Deaths in the ED increased during the early pandemic period, but then fell and were persistently lower than baseline, especially for the older (75-84) and oldest old (85+ years). CONCLUSIONS: The decline in ED visits for emergent conditions among older adults has been more pronounced and persistent than for younger patients, with fewer deaths in the ED. This is concerning given the greater prevalence and risk of poor outcomes for emergent conditions in this age group that are amenable to time-sensitive ED diagnosis and treatment, and may in part explain excess mortality during the COVID-19 era among older adults.

Tomographic X-ray scattering based on invariant reconstruction: analysis of the 3D nanostructure of bovine bone.

Small-angle X-ray scattering (SAXS) is an effective characterization technique for multi-phase nanocomposites. The structural complexity and heterogeneity of biological materials require the development of new techniques for the 3D characterization of their hierarchical structures. Emerging SAXS tomographic methods allow reconstruction of the 3D scattering pattern in each voxel but are costly in terms of synchrotron measurement time and computer time. To address this problem, an approach has been developed based on the reconstruction of SAXS invariants to allow for fast 3D characterization of nanostructured inhomogeneous materials. SAXS invariants are scalars replacing the 3D scattering patterns in each voxel, thus simplifying the 6D reconstruction problem to several 3D ones. Standard procedures for tomographic reconstruction can be directly adapted for this problem. The procedure is demonstrated by determining the distribution of the nanometric bone mineral particle thickness (T parameter) throughout a macroscopic 3D volume of bovine cortical bone. The T parameter maps display spatial patterns of particle thickness in fibrolamellar bone units. Spatial correlation between the mineral nano-structure and microscopic features reveals that the mineral particles are particularly thin in the vicinity of vascular channels.

Emergency Department Utilization for Emergency Conditions During COVID-19.

STUDY OBJECTIVE: We use a national emergency medicine clinical quality registry to describe recent trends in emergency department (ED) visitation overall and for select emergency conditions. METHODS: Data were drawn from the Clinical Emergency Department Registry, including 164 ED sites across 35 states participating in the registry with complete data from January 2019 through November 15, 2020. Overall ED visit counts, as well as specific emergency medical conditions identified by International Classification of Diseases, Tenth Revision, Clinical Modification code (myocardial infarction, cerebrovascular accident, cardiac arrest/ventricular fibrillation, and venous thromboembolisms), were tabulated. We plotted biweekly visit counts overall and across specific geographic regions. RESULTS: The largest declines in visit counts occurred early in the pandemic, with a nadir in April 46% lower than the 2019 monthly average. By November, overall ED visit counts had increased, but were 23% lower than prepandemic levels. The proportion of all ED visits that were for the select emergency conditions increased early in the pandemic; however, total visit counts for acute myocardial infarction and cerebrovascular disease have remained lower in 2020 compared with 2019. Despite considerable geographic and temporal variation in the trajectory of the coronavirus disease 2019 outbreak, the overall pattern of ED visits observed was similar across regions and time. CONCLUSION: The persistent decline in ED visits for these time-sensitive emergency conditions raises the concern that coronavirus disease 2019 may continue to impede patients from seeking essential care. Efforts thus far to encourage individuals with concerning signs and symptoms to seek emergency care may not have been sufficient.

Fair Play: Application of Normalized Scoring to Emergency Department Throughput Quality Measures in a National Registry.

STUDY OBJECTIVE: The measurement of emergency department (ED) throughput as a patient-centered quality measure is ubiquitous; however, marked heterogeneity exists between EDs, complicating comparisons for payment purposes. We evaluate 4 scoring methodologies for accommodating differences in ED visit volume and heterogeneity among ED groups that staff multiple EDs to improve the validity and "fairness" of ED throughput quality measurement in a national registry, with the goal of developing a volume-adjusted throughput measure that balances variation at the ED group level. METHODS: We conducted an ED group-level analysis using the 2017 American College of Emergency Physicians Clinical Emergency Data Registry data set, which included 548 ED groups inclusive of 889 unique EDs. We calculated ED throughput performance scores for each ED group by using 4 scoring approaches: plurality, simple average, weighted average, and a weighted standardized score. For comparison, ED groups (ie, taxpayer identification numbers) were grouped into 3 types: taxpayer identification numbers with only 1 ED; those with multiple EDs, but no ED with greater than 60,000 visits; and those with multiple EDs and at least 1 ED with greater than 60,000 visits. RESULTS: We found marked differences in the classification of ED throughput performance between scoring approaches. The weighted standardized score (z score) approach resulted in the least skewed and most uniform distribution across the majority of ED types, with a kurtosis of 12.91 for taxpayer identification numbers composed of 1 ED, 2.58 for those with multiple EDs without any supercenter, and 3.56 for those with multiple EDs with at least 1 supercenter, all lower than comparable scoring methods. The plurality and simple average scoring approaches appeared to disproportionally penalize ED groups that staff a single ED or multiple large-volume EDs. CONCLUSION: Application of a weighted standardized (z score) approach to ED throughput measurement resulted in a more balanced variation between different ED group types and reduced distortions in the length-of-stay measurement among ED groups staffing high-volume EDs. This approach may be a more accurate and acceptable method of profiling ED group throughput pay-for-performance programs.