Improved Utilization of Serial Testing Without Increased Admissions after Implementation of High-Sensitivity Troponin I: a Controlled Retrospective Cohort Study.

BACKGROUND: Guidelines recommend high-sensitivity cardiac troponin (hs-cTn) for diagnosis of myocardial infarction. Use of hs-cTn is increasing across the U.S., but questions remain regarding clinical and operational impact. Prior studies have had methodologic limitations and yielded conflicting results. OBJECTIVE: To evaluate the impact of transitioning from conventional cardiac troponin (cTn) to hs-cTn on test and resource utilization, operational efficiency, and patient safety. DESIGN: Retrospective cohort study in two New York City hospitals during the months before and after transition from conventional cTn to hs-cTn at Hospital 1. Hospital 2 served as a control. PARTICIPANTS: Consecutive emergency department (ED) patients with at least one cTn test resulted. INTERVENTION: Multifaceted hs-cTn intervention bundle, including a 0/2-h diagnostic algorithm for non-ST-elevation myocardial infarction, an educational bundle, enhancements to the electronic medical record, and nursing interventions to facilitate timed sample collection. MAIN MEASURES: Primary outcomes included serial cTn test utilization, probability of hospital admission, ED length of stay (LOS), and among discharged patients, probability of ED revisit within 72 h resulting in hospital admission. Multivariable regression models adjusted for age, sex, temporal trends, and interhospital differences. KEY RESULTS: The intervention was associated with increased use of serial cTn testing (adjusted risk difference: 48 percentage points, 95% CI: 45-50, P < 0.001) and ED LOS (adjusted geometric mean difference: 50 min, 95% CI: 50-51, P < 0.001). There was no significant association between the intervention and probability of admission (adjusted relative risk [aRR]: 0.99, 95% CI: 0.89-1.1, P = 0.81) or probability of ED revisit within 72 h resulting in admission (aRR: 1.1, 95% CI: 0.44-2.9, P = 0.81). CONCLUSIONS: Implementation of a hs-cTn intervention bundle was associated with an improvement in serial cTn testing, a neutral effect on probability of hospital admission, and a modest increase in ED LOS.

A Collaborative Emergency Medicine and Radiology Pulmonary Nodule Program: Identification of Associated Efficacy and Outcomes.

PURPOSE: Incidental radiologic findings are commonplace, but the episodic nature of emergency department (ED) care makes it challenging to ensure that patients obtain appropriate follow-up. Rates of follow-up range from 30% to 77%, with some studies demonstrating that more than 30% have no follow-up at all. The aim of this study is to describe and analyze the outcomes of a collaborative emergency medicine and radiology initiative to establish a formal workflow for the follow-up of pulmonary nodules identified during ED care. METHODS: A retrospective analysis was performed of patients referred to the pulmonary nodule program (PNP). Patients were divided into two categories: those with follow-up and those who do not have post-ED follow-up. The primary outcome was determining follow-up rates and outcomes, including patients referred for biopsy. The characteristics of patients who completed follow-up compared with those lost to follow-up were also examined. RESULTS: A total of 574 patients were referred to the PNP. Initial follow-up was established in 390 (69.1%); 30.8% were considered lost to follow-up, and more than half of these patients did not respond to initial contact. There were minimal differences in characteristics between patients in these two categories. Of the 259 patients who completed PNP follow-up, 26 were referred for biopsy (13%). CONCLUSIONS: The PNP provided effective transitions of care and potentially improved patient health care. Strategies to further enhance follow-up adherence will provide iterative improvement of the program. The PNP provides an implementation framework for post-ED pulmonary nodule follow-up in other health care systems and can be modified for use with other incidental diagnostic findings.

Social Determinants of Health Screening and Management: Lessons at a Large, Urban Academic Health System.

BACKGROUND: In October 2022 a multisite social determinants of health screening initiative was expanded across seven emergency departments of a large, urban hospital system. The aim of the initiative was to identify and address those underlying social needs that frequently interfere with a patient's health and well-being, often resulting in increased preventable system utilization. METHODS: Building on an established Patient Navigator Program, an existing screening process, and long-standing community-based partnerships, an interdisciplinary workgroup was formed to develop and implement the initiative. Technical and operational workflows were developed and implemented, and new staff members were hired and trained to screen and support patients with identified social needs. In addition, a community-based organization network was formed to explore and test social service referral strategies. RESULTS: Within the first five months of implementation, more than 8,000 patients were screened across seven emergency departments (EDs), of which 17.3% demonstrated a social need. Patient Navigators see between 5% and 10% of total nonadmitted ED patients. Among the three social needs of focus, housing presented as the greatest need (10.2%), followed by food (9.6%) and transportation (8.0%). Among patients identified as rising/high risk (728), 50.0% accepted support and are actively working with a Patient Navigator. CONCLUSION: There is growing evidence to support the link between unmet social needs and poor health outcomes. Health care systems are uniquely positioned to provide whole person care by identifying unresolved social needs and by building capacity within local community-based organizations to support those needs.

Laboratory Interventions to Eliminate Unnecessary Rapid COVID-19 Testing During a Reagent Shortage.

OBJECTIVES: In the fall of 2020, US medical centers were running out of rapid coronavirus disease 2019 (COVID-19) tests. The aim of this study is to evaluate the impact of an intervention to eliminate rapid test misutilization and to quantify the effect of the countermeasures to control rapid test ordering using a test utilization dashboard. METHODS: Interventions were made to preserve a severely limited supply of rapid diagnostic tests based on real-time analysis of a COVID-19 test utilization dashboard. This study is a retrospective observational study evaluating pre- and postintervention rates of appropriate rapid test use, reporting times, and cost/savings of resources used. RESULTS: This study included 14,462 severe acute respiratory syndrome coronavirus 2 reverse transcriptase polymerase chain reaction tests ordered during the study period. After the intervention, there was a 27.3% decrease in nonconforming rapid tests. Rapid test reporting time from laboratory receipt decreased by 1.47 hours. The number of days of rapid test inventory on hand increased by 39 days. CONCLUSIONS: Performing diagnostic test stewardship, informed by real-time review of a test utilization dashboard, was associated with significantly improved appropriate utilization of rapid diagnostic COVID-19 tests, improved reporting times, implied cost savings, and improved reagent inventory on hand, which facilitated the management of scarce resources during a pandemic.

In severe COVID-19, high-flow vs. conventional oxygen therapy reduced intubation and time to clinical recovery at 28 d.

SOURCE CITATION: Ospina-Tascón GA, Calderón-Tapia LE, García AF, et al. Effect of high-flow oxygen therapy vs conventional oxygen therapy on invasive mechanical ventilation and clinical recovery in patients with severe COVID-19: a randomized clinical trial. JAMA. 2021;326:2161-71. 34874419.

Emergency Department Utilization Among Maintenance Hemodialysis Patients: A Systematic Review.

RATIONALE & OBJECTIVE: To evaluate predictors of emergency department (ED) utilization by adult patients receiving hemodialysis (HD) and interventions to reduce ED utilization by HD patients. STUDY DESIGN: We searched Ovid MEDLINE, Ovid Embase, and the Cochrane Library for randomized controlled trials and observational studies published until April 2020. SETTING & PARTICIPANTS: We included studies that investigated predictors of ED utilization and/or interventions to reduce ED utilization in HD patients. We extracted data regarding the study design and study population and results regarding ED utilization from 38 studies using Excel software. ANALYTICAL APPROACH: We performed a narrative synthesis to group articles that investigated similar themes. RESULTS: 1,060 titles and abstracts were screened, of which 98 were selected for full-text review. In total, 38 studies met the inclusion criteria and underwent data extraction. Quality was high according to the Downs and Black tool, with 11 studies rated as good, 22 as fair, and 5 as poor. 34 studies described predictors of ED utilization, whereas 4 studies investigated interventions in which ED utilization was studied. Our narrative synthesis produced 8 concept subgroups in the core concepts of access to care, comorbid condition burden, and new health care models. Poor access to care and a high comorbid condition burden are associated with increased ED use. No ED-based interventions designed to reduce ED utilization were identified, but recent changes in health care systems, like the formation of End-Stage Renal Disease Seamless Care Organizations and greater involvement of palliative care services, are associated with improved outcomes. LIMITATIONS: Clinical heterogeneity and variability in the included studies precluded a meta-analysis. CONCLUSIONS: HD patients' high ED use is multifactorial. Further research is required to understand and predict ED utilization in this vulnerable population, which will facilitate the development of interventions to reduce avoidable ED use. PROSPERO REGISTRATION NUMBER: CRD42020196569.

Emergency Department Patient Navigator Program Demonstrates Reduction in Emergency Department Return Visits and Increase in Follow-up Appointment Adherence.

BACKGROUND: An estimated 56% of emergency department (ED) visits are avoidable. One motivation for return visits is patients' perception of poor access to timely outpatient care. Efforts to facilitate access may help reduce preventable ED visits. We aimed to analyze whether an ED patient navigator (PN) program improved adherence with outpatient appointments and reduced ED return visits. METHODS: We performed a retrospective analysis of patients evaluated and discharged from two EDs from October 2016 to December 2019. Using propensity score matching, an intervention case group was matched against two control groups - patients similar to the case group who presented either (1) pre-PN intervention or (2) post-PN intervention and did not receive intervention. The four outcomes included 72-h return ED visits, 30-day return ED visits, overall ED utilization, as well as the intervention group's adherence rates to PN-scheduled outpatient appointments. From 482,896 charts, propensity matching led to a total of 14,295 patients in each group. RESULTS: PN intervention decreased both acute and subacute ED return visits. Compared to both pre-PN and post-PN controls, navigated patients had a decrease in 72-h and 30-day return visits from 2% to 1% and 7% to 4% (p < 0.001) respectively. Navigated patients also had outpatient appointment adherence rates of 74-80% compared to the estimated national average of 25-56%. While there was no difference in mean ED utilization between the intervention group and pre-PN control group, mean ED utilization was found to be higher in the intervention group compared to the post-PN control group with 0.62 visits compared to 0.38 mean visits (p < 0.001). CONCLUSIONS: By facilitating access to post-ED care, PNs may reduce avoidable ED utilization and improve outpatient follow-up adherence. While overall ED utilization did not change, this may be due to the overall vulnerability of the navigated group which is the goal PN intervention group.

Deep significance clustering: a novel approach for identifying risk-stratified and predictive patient subgroups.

OBJECTIVE: Deep significance clustering (DICE) is a self-supervised learning framework. DICE identifies clinically similar and risk-stratified subgroups that neither unsupervised clustering algorithms nor supervised risk prediction algorithms alone are guaranteed to generate. MATERIALS AND METHODS: Enabled by an optimization process that enforces statistical significance between the outcome and subgroup membership, DICE jointly trains 3 components, representation learning, clustering, and outcome prediction while providing interpretability to the deep representations. DICE also allows unseen patients to be predicted into trained subgroups for population-level risk stratification. We evaluated DICE using electronic health record datasets derived from 2 urban hospitals. Outcomes and patient cohorts used include discharge disposition to home among heart failure (HF) patients and acute kidney injury among COVID-19 (Cov-AKI) patients, respectively. RESULTS: Compared to baseline approaches including principal component analysis, DICE demonstrated superior performance in the cluster purity metrics: Silhouette score (0.48 for HF, 0.51 for Cov-AKI), Calinski-Harabasz index (212 for HF, 254 for Cov-AKI), and Davies-Bouldin index (0.86 for HF, 0.66 for Cov-AKI), and prediction metric: area under the Receiver operating characteristic (ROC) curve (0.83 for HF, 0.78 for Cov-AKI). Clinical evaluation of DICE-generated subgroups revealed more meaningful distributions of member characteristics across subgroups, and higher risk ratios between subgroups. Furthermore, DICE-generated subgroup membership alone was moderately predictive of outcomes. DISCUSSION: DICE addresses a gap in current machine learning approaches where predicted risk may not lead directly to actionable clinical steps. CONCLUSION: DICE demonstrated the potential to apply in heterogeneous populations, where having the same quantitative risk does not equate with having a similar clinical profile.

Calculated decisions: ACEP ED COVID-19 management tool.

This supplement reviews the ACEP ED COVID-19 Management Tool, an emergency department classification and management tool for adult patients (aged ≥18 years) with suspected or confirmed SARS-CoV-2.

Socioeconomic variation in characteristics, outcomes, and healthcare utilization of COVID-19 patients in New York City.

OBJECTIVES: There is limited evidence on how clinical outcomes differ by socioeconomic conditions among patients with coronavirus disease 2019 (COVID-19). Most studies focused on COVID-19 patients from a single hospital. Results based on patients from multiple health systems have not been reported. The objective of this study is to examine variation in patient characteristics, outcomes, and healthcare utilization by neighborhood social conditions among COVID-19 patients. METHODS: We extracted electronic health record data for 23,300 community dwelling COVID-19 patients in New York City between March 1st and June 11th, 2020 from all care settings, including hospitalized patients, patients who presented to the emergency department without hospitalization, and patients with ambulatory visits only. Zip Code Tabulation Area-level social conditions were measured by the Social Deprivation Index (SDI). Using logistic regressions and Cox proportional-hazards models, we examined the association between SDI quintiles and hospitalization and death, controlling for race, ethnicity, and other patient characteristics. RESULTS: Among 23,300 community dwelling COVID-19 patients, 60.7% were from neighborhoods with disadvantaged social conditions (top SDI quintile), although these neighborhoods only account for 34% of overall population. Compared to socially advantaged patients (bottom SDI quintile), socially disadvantaged patients (top SDI quintile) were older (median age 55 vs. 53, P<0.001), more likely to be black (23.1% vs. 6.4%, P<0.001) or Hispanic (25.4% vs. 8.5%, P<0.001), and more likely to have chronic conditions (e.g., diabetes: 21.9% vs. 10.5%, P<0.001). Logistic and Cox regressions showed that patients with disadvantaged social conditions had higher risk for hospitalization (odds ratio: 1.68; 95% confidence interval [CI]: [1.46, 1.94]; P<0.001) and mortality (hazard ratio: 1.91; 95% CI: [1.35, 2.70]; P<0.001), adjusting for other patient characteristics. CONCLUSION: Substantial socioeconomic disparities in health outcomes exist among COVID-19 patients in NYC. Disadvantaged neighborhood social conditions were associated with higher risk for hospitalization, severity of disease, and death.

A predictive model of clinical deterioration among hospitalized COVID-19 patients by harnessing hospital course trajectories.

From early March through mid-May 2020, the COVID-19 pandemic overwhelmed hospitals in New York City. In anticipation of ventilator shortages and limited ICU bed capacity, hospital operations prioritized the development of prognostic tools to predict clinical deterioration. However, early experience from frontline physicians observed that some patients developed unanticipated deterioration after having relatively stable periods, attesting to the uncertainty of clinical trajectories among hospitalized patients with COVID-19. Prediction tools that incorporate clinical variables at one time-point, usually on hospital presentation, are suboptimal for patients with dynamic changes and evolving clinical trajectories. Therefore, our study team developed a machine-learning algorithm to predict clinical deterioration among hospitalized COVID-19 patients by extracting clinically meaningful features from complex longitudinal laboratory and vital sign values during the early period of hospitalization with an emphasis on informative missing-ness. To incorporate the evolution of the disease and clinical practice over the course of the pandemic, we utilized a time-dependent cross-validation strategy for model development. Finally, we validated our prediction model on an external validation cohort of COVID-19 patients served in a demographically distinct population from the training cohort. The main finding of our study is the identification of risk profiles of early, late and no clinical deterioration during the course of hospitalization. While risk prediction models that include simple predictors at ED presentation and clinical judgement are able to identify any deterioration vs. no deterioration, our methodology is able to isolate a particular risk group that remain stable initially but deteriorate at a later stage of the course of hospitalization. We demonstrate the superior predictive performance with the utilization of laboratory and vital sign data during the early period of hospitalization compared to the utilization of data at presentation alone. Our results will allow efficient hospital resource allocation and will motivate research in understanding the late deterioration risk group.

MyEDCare: Evaluation of a Smartphone-Based Emergency Department Discharge Process.

BACKGROUND: Poor comprehension and low compliance with post-ED (emergency department) care plans increase the risk of unscheduled ED return visits and adverse outcomes. Despite the growth of personal health records to support transitions of care, technological innovation's focus on the ED discharge process has been limited. Recent literature suggests that digital communication incorporated into post-ED care can improve patient satisfaction and care quality. OBJECTIVES: We evaluated the feasibility of utilizing MyEDCare, a text message and smartphone-based electronic ED discharge process at two urban EDs. METHODS: MyEDCare sends text messages to patients' smartphones at the time of discharge, containing a hyperlink to a Health Insurance Portability and Accountability Act (HIPAA)-compliant website, to deliver patient-specific ED discharge instructions. Content includes information on therapeutics, new medications, outpatient care scheduling, return precautions, as well as results of laboratory and radiological diagnostic testing performed in the ED. Three text messages are sent to patients: at the time of ED discharge with the nurse assistance for initial access of content, as well as 2 and 29 days after ED discharge. MyEDCare was piloted in a 9-month pilot period in 2019 at two urban EDs in an academic medical center. We evaluated ED return visits, ED staff satisfaction, and patient satisfaction using ED Consumer Assessment of Healthcare Providers and Systems (ED-CAHPS) patient satisfaction scores. RESULTS: MyEDCare enrolled 27,713 patients discharged from the two EDs, accounting for 43% of treat-and-release ED patients. Of the treat-and-release patients, 27% completed MyEDCare discharge process, accessing the online content at the time of ED discharge. Patients discharged via MyEDCare had fewer 72-hour, 9-day, and 30-day unscheduled return ED visits and reported higher satisfaction related to nursing care. CONCLUSION: EDs and urgent care facilities may consider developing a HIPAA-compliant, text message, and smartphone-based discharge process, including the transmission of test results, to improve patient-centered outcomes.

Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions.

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin-angiotensin-aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.

Testing-on-a-probe biosensors reveal association of early SARS-CoV-2 total antibodies and surrogate neutralizing antibodies with mortality in COVID-19 patients.

The association of mortality with the early humoral response to SARS-CoV-2 infection within the first few days after onset of symptoms (DAOS) has not been thoroughly investigated partly due to a lack of sufficiently sensitive antibody testing methods. Here we report two sensitive and automated testing-on-a-probe (TOP) biosensor assays for SARS-CoV-2 viral specific total antibodies (TAb) and surrogate neutralizing antibodies (SNAb), which are suitable for clinical use. The TOP assays employ an RBD-coated quartz probe using a Cy5-Streptavidin-polysacharide conjugate to improve sensitivity and minimize interference. Disposable cartridges containing pre-dispensed reagents require no liquid manipulation or fluidics during testing. The TOP-TAb assay exhibited higher sensitivity in the 0-7 DAOS window than a widely used FDA-EUA assay. The rapid and automated TOP-SNAb correlated well with two well-established SARS-CoV-2 virus neutralization tests. The clinical utility of the TOP assays was demonstrated by evaluating early antibody responses in 120 SARS-CoV-2 RT-PCR positive adult hospitalized patients. Higher TAb and SNAb positivity rates and more robust antibody responses at patient's initial hospital presentation were seen in inpatients who survived COVID-19 than those who died in the hospital. Survival analysis using the Cox Proportional Hazards Model showed that patients who had negative TAb and/or SNAb at initial hospital presentation were at a higher risk of in-hospital mortality. Furthermore, TAb and SNAb levels at presentation were inversely associated with SARS-CoV-2 viral load based on concurrent RT-PCR testing. Overall, the sensitive and automated TAb and SNAb assays allow the detection of early SARS-CoV-2 antibodies which associate with mortality.

Clinical informatics during the COVID-19 pandemic: Lessons learned and implications for emergency department and inpatient operations.

In response to a pandemic, hospital leaders can use clinical informatics to aid clinical decision making, virtualizing medical care, coordinating communication, and defining workflow and compliance. Clinical informatics procedures need to be implemented nimbly, with governance measures in place to properly oversee and guide novel patient care pathways, diagnostic and treatment workflows, and provider education and communication. The authors' experience recommends (1) creating flexible order sets that adapt to evolving guidelines that meet needs across specialties, (2) enhancing and supporting inherent telemedicine capability, (3) electronically enabling novel workflows quickly and suspending noncritical administrative or billing functions in the electronic health record, and (4) using communication platforms based on tiered urgency that do not compromise security and privacy.