Evaluation of the influenza-like illness case definition and the acute respiratory infection case definition in the diagnosis of influenza and COVID-19 in healthcare personnel.

BACKGROUND: To evaluate the influenza-like illness (ILI) and acute respiratory infection (ARI) case definitions in the diagnosis of COVID-19 and influenza in healthcare personnel (HCP). METHODS: We followed a cohort of 5752 HCP from November 2022 to May 2023. Symptomatic HCP were tested for SARS-CoV-2 and influenza by real-time PCR and/or rapid antigen detection test. ILI was defined as the sudden onset of ≥1 systemic symptom and ≥1 respiratory symptom. ARI was defined as the sudden onset of ≥1 respiratory symptom. Patients with respiratory symptoms were grouped either as ILI or as ARI based on the presence of fever, malaise, headache and/or myalgia. RESULTS: Overall, 466 ILI cases and 383 ARI cases occurred. HCP with ILI had an adjusted odds ratio (aOR) of 22.05 [95% confidence interval (CI): 6.23-78.04] to be diagnosed with influenza. HCP with ARI had an aOR of 2.70 (95% CI: 1.88-3.88) to be diagnosed with COVID-19. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ILI for influenza were 96.6%, 49.9%, 18.2%, and 99.2%, respectively. The sensitivity, specificity, PPV, and NPV of ARI for COVID-19 were 51.7%, 73.6%, 84.9%, and 34.8%, respectively. ILI and ARI had an overall correct classification rate of 89.6% and 74.1%, respectively. CONCLUSION: Our findings support the use of both ILI and ARI case definitions in the diagnosis of influenza and COVID-19 in HCP.

Colorado Insulin Copay Cap: Lower Out-Of-Pocket Payments, Increased Prescription Volume And Days' Supply.

In 2020, Colorado became the first state to cap out-of-pocket spending for insulin prescriptions, requiring fully insured health plans to cap out-of-pocket spending at $100 for a thirty-day supply. We provide the first evidence on the association of Colorado's Insulin Affordability Program with patient out-of-pocket spending, the amounts paid by plans per insulin prescription, and prescription filling. Using statewide claims data from the period 2018-21, we focused on the first two years that the copay cap law was in effect. We found that Colorado's Insulin Affordability Program was associated with significant reductions in out-of-pocket spending for insulin prescriptions, with the mean out-of-pocket payment per thirty-day supply falling nearly in half (from $62.59 to $35.64). Average plan payments increased slightly more ($31.39) than the decrease in out-of-pocket spending, as the total amount paid per prescription increased by about 1 percent. The average insulin user realized annual savings of $184, while the mean number of fills and the mean days' supply per year increased by 4.2 percent and 11.4 percent, respectively.

Health Outcome Changes in Individuals With Type 1 Diabetes After a State-Level Insulin Copayment Cap.

Importance: Many insulin users ration doses due to high out-of-pocket costs. Starting January 2020 with Colorado, 25 states and the District of Columbia enacted laws that cap insulin copayments. Objective: To estimate the association of Colorado's $100 copayment cap with out-of-pocket spending, medication adherence, and health care services utilization for diabetes-related complications. Design, Setting, and Participants: In this cohort study using Colorado's All-Payer Claims Database, nonelderly insulin users with type 1 diabetes were analyzed from January 2019 to December 2020. Outcome changes were compared in the prepolicy and postpolicy period among individuals continuously enrolled in state-regulated and non-state-regulated plans using difference-in-differences regressions. Subgroup analyses were conducted based on individuals' prepolicy spending (low: never ≥$100 out-of-pocket vs high: ≥$100 out-of-pocket cost at least once). Data were analyzed from June 2023 to May 2024. Exposure: Enrollment in state-regulated health insurance plans subject to the copayment cap legislation. Main Outcomes and Measures: Adherence to basal and bolus insulin treatment was evaluated using the proportion of days covered measure, out-of-pocket spending reflected prescription cost for a 30-day supply, and health care utilization for diabetes-related complications was identified using primary diagnosis codes from medical claims data. Results: The panel included 1629 individuals with type 1 diabetes (39 096 person-months), of which 924 were male (56.7%), 540 (33.1%) had 1 or more comorbidities, and the mean (SD) age was 40.6 (15.9) years. Overall, the copayment cap was associated with out-of-pocket spending declines of $17.3 (95% CI, -$27.3 to -$7.3) for basal and $11.5 (95% CI, -$24.7 to $1.7) for bolus insulins and increases in adherence of 3.2 (95% CI, 0.0 to 6.5) percentage points for basal and 3.3 (95% CI, 0.3 to 6.4) percentage points for bolus insulins. Changes in adherence were associated with increases within the prepolicy high-spending group (basal, 9.9; 95% CI, 2.4 to 17.4 percentage points; bolus, 13.0; 95% CI, 5.1 to 20.9 percentage points). The policy was also associated with a mean reduction of -0.09 (95% CI, -0.16 to -0.02) medical claims for diabetes-related complications per person per month among high spenders, a 30% decrease. Conclusions and Relevance: In this cohort study of Colorado's insulin copayment cap among individuals with type 1 diabetes, the policy was associated with an overall decline in out-of-pocket spending, an increase in medication adherence, and a decline in claims for diabetes-related complications only among insulin users who spent more than $100 in the prepolicy period at least once.

Effectiveness of COVID-19 booster vaccination, morbidity and absenteeism among healthcare personnel during the 2022-2023 season dominated by Omicron BA.5 and BA.2 subvariants.

AIM: We assessed the vaccination effectiveness (VE) of a COVID-19 booster vaccine dose and the association between morbidity and absenteeism with COVID-19 booster vaccine receipt among healthcare personnel (HCP) in 2022-2023 in Greece. METHODS: We followed 5752 HCP from November 14, 2022 through May 28, 2023 for episodes of absenteeism. Absenteeism for non-infectious causes, pregnancy leave, or annual leave was not recorded. Full vaccination was defined as a primary vaccination series plus one booster dose within the past six months. Multivariable regression models were used to estimate the association of full COVID-19 vaccination with the outcomes of interest. RESULTS: A total of 1029 episodes of absenteeism occurred during the study period (17.9 episodes per 100 HCP). The mean duration of absence per episode was 5.2 days, and the total duration of absence was 5237 days. COVID-19 was diagnosed in 736 (12.8 %) HCP, asymptomatic SARS-CoV-2 infection in 62 (1.1 %) HCP, and influenza in 95 (1.7 %) HCP. Overall, COVID-19, influenza, and asymptomatic SARS-CoV-2 infection accounted for 71.5 %, 9.2 %, and 6.0 % of episodes of absenteeism, respectively. Multivariable regression models indicated that fully vaccinated HCP were absent from work for shorter periods [adjusted odds ratio (aOR): 0.42; 95 % confidence interval (CI): 0.21-0.83], were less likely to develop COVID-19 [aOR: 0.37; 95 % CI: 0.17-0.81)], and were more likely to develop an asymptomatic SARS-CoV-2 infection (aOR: 5.90; 95 % CI: 1.27-27.45). The adjusted full VE against COVID-19 was 62.8 % (95 % CI: 18.6 %-83.0 %). CONCLUSIONS: COVID-19 remains a significant cause of morbidity and absenteeism among HCP. Full COVID-19 vaccination status conferred significant protection against COVID-19 and was associated with shorter periods of absence from work.

Comparison of morbidity and absenteeism due to COVID-19 and seasonal influenza in a large cohort of health care personnel in the 2022 to 2023 season.

BACKGROUND: To compare the morbidity and work absenteeism associated with coronavirus disease 2019 (COVID-19) and influenza among health care personnel (HCP) in 2022 to 2023. METHODS: We followed 5,752 hospital-based HCP in Greece from November 14, 2022 through May 28, 2023. Symptomatic HCP was tested for SARS-CoV-2 and influenza by real-time polymerase chain reaction and/or rapid antigen detection test. The association between the duration of absenteeism and the type of disease was estimated by multivariable regression models. RESULTS: A total of 734 COVID-19 cases and 93 influenza cases were studied. The mean duration of absence per COVID-19 case was 5.8days compared with a mean of absence of 3.6days per influenza case (P value <.001). Overall, COVID-19 accounted for 4,245days missed during the study period compared with 333days missed due to influenza. Multivariable regression estimates indicated that HCP with COVID-19 had 1.91 more days of absenteeism (95% confidence interval 1.67-2.15) compared with those with influenza, on average. CONCLUSIONS: As SARS-CoV-2 becomes endemic, COVID-19 remains the prevalent cause of morbidity and absenteeism among HCP, accounting for considerably more workdays missed compared with influenza. HCP should be up-to-date with COVID-19 booster vaccinations and annual influenza vaccination in order to protect them as well as health care systems from HCP absenteeism.

Hospital Readmissions in Patients Supported with Durable Centrifugal-Flow Left Ventricular Assist Devices.

Background: Centrifugal-flow left ventricular assist devices (CF-LVADs) have improved morbidity and mortality for their recipients. Hospital readmissions remain common, negatively impacting quality of life and survival. We sought to identify risk factors associated with hospital readmissions among patients with CF-LVADs. Methods: Consecutive patients receiving a CF-LVAD between February 2011 and March 2021 were retrospectively evaluated using prospectively maintained institutional databases. Hospital readmissions within three years post-LVAD implantation were dichotomized into heart failure (HF)/LVAD-related or non-HF/LVAD-related readmissions. Multivariable Cox regression models augmented using a machine learning algorithm, the least absolute shrinkage and selection operator (LASSO) method, for variable selection were used to estimate associations between HF/LVAD-related readmissions and pre-, intra- and post-operative clinical variables. Results: A total of 204 CF-LVAD recipients were included, of which 138 (67.7%) had at least one HF/LVAD-related readmission. HF/LVAD-related readmissions accounted for 74.4% (436/586) of total readmissions. The main reasons for HF/LVAD-related readmissions were major bleeding, major infection, HF exacerbation, and neurological dysfunction. Using pre-LVAD variables, HF/LVAD-related readmissions were associated with substance use, previous cardiac surgery, HF duration, pre-LVAD inotrope dependence, percutaneous LVAD/VA-ECMO support, LVAD type, and the left ventricular ejection fraction in multivariable analysis (Harrell's concordance c-statistic; 0.629). After adding intra- and post-operative variables in the multivariable model, LVAD implant hospitalization length of stay was an additional predictor of readmission. Conclusions: Using machine learning-based techniques, we generated models identifying pre-, intra-, and post-operative variables associated with a higher likelihood of rehospitalizations among patients on CF-LVAD support. These models could provide guidance in identifying patients with increased readmission risk for whom clinical strategies to mitigate this risk may further improve LVAD recipient outcomes.

Waning effectiveness of mRNA COVID-19 vaccines against inpatient and emergency department encounters.

In the United States, most real-world estimates of COVID-19 vaccine effectiveness are based on data drawn from large health systems or sentinel populations. More data is needed to understand how the benefits of vaccination may vary across US populations with disparate risk profiles and policy contexts. We aimed to provide estimates of mRNA COVID-19 vaccine effectiveness against moderate and severe outcomes of COVID-19 based on state population-level data sources. Using statewide integrated administrative and clinical data and a test-negative case-control study design, we assessed mRNA COVID-19 vaccine effectiveness against SARS-CoV-2-related hospitalizations and emergency department visits among adults in South Carolina. We presented estimates of vaccine effectiveness at discrete time intervals for adults who received one, two or three doses of mRNA COVID-19 vaccine compared to adults who were unvaccinated. We also evaluated changes in vaccine effectiveness over time (waning) for the overall sample and in subgroups defined by age. We showed that while two doses of mRNA COVID-19 vaccine were initially highly effective, vaccine effectiveness waned as time elapsed since the second dose. Compared to protection against hospitalizations, protection against emergency department visits was found to wane more sharply. In all cases, a third dose of mRNA COVID-19 vaccine conferred significant gains in protection relative to waning protection after two doses. Further, over more than 120 days of follow-up, the data revealed relatively limited waning of vaccine effectiveness after a third dose of mRNA COVID-19 vaccine.

Effectiveness of COVID-19 vaccination against school absenteeism in children and adolescents hospitalized with COVID-19.

BACKGROUND: COVID-19 vaccination has been recommended for children to protect them and to enable in-person educational and social activities. METHODS: We estimated COVID-19 vaccination effectiveness (VE) against school absenteeism in children 5-17 years old hospitalized from September 1, 2021 through May 31, 2023. Full vaccination was defined as two vaccine doses. RESULTS: We studied 231 children admitted to hospital with COVID-19, including 206 (89.2 %) unvaccinated/partially vaccinated and 25 (10.8 %) fully vaccinated. Unvaccinated/partially vaccinated children were absent from school for longer periods compared to fully vaccinated children (median absence: 14 versus 10 days; p-value = 0.05). Multivariable regression showed that full COVID-19 vaccination was associated with fewer days of absence compared to no/partial vaccination on average (adjusted relative risk: 0.77; 95 % CI: 0.61 to 0.98). COVID-19 VE was 50.7 % (95 % CI: -11.3 % to 78.2 %) for school absenteeism above the median duration of absenteeism. CONCLUSIONS: Full COVID-19 vaccination conferred protection against school absenteeism in hospitalized school-aged children with COVID-19.

Concordance in Medical Urgency Classification of Discharge Diagnoses and Reasons for Visit.

Importance: Current policies to divert emergency department (ED) visits for less medically urgent conditions to more cost-effective settings rely on retrospective adjudication of discharge diagnoses. However, patients present to the ED with concerns, making it challenging for clinicians. Objective: To characterize ED visits based on the medical urgency of the presenting reasons for visit and to explore the concordance between discharge diagnoses and reasons for visit. Design, Setting, and Participants: In this retrospective, cross-sectional study, a nationwide sample of ED visits by adults (aged ≥18 years) in the US from the 2018 and 2019 calendar years' ED data of the National Hospital Ambulatory Medical Care Survey was used. An algorithm to probabilistically assign ED visits into medical urgency categories based on the presenting reason for visit was developed. A 3-step, look-back method was applied using an updated version of the New York University ED algorithm, and a map of all possible discharge diagnoses to the same reasons for visit was developed. Analyses were conducted in July and August 2023. Main Outcomes and Measures: The main outcome was probabilistic medical urgency classification of reasons for visits and discharge diagnoses and their concordance. Results: We analyzed 27 068 ED visits (mean age, 48.2% years [95% CI, 47.5%-48.9% years]) representing 190.7 million visits nationwide. Women (mean, 57.0% [95% CI, 55.9%-58.1%]) and patients with public health insurance coverage, including Medicare (mean, 24.9% [95% CI, 21.9%-28.0%]) and Medicaid (mean, 25.1% [95% CI, 21.0%-29.2%]), accounted for the largest share of ED visits, and a mean of 13.2% (95% CI, 11.4%-15.0%) of all visits resulted in a hospital admission. Overall, about 38.5% and 53.9% of all ED visits were classified with 100% and 75% probabilities, respectively, as injury related, emergency care needed, emergent but primary care treatable, nonemergent, or mental health or substance use disorders related based on discharge diagnosis compared with 0.4% and 12.4%, respectively, of all encounters based on patients' reason for visit. Among discharge diagnoses assigned with high certainty to only 1 urgency category using the New York University ED algorithm, between 38.0% (95% CI, 36.3%-39.6%) and 57.4% (95% CI, 56.0%-58.8%) aligned with the probabilistic categorical assignments of their corresponding reasons for visit. Conclusions and Relevance: In this cross-sectional study of 190.7 million ED visits among adults aged 18 years or older, a smaller percentage of reasons for visit could be prospectively categorized with high accuracy to a specific medical urgency category compared with all visits based on discharge diagnoses, and a limited concordance between reasons for visit and discharge diagnoses was found. Alternative methods are needed to identify the medical necessity of ED encounters more accurately.

Machine Learning Multicenter Risk Model to Predict Right Ventricular Failure After Mechanical Circulatory Support: The STOP-RVF Score.

Importance: The existing models predicting right ventricular failure (RVF) after durable left ventricular assist device (LVAD) support might be limited, partly due to lack of external validation, marginal predictive power, and absence of intraoperative characteristics. Objective: To derive and validate a risk model to predict RVF after LVAD implantation. Design, Setting, and Participants: This was a hybrid prospective-retrospective multicenter cohort study conducted from April 2008 to July 2019 of patients with advanced heart failure (HF) requiring continuous-flow LVAD. The derivation cohort included patients enrolled at 5 institutions. The external validation cohort included patients enrolled at a sixth institution within the same period. Study data were analyzed October 2022 to August 2023. Exposures: Study participants underwent chronic continuous-flow LVAD support. Main Outcome and Measures: The primary outcome was RVF incidence, defined as the need for RV assist device or intravenous inotropes for greater than 14 days. Bootstrap imputation and adaptive least absolute shrinkage and selection operator variable selection techniques were used to derive a predictive model. An RVF risk calculator (STOP-RVF) was then developed and subsequently externally validated, which can provide personalized quantification of the risk for LVAD candidates. Its predictive accuracy was compared with previously published RVF scores. Results: The derivation cohort included 798 patients (mean [SE] age, 56.1 [13.2] years; 668 male [83.7%]). The external validation cohort included 327 patients. RVF developed in 193 of 798 patients (24.2%) in the derivation cohort and 107 of 327 patients (32.7%) in the validation cohort. Preimplant variables associated with postoperative RVF included nonischemic cardiomyopathy, intra-aortic balloon pump, microaxial percutaneous left ventricular assist device/venoarterial extracorporeal membrane oxygenation, LVAD configuration, Interagency Registry for Mechanically Assisted Circulatory Support profiles 1 to 2, right atrial/pulmonary capillary wedge pressure ratio, use of angiotensin-converting enzyme inhibitors, platelet count, and serum sodium, albumin, and creatinine levels. Inclusion of intraoperative characteristics did not improve model performance. The calculator achieved a C statistic of 0.75 (95% CI, 0.71-0.79) in the derivation cohort and 0.73 (95% CI, 0.67-0.80) in the validation cohort. Cumulative survival was higher in patients composing the low-risk group (estimated <20% RVF risk) compared with those in the higher-risk groups. The STOP-RVF risk calculator exhibited a significantly better performance than commonly used risk scores proposed by Kormos et al (C statistic, 0.58; 95% CI, 0.53-0.63) and Drakos et al (C statistic, 0.62; 95% CI, 0.57-0.67). Conclusions and Relevance: Implementing routine clinical data, this multicenter cohort study derived and validated the STOP-RVF calculator as a personalized risk assessment tool for the prediction of RVF and RVF-associated all-cause mortality.

Determinants of Persistent, Multi-Year, Frequent Emergency Department Use Among Children and Young Adults in Three US States.

OBJECTIVE: This study examines the factors associated with persistent, multi-year, and frequent emergency department (ED) use among children and young adults. METHODS: We conducted a retrospective secondary analysis using the 2012-2017 Healthcare Cost and Utilization Project State Emergency Department Databases for children and young adults aged 0-19 who visited any ED in Florida, Massachusetts, and New York. We estimated the association between persistent frequent ED use and individuals' characteristics using multivariable logistic regression models. RESULTS: Among 1.3 million patients with 1.8 million ED visits in 2012, 2.9% (37,558) exhibited frequent ED use (≥4 visits in 2012) and accounted for 10.2% (181,138) of all ED visits. Longitudinal follow-up of frequent ED users indicated that 15.4% (5770) remained frequent users periodically over the next 1 or 2 years, while 2.2% (831) exhibited persistent frequent use over the next 3-5 years. Over the 6-year study period, persistent frequent users had 31,551 ED visits at an average of 38.0 (standard deviation = 16.2) visits. Persistent frequent ED use was associated with higher intensity of ED use in 2012, public health insurance coverage, inconsistent health insurance coverage over time, residence in non-metropolitan and lower-income areas, multimorbidity, and more ED visits for less medically urgent conditions. CONCLUSIONS: Clinicians and policymakers should consider the diverse characteristics and needs of pediatric persistent frequent ED users compared to broader definitions of frequent users when designing and implementing interventions to improve health outcomes and contain ED visit costs.

Association of the affordable care act with racial and ethnic disparities in uninsured emergency department utilization.

BACKGROUND: Disparities in uninsured emergency department (ED) use are well documented. However, a comprehensive analysis evaluating how the Affordable Care Act (ACA) may have reduced racial and ethnic disparities is lacking. The goal was to assess the association of the ACA with racial and ethnic disparities in uninsured ED use. METHODS: This study used data from the Healthcare Cost and Utilization Project (HCUP) State Emergency Department Databases (SEDD) for Georgia, Florida, Massachusetts, and New York from 2011 to 2017. Participants include non-elderly adults between 18 and 64 years old. Outcomes include uninsured rates of ED visits by racial and ethnic groups and stratified by medical urgency using the New York University ED algorithm. Visits were aggregated to year-quarter ED visits per 100,000 population and stratified for non-Hispanic White, non-Hispanic Black, and Hispanic non-elderly adults. Quasi-experimental difference-in-differences and triple differences regression analyses to identify the effect of the ACA and the separate effect of the Medicaid expansion were used comparing uninsured ED visits by race and ethnicity groups pre-post ACA. RESULTS: The ACA was associated with a 14% reduction in the rate of uninsured ED visits per 100,000 population (from 10,258 pre-ACA to 8,877 ED visits per 100,000 population post-ACA) overall. The non-Hispanic Black compared to non-Hispanic White disparity decreased by 12.4% (-275.1 ED visits per 100,000) post-ACA. About 60% of the decline in the Black-White disparity was attributed to disproportionate declines in ED visit rates for conditions classified as not-emergent (-93.2 ED visits per 100,000), and primary care treatable/preventable (-64.1 ED visits per 100,000), while the disparity in ED visit rates for injuries and not preventable conditions also declined (-106.57 ED visits per 100,000). All reductions in disparities were driven by the Medicaid expansion. No significant decrease in Hispanic-White disparity was observed. CONCLUSIONS: The ACA was associated with fewer uninsured ED visits and reduced the Black-White ED disparity, driven mostly by a reduction in less emergent ED visits after the ACA in Medicaid expansion states. Disparities between Hispanic and non-Hispanic White adults did not decline after the ACA. Despite the positive momentum of declining disparities in uninsured ED visits, disparities, especially among Black people, remain.

Association of Medicaid expansion with dental emergency department visits overall and by states' Medicaid dental benefits provision.

BACKGROUND: Evidence on the association of Medicaid expansion with dental emergency department (ED) utilization is limited, while even less is known on policy-related changes in dental ED visits by Medicaid programs' dental benefits generosity. The objective of this study was to estimate the association of Medicaid expansion with changes in dental ED visits overall and by states' benefits generosity. METHODS: We used the Healthcare Cost and Utilization Project's Fast Stats Database from 2010 to 2015 for non-elderly adults (19 to 64 years of age) across 23 States, 11 of which expanded Medicaid in January 2014 while 12 did not. Difference-in-differences regression models were used to estimate changes in dental-related ED visits overall and further stratified by states' dental benefit coverage in Medicaid between expansion and non-expansion States. RESULTS: After 2014, dental ED visits declined by 10.9 [95% confidence intervals (CI): -18.5 to -3.4] visits per 100,000 population quarterly in states that expanded Medicaid compared to non-expansion states. However, the overall decline was concentrated in Medicaid expansion states with dental benefits. In particular, among expansion states, dental ED visits per 100,000 population declined by 11.4 visits (95% CI: -17.9 to -4.9) quarterly in states with dental benefits in Medicaid compared to states with emergency-only or no dental benefits. Significant differences between non-expansion states by Medicaid's dental benefits generosity were not observed [6.3 visits (95% CI: -22.3 to 34.9)]. CONCLUSIONS: Our findings suggest the need to strengthen public health insurance programs with more generous dental benefits to curtail costly dental ED visits.

Rural-Urban Disparities in Hospital Admissions and Mortality Among Patients with COVID-19: Evidence from South Carolina from 2021 to 2022.

Although rural communities have been hard-hit by the COVID-19 pandemic, there is limited evidence on COVID-19 outcomes in rural America using up-to-date data. This study aimed to estimate the associations between hospital admissions and mortality and rurality among COVID-19 positive patients who sought hospital care in South Carolina. We used all-payer hospital claims, COVID-19 testing, and vaccination history data from January 2021 to January 2022 in South Carolina. We included 75,545 hospital encounters within 14 days after positive and confirmatory COVID-19 testing. Associations between hospital admissions and mortality and rurality were estimated using multivariable logistic regressions. About 42% of all encounters resulted in an inpatient hospital admission, while hospital-level mortality was 6.3%. Rural residents accounted for 31.0% of all encounters for COVID-19. After controlling for patient-level, hospital, and regional characteristics, rural residents had higher odds of overall hospital mortality (Adjusted Odds Ratio - AOR = 1.19, 95% Confidence Intervals - CI = 1.04-1.37), both as inpatients (AOR = 1.18, 95% CI = 1.05-1.34) and as outpatients (AOR = 1.63, 95% CI = 1.03-2.59). Sensitivity analyses using encounters with COVID-like illness as the primary diagnosis only and encounters from September 2021 and beyond - a period when the Delta variant was dominant and booster vaccination was available - yielded similar estimates. No significant differences were observed in inpatient hospitalizations (AOR = 1.00, 95% CI = 0.75-1.33) between rural and urban residents. Policymakers should consider community-based public health approaches to mitigate geographic disparities in health outcomes among disadvantaged population subgroups.

Emergency department utilization and disposition outcomes by pediatric patients with cancer in Maryland and New York from 2013 to 2017.

BACKGROUND: Pediatric patients with cancer commonly seek emergency department (ED) care, yet there is limited evidence on ED utilization patterns and disposition outcomes among these patients. METHODS: Retrospective analysis of the Healthcare Cost and Utilization Project State Emergency Department Databases and State Inpatient Databases for Maryland and New York from 2013 to 2017. We compared ED visits and disposition outcomes for 5.8 million pediatric patients (<18 years old) with and without cancer, and used multivariable regressions to estimate associations between the number of ED visits, hospital (inpatient) admissions through the ED, and ED or inpatient mortality and sociodemographic and clinical factors within the cancer cohort. RESULTS: Pediatric patients with cancer had more ED visits per year on average (2.4 vs. 1.5, p < .001), higher shares of admissions (56.8% vs. 6.6%, p < .001) and mortality (1.2% vs. 0.1%, p < .001) compared to those without cancer. Among patients with cancer, uninsured pediatric patients had fewer ED visits and lower risk of admission to a hospital through the ED compared to those with Medicaid coverage (total visits: incidence rate ratio [IRR]: 0.82, 95% confidence intervals [CI]: 0.75-0.90; admission: IRR: 0.75, 95% CI: 0.65-0.86). Mortality risks were higher for pediatric patients with cancer residing in areas with the lowest median household income, and with no health insurance coverage (IRR: 2.81, 95% CI: 1.21-6.51) compared to Medicaid. CONCLUSIONS: Our findings emphasize the importance of enhancing health insurance coverage policies and social services for pediatric patients with cancer and their families to address clinical and nonclinical needs.

Child and Adolescent Anxiety and Depression Prior to and During the COVID-19 Pandemic in the United States.

Childhood anxiety and depression have been increasing for years, and evidence suggests the COVID-19 pandemic has exacerbated this trend. However, research has examined anxiety and depression primarily as exclusive conditions, overlooking comorbidity. This study examined relationships between the COVID-19 pandemic and anxiety and depression to clarify risk factors for singular and comorbid anxiety and depression in children. Using 2018-2019 and 2020-2021 samples from the National Survey of Children's Health, a nationally representative survey of children aged 0-17 in the United States, associations between the COVID-19 pandemic and child anxiety and depression were examined via survey-weights' adjusted bivariate and multiple regression analyses, controlling for demographic characteristics. The COVID-19 pandemic was associated with higher odds of having comorbid anxiety and depression but not singular anxiety or depression. Female sex, older age, having special healthcare needs, more frequent inability to cover basic needs on family income, and poorer caregiver mental health were associated with having been diagnosed with singular and comorbid anxiety and depression. Children that witnessed or were victims of violence in the neighborhood were also more likely to have comorbid anxiety and depression. Implications for prevention, intervention, and policy are discussed.

Adult Cancer-Related Emergency Department Utilization: An Analysis of Trends and Outcomes From Emergency Departments in Maryland and New York.

PURPOSE: To explore emergency department (ED) visits by adults with cancer and to estimate associations between inpatient admissions through the ED and mortality with sociodemographic and clinical factors within this cohort. METHODS: We conducted a retrospective, pooled, cross-sectional analysis of the Healthcare Cost and Utilization State Emergency Department Databases and State Inpatient Databases for Maryland and New York from January 2013 to December 2017. We examined inpatient admissions through the ED and mortality using frequencies. Among patients with cancer, multivariable regressions were used to estimate sociodemographic and clinical factors associated with inpatient admissions and outpatient ED and inpatient mortality overall. RESULTS: Among 22.7 million adult ED users, 1.3 million (5.7%) had at least one cancer-related diagnosis. ED visit rates per 100,000 population increased annually throughout the study period for patients with cancer and were 9.9% higher in 2017 compared with 2013 (2013: 303.5; 2017: 333.6). Having at least one inpatient admission (68.7% v 20.5%; P < .001) and inpatient or ED mortality (6.5% v 1.0%; P < .001) were higher among ED users with cancer compared with those without. Among patients with cancer, being uninsured (adjusted odds ratio, 0.52; 95% CI, 0.44 to 0.62) compared with having Medicare coverage and non-Hispanic Black (adjusted odds ratio, 0.86; 95% CI, 0.80 to 0.92) compared with non-Hispanic White were associated with decreased odds of inpatient admissions. In contrast, patients with cancer without health insurance, non-Hispanic Black patients, and residents of nonlarge metropolitan areas and of areas with lower household incomes had increased odds of mortality. CONCLUSION: High inpatient admissions through the ED and mortality among adult patients with cancer, coupled with an increase in cancer-related ED visit rates and observed disparities in outcomes, highlight the need to improve access to oncologic services to contain ED use and improve care for patients with cancer.

Effectiveness of full (booster) COVID-19 vaccination against severe outcomes and work absenteeism in hospitalized patients with COVID-19 during the Delta and Omicron waves in Greece.

AIM: We estimated vaccine effectiveness (VE) of full (booster) vaccination against severe outcomes in hospitalized COVID-19 patients during the Delta and Omicron waves. METHODS: The study extended from November 15, 2021 to April 17, 2022. Full vaccination was defined as a primary vaccination plus a booster ≥ 6 months later. RESULTS: We studied 1138 patients (mean age: 66.6 years), of whom 826 (72.6 %) had ≥ 1 comorbidity. Of the 1138 patients, 75 (6.6 %) were admitted to intensive care unit (ICU), 64 (5.6 %) received mechanical ventilation, and 172 (15.1 %) died. There were 386 (33.9 %) fully vaccinated, 172 (15.1 %) partially vaccinated, and 580 (51 %) unvaccinated patients. Unvaccinated patients were absent from work for longer periods compared to partially or fully vaccinated patients (mean absence of 20.1 days versus 12.3 and 17.3 days, respectively; p-value = 0.03). Compared to unvaccinated patients, fully vaccinated patients were less likely to be admitted to ICU [adjusted relative risk (ARR: 0.49; 95 % CI: 0.29-0.84)], mechanically ventilated (ARR: 0.43; 95 % CI: 0.23-0.80), and die (ARR: 0.57; 95 % CI: 0.42-0.78), while they were hospitalized for significantly shorter periods (ARR: 0.79; 95 % CI: 0.70-0.89). The adjusted full VE was 48.8 % (95 % CI: 42.7 %-54.9 %) against ICU admission, 55.4 % (95 % CI: 52.0 %-56.2 %) against mechanical ventilation, and 22.6 % (95 % CI: 7.4 %-34.8 %) against death. For patients with ≥ 3 comorbidities, VE was 56.2 % (95 % CI: 43.9 %-67.1 %) against ICU admission, 60.2 % (95 % CI: 53.7 %-65.4 %) against mechanical ventilation, and 43.9 % (95 % CI: 19.9 %-59.7 %) against death. CONCLUSIONS: Full (booster) COVID-19 vaccination conferred protection against severe outcomes, prolonged hospitalization, and prolonged work absenteeism.