Racial and Ethnic Disparities in Hospital Admissions from COVID-19: Determining the Impact of Neighborhood Deprivation and Primary Language

The Impact of Language on Hospital Outcomes for COVID-19 Patients: A Study of Non-English Speaking Hispanic Patients

BACKGROUND

The COVID-19 pandemic has highlighted and exacerbated health inequities, as demonstrated by the disproportionate rates of infection, hospitalization, and death in marginalized racial and ethnic communities. Although non-English speaking (NES) patients have substantially higher rates of COVID-19 positivity than other groups, research has not yet examined primary language, as determined by the use of interpreter services, and hospital outcomes for patients with COVID-19.

METHODS

Data were collected from 1,770 patients with COVID-19 admitted to an urban academic health medical center in the Chicago, Illinois area from March 2020 to April 2021. Patients were categorized as non-Hispanic White, non-Hispanic Black, NES Hispanic, and English-speaking (ES) Hispanic using NES as a proxy for English language proficiency. Multivariable logistic regression was used to compare the predicted probability for each outcome (i.e., ICU admission, intubation, and in-hospital death) by race/ethnicity.

RESULTS

After adjusting for possible confounders, NES Hispanic patients had the highest predicted probability of ICU admission (p-value < 0.05). Regarding intubation and in-hospital death, NES Hispanic patients had the highest probability, although statistical significance was inconclusive, compared to White, Black, and ES Hispanic patients.

CONCLUSIONS

Race and ethnicity, socioeconomic status, and language have demonstrated disparities in health outcomes. This study provides evidence for heterogeneity within the Hispanic population based on language proficiency that may potentially further contribute to disparities in COVID-19-related health outcomes within marginalized communities.

Examining trends in emergency medicine journals' publications about racism

OBJECTIVE

In recent years, the academic medicine community has produced numerous statements and calls to action condemning racism. Though health equity work examining health disparities has expanded, few studies specifically name racism as an operational construct. As emergency departments serve a high proportion of patients with social and economic disadvantage rooted in structural racism, it is critically important that racism be a focus of our academic discourse. This study examines the frequency at which four prominent emergency medicine journals, Annals of Emergency Medicine, Academic Emergency Medicine, the American Journal of Emergency Medicine, and the Western Journal of Emergency Medicine, publish on health disparities and racism.

METHODS

This is a descriptive analysis measuring the frequency of publications on health disparities and racism in U.S.-based emergency medicine journals from 2014 to 2021. The search strategies for the concepts of "racism" and "health disparities" used a combination of MeSH and keywords. These search strategies were developed based on prior literature and the MEDLINE/PubMed Health Disparities and Minority Health Search Strategy. Articles identified through the PubMed search were then reviewed by two authors for final inclusion.

RESULTS

Since 2014, a total of 6248 articles were published by the four emergency medicine journals over the 8-year study period. Of those, 82 research papers that focused on health disparities were identified and only 16 that focused on racism. Most emergency medicine publications on racism and health disparities were in 2021.

CONCLUSIONS

Our findings suggest that the national discourse on racism and calls to action within emergency medicine were followed by an increase in publications on health disparities and racism. Continued investigation is needed to evaluate these trends moving forward.

Impact of Language Barriers on Outcomes and Experience of COVID-19 Patients Hospitalized in Quebec, Canada, During the First Wave of the Pandemic

Language barriers (LB) contribute to coronavirus disease 2019 (COVID-19) health inequities. People with LB were more likely to be SARS-CoV-2 positive despite lower testing and had higher rates of hospitalization. Data on hospital outcomes among immigrants with LB, however, are limited. We aimed to investigate the clinical outcomes of hospitalized COVID-19 cases by LB, immigration status, ethnicity, and access to COVID-19 health information and services prior to admission. Adults with laboratory-confirmed community-acquired COVID-19 hospitalized from March 1 to June 30, 2020, at four tertiary-care hospitals in Montréal, Quebec, Canada were included. Demographics, comorbidities, immigration status, country of birth, ethnicity, presence of LB, and hospital outcomes (ICU admission and death) were obtained through a chart review. Additional socio-economic and access to care questions were obtained through a phone survey. A Fine-Gray competing risk subdistribution hazards model was used to estimate the risk of ICU admission and in-hospital death by immigrant status, region of birth and LB Among 1093 patients, 622 (56.9%) were immigrants and 101 (16.2%) of them had a LB. One third (36%) of immigrants with LB did not have access to an interpreter during hospitalization. Admission to ICU and in-hospital mortality were not significantly different between groups. Prior to admission, one third (14/41) of immigrants with LB had difficulties accessing COVID-19 information in their mother tongue and one third (9/27) of non-white immigrants with a LB had difficulties accessing COVID-19 services. Immigrants with LB were inequitably affected by the first wave of the pandemic in Quebec, Canada. In our study, a large proportion had difficulties accessing information and services related to COVID-19 prior to admission, which may have increased SARS-CoV-2 exposure and hospitalizations. After hospitalization, a large proportion did not have access to interpreters. Providing medical information and care in the language of preference of increasing diverse populations in Canada is important for promoting health equity.

Neighborhood Factors Associated with COVID-19 Cases in California

BACKGROUND

There is a need to assess neighborhood-level factors driving COVID-19 disparities across racial and ethnic groups.

OBJECTIVE

To use census tract-level data to investigate neighborhood-level factors contributing to racial and ethnic group-specific COVID-19 case rates in California.

DESIGN

Quasi-Poisson generalized linear models were used to identify neighborhood-level factors associated with COVID-19 cases. In separate sequential models for Hispanic, Black, and Asian, we characterized the associations between neighborhood factors on neighborhood COVID-19 cases. Subanalyses were conducted on neighborhoods with majority Hispanic, Black, and Asian residents to identify factors that might be unique to these neighborhoods. Geographically weighted regression using a quasi-Poisson model was conducted to identify regional differences.

MAIN MEASURES

All COVID-19 cases and tests reported through January 31, 2021, to the California Department of Public Health. Neighborhood-level data from census tracts were obtained from American Community Survey 5-year estimates (2015-2019), United States Census (2010), and United States Department of Housing and Urban Development.

KEY RESULTS

The neighborhood factors associated with COVID-19 case rate were racial and ethnic composition, age, limited English proficiency (LEP), income, household size, and population density. LEP had the largest influence on the positive association between proportion of Hispanic residents and COVID-19 cases (- 2.1% change). This was also true for proportion of Asian residents (- 1.8% change), but not for the proportion of Black residents (- 0.1% change). The influence of LEP was strongest in areas of the Bay Area, Los Angeles, and San Diego.

CONCLUSION

Neighborhood-level contextual drivers of COVID-19 burden differ across racial and ethnic groups.

Economic Determinants of Health Disparities and the Role of the Primary Care Provider

The economic determinants of adverse personal health outcomes and population level disparities pose a daunting challenge for primary care providers in promoting health for persons experiencing poverty and neighborhood deprivation. Until they are addressed, however, the health and economic well-being of persons experiencing neighborhood deprivation is not likely to be improved. There is growing evidence of effective interventions that primary care providers can adopt to address social and economic determinants of health. Primary care providers can participate in clinic and community-based approaches that target individual, neighborhood and social level drives of health and disparities.

Communications for US Populations With Limited English Proficiency During Infectious Disease Outbreaks: A Scoping Review

The COVID-19 pandemic has highlighted the need for research about communicating with populations who have limited English proficiency in the United States during infectious disease outbreaks. These populations have experienced significantly worse health outcomes during emergencies, including the COVID-19 pandemic, and evidence-based risk communications are critical to protecting their health. To support improved development of emergency communications for these communities, we conducted a scoping review that examined the extent of research available, with an intent to identify which communications topics are covered in the literature and where research gaps exist. Following the JBI framework, with reporting guided by the PRISMA extension for scoping reviews, 6 electronic databases were systematically searched in October 2022. The inclusion criteria for articles selected were: data collected between 2009 and 2022, published in English, and focused on communications pertaining to emergency infectious disease outbreaks (eg, H1N1 influenza, Zika virus, COVID-19) for populations with limited English proficiency. Of 2,049 articles identified through the search, 31 met the inclusion criteria and were selected for review. We identified major limitations in the evidence base: a majority of studies were conducted only among Spanish speakers or during the COVID-19 pandemic, and most used qualitative or nonrandom samples. Most studies documented basic language barriers in communications, but there was little exploration of more nuanced barriers, such as cultural relevance or social context. Ahead of future outbreaks, more research is urgently needed to examine the information landscapes of populations with limited English proficiency, to inform the development of more effective communications strategies from public health institutions and others.

Effect of chronic disease on racial difference in COVID-19-associated hospitalization among cancer patients

BACKGROUND

Research indicates that Black cancer patients have higher rates of COVID-19 hospitalization than their White counterparts. However, the extent to which chronic diseases contribute to racial disparities remains uncertain. We aimed to quantify the effect of chronic diseases on racial disparity in COVID-19-associated hospitalization among cancer patients.

METHODS

We linked Louisiana Tumor Registry's data with statewide COVID-19 data and hospital in-patient discharge data to identify patients diagnosed with cancer in 2015-2019 who tested positive for COVID-19 in 2020 and those with COVID-19-associated hospitalization. Multivariable logistic regression and mediation methods based on linear structural equations were employed to assess the effects of the number of chronic diseases (0, 1-2, ≥3) and individual chronic diseases.

RESULTS

Of 6381 cancer patients who tested positive for COVID-19, 31.6% were non-Hispanic Black cancer patients. Compared with non-Hispanic White cancer patients, non-Hispanic Black cancer patients had a higher prevalence of chronic diseases (79.5% vs 66.0%) and higher COVID-19-associated hospitalization (27.2% vs 17.2%). The odds of COVID-19-associated hospitalization were 80% higher for non-Hispanic Black cancer patients than non-Hispanic White cancer patients (odds ratio = 1.80, 95% confidence interval = 1.59 to 2.04). After adjusting for age, sex, insurance, poverty, obesity, and cancer type, number of chronic diseases explained 37.8% of the racial disparity in COVID-19-associated hospitalization, and hypertension, diabetes, and chronic renal disease were the top 3 chronic diseases explaining 9.6%, 8.9%, and 7.3% of the racial disparity, respectively.

CONCLUSION

Chronic diseases played a substantial role in the racial disparity in COVID-19-associated hospitalization among cancer patients, especially hypertension, diabetes, and renal disease. Understanding and addressing the root causes are crucial for targeted interventions, policies, and health-care strategies to reduce racial disparity.

The importance of patient-partnered research in addressing long COVID: Takeaways for biomedical research study design from the RECOVER Initiative's Mechanistic Pathways taskforce

The NIH-funded RECOVER study is collecting clinical data on patients who experience a SARS-CoV-2 infection. As patient representatives of the RECOVER Initiative's Mechanistic Pathways task force, we offer our perspectives on patient motivations for partnering with researchers to obtain results from mechanistic studies. We emphasize the challenges of balancing urgency with scientific rigor. We recognize the importance of such partnerships in addressing post-acute sequelae of SARS-CoV-2 infection (PASC), which includes 'long COVID,' through contrasting objective and subjective narratives. Long COVID's prevalence served as a call to action for patients like us to become actively involved in efforts to understand our condition. Patient-centered and patient-partnered research informs the balance between urgency and robust mechanistic research. Results from collaborating on protocol design, diverse patient inclusion, and awareness of community concerns establish a new precedent in biomedical research study design. With a public health matter as pressing as the long-term complications that can emerge after SARS-CoV-2 infection, considerate and equitable stakeholder involvement is essential to guiding seminal research. Discussions in the RECOVER Mechanistic Pathways task force gave rise to this commentary as well as other review articles on the current scientific understanding of PASC mechanisms.

Empirical distributions of time intervals between COVID-19 cases and more severe outcomes in Scotland

A critical factor in infectious disease control is the risk of an outbreak overwhelming local healthcare capacity. The overall demand on healthcare services will depend on disease severity, but the precise timing and size of peak demand also depends on the time interval (or clinical time delay) between initial infection, and development of severe disease. A broader distribution of intervals may draw that demand out over a longer period, but have a lower peak demand. These interval distributions are therefore important in modelling trajectories of e.g. hospital admissions, given a trajectory of incidence. Conversely, as testing rates decline, an incidence trajectory may need to be inferred through the delayed, but relatively unbiased signal of hospital admissions. Healthcare demand has been extensively modelled during the COVID-19 pandemic, where localised waves of infection have imposed severe stresses on healthcare services. While the initial acute threat posed by this disease has since subsided with immunity buildup from vaccination and prior infection, prevalence remains high and waning immunity may lead to substantial pressures for years to come. In this work, then, we present a set of interval distributions, for COVID-19 cases and subsequent severe outcomes; hospital admission, ICU admission, and death. These may be used to model more realistic scenarios of hospital admissions and occupancy, given a trajectory of infections or cases. We present a method for obtaining empirical distributions using COVID-19 outcomes data from Scotland between September 2020 and January 2022 (N = 31724 hospital admissions, N = 3514 ICU admissions, N = 8306 mortalities). We present separate distributions for individual age, sex, and deprivation of residing community. While the risk of severe disease following COVID-19 infection is substantially higher for the elderly and those residing in areas of high deprivation, the length of stay shows no strong dependence, suggesting that severe outcomes are equally severe across risk groups. As Scotland and other countries move into a phase where testing is no longer abundant, these intervals may be of use for retrospective modelling of patterns of infection, given data on severe outcomes.

Preferred Language Mediates Association Between Race, Ethnicity, and Delayed Presentation in Critically Ill Patients With COVID-19

Which social factors explain racial and ethnic disparities in COVID-19 access to care and outcomes remain unclear.

OBJECTIVES

We hypothesized that preferred language mediates the association between race, ethnicity and delays to care.

DESIGN SETTING AND PARTICIPANTS

Multicenter, retrospective cohort study of adults with COVID-19 consecutively admitted to the ICU in three Massachusetts hospitals in 2020.

MAIN OUTCOME AND MEASURES

Causal mediation analysis was performed to evaluate potential mediators including preferred language, insurance status, and neighborhood characteristics.

RESULTS

Non-Hispanic White (NHW) patients (157/442, 36%) were more likely to speak English as their preferred language (78% vs. 13%), were less likely to be un- or under-insured (1% vs. 28%), lived in neighborhoods with lower social vulnerability index (SVI) than patients from racial and ethnic minority groups (SVI percentile 59 [28] vs. 74 [21]) but had more comorbidities (Charlson comorbidity index 4.6 [2.5] vs. 3.0 [2.5]), and were older (70 [13.2] vs. 58 [15.1] years). From symptom onset, NHW patients were admitted 1.67 [0.71-2.63] days earlier than patients from racial and ethnic minority groups (p < 0.01). Non-English preferred language was associated with delay to admission of 1.29 [0.40-2.18] days (p < 0.01). Preferred language mediated 63% of the total effect (p = 0.02) between race, ethnicity and days from symptom onset to hospital admission. Insurance status, social vulnerability, and distance to the hospital were not on the causal pathway between race, ethnicity and delay to admission.

CONCLUSIONS AND RELEVANCE

Preferred language mediates the association between race, ethnicity and delays to presentation for critically ill patients with COVID-19, although our results are limited by possible collider stratification bias. Effective COVID-19 treatments require early diagnosis, and delays are associated with increased mortality. Further research on the role preferred language plays in racial and ethnic disparities may identify effective solutions for equitable care.

Incorporating resilience when assessing pandemic risk in the Arctic: a case study of Alaska

The discourse on vulnerability to COVID-19 or any other pandemic is about the susceptibility to the effects of disease outbreaks. Over time, vulnerability has been assessed through various indices calculated using a confluence of societal factors. However, categorising Arctic communities, without considering their socioeconomic, cultural and demographic uniqueness, into the high and low continuum of vulnerability using universal indicators will undoubtedly result in the underestimation of the communities' capacity to withstand and recover from pandemic exposure. By recognising vulnerability and resilience as two separate but interrelated dimensions, this study reviews the Arctic communities' ability to cope with pandemic risks. In particular, we have developed a pandemic vulnerability-resilience framework for Alaska to examine the potential community-level risks of COVID-19 or future pandemics. Based on the combined assessment of the vulnerability and resilience indices, we found that not all highly vulnerable census areas and boroughs had experienced COVID-19 epidemiological outcomes with similar severity. The more resilient a census area or borough is, the lower the cumulative death per 100 000 and case fatality ratio in that area. The insight that pandemic risks are the result of the interaction between vulnerability and resilience could help public officials and concerned parties to accurately identify the populations and communities at most risk or with the greatest need, which, in turn, helps in the efficient allocation of resources and services before, during and after a pandemic. A resilience-vulnerability-focused approach described in this paper can be applied to assess the potential effect of COVID-19 and similar future health crises in remote regions or regions with large Indigenous populations in other parts of the world.

Association of socio-economic deprivation with COVID-19 incidence and fatality during the first wave of the pandemic in Italy: lessons learned from a local register-based study

BACKGROUND

COVID-19 has been characterised by its global and rapid spread, with high infection, hospitalisation, and mortality rates worldwide. However, the course of the pandemic showed differences in chronology and intensity in different geographical areas and countries, probably due to a multitude of factors. Among these, socio-economic deprivation has been supposed to play a substantial role, although available evidence is not fully in agreement. Our study aimed to assess incidence and fatality rates of COVID-19 across the levels of socio-economic deprivation during the first epidemic wave (March-May 2020) in the Italian Province of Foggia, Apulia Region.

METHODS

Based on the data of the regional active surveillance platform, we performed a retrospective epidemiological study among all COVID-19 confirmed cases that occurred in the Apulian District of Foggia, Italy, from March 1st to May 5th, 2020. Geocoded addresses were linked to the individual Census Tract (CT) of residence. Effects of socio-economic condition were calculated by means of the Socio-Economic and Health-related Deprivation Index (SEHDI) on COVID-19 incidence and fatality.

RESULTS

Of the 1054 confirmed COVID-19 cases, 537 (50.9%) were men, 682 (64.7%) were 0-64 years old, and 338 (32.1%) had pre-existing comorbidities. COVID-19 incidence was higher in the less deprived areas (p < 0.05), independently on age. The level of socio-economic deprivation did not show a significant impact on the vital status, while a higher fatality was observed in male cases (p < 0.001), cases > 65 years (p < 0.001), cases having a connection with a nursing home (p < 0.05) or having at least 1 comorbidity (p < 0.001). On the other hand, a significant protection for healthcare workers was apparent (p < 0.001).

CONCLUSIONS

Our findings show that deprivation alone does not affect COVID-19 incidence and fatality burden, suggesting that the burden of disease is driven by a complexity of factors not yet fully understood. Better knowledge is needed to identify subgroups at higher risk and implement effective preventive strategies.

Differential Effects of Race/Ethnicity and Social Vulnerability on COVID-19 Positivity, Hospitalization, and Death in the San Francisco Bay Area

BACKGROUND

Higher COVID-19 incidence and morbidity have been documented for US Black and Hispanic populations but not as clearly for other racial and ethnic groups. Efforts to elucidate the mechanisms underlying racial health disparities can be confounded by the relationship between race/ethnicity and socioeconomic status.

OBJECTIVE

Examine race/ethnicity and social vulnerability effects on COVID-19 outcomes in the San Francisco Bay Area, an ethnically and socioeconomically diverse region, using geocoded patient records from 2020 in the University of California, San Francisco Health system.

KEY RESULTS

Higher social vulnerability, but not race/ethnicity, was associated with less frequent testing yet a higher likelihood of testing positive. Asian hospitalization rates (11.5%) were double that of White patients (5.4%) and exceeded the rates for Black (9.3%) and Hispanic patients (6.9%). A modest relationship between higher hospitalization rates and increasing social vulnerability was evident only for White patients. Hispanic patients had the highest years of expected life lost due to COVID-19.

CONCLUSIONS

COVID-19 outcomes were not consistently explained by greater social vulnerability. Asian individuals showed disproportionately high rates of hospitalization regardless of social vulnerability status. Study of the San Francisco Bay Area population not only provides valuable insights into the differential contributions of race/ethnicity and social determinants of health to COVID-19 outcomes but also emphasizes that all racial groups have experienced the toll of the pandemic, albeit in different ways and to varying degrees.

Disparities in Level of Care and Outcomes Among Patients with COVID-19: Associations Between Race/Ethnicity, Social Determinants of Health and Virtual Hospitalization, Inpatient Hospitalization, Intensive Care, and Mortality

OBJECTIVE

To examine the role of race/ethnicity and social determinants of health on COVID-19 care and outcomes for patients within a healthcare system that provided virtual hospital care.

METHODS

This retrospective cohort study included 12,956 adults who received care for COVID-19 within an integrated healthcare system between 3/1/2020 and 8/31/2020. Multinomial models were used to examine associations between race/ethnicity, insurance, neighborhood deprivation measured by Area Deprivation Index (ADI), and outcomes of interest. Outcomes included (1) highest level of care: virtual observation (VOU), virtual hospitalization (VACU), or inpatient hospitalization; (2) intensive care (ICU); and (3) all-cause 30-day mortality.

RESULTS

Patients were 41.8% White, 27.2% Black, and 31.0% Hispanic. Compared to White patients, Black patients had 1.86 higher odds of VACU admission and 1.43 higher odds of inpatient hospitalization (vs. VOU). Hispanic patients had 1.24 higher odds of inpatient hospitalization (vs. VOU). In models stratified by race/ethnicity, Hispanic and Black patients had higher odds of inpatient hospitalization (vs. VOU) if Medicaid insured compared to commercially insured. Hispanic patients living in the most deprived neighborhood had higher odds of inpatient hospitalization, compared to those in the least deprived neighborhood. Black and Hispanic patients had higher odds of ICU admission and 30-day mortality after adjustment for other social determinants.

CONCLUSIONS

Insurance and ADI were associated with COVID-19 outcomes; however, associations varied by race/ethnicity. Racial/ethnic disparities in outcomes are not fully explained by measured social determinants of health, highlighting the need for further investigation into systemic causes of inequities in COVID-19 outcomes.

Evaluating disparities by social determinants in hospital admission decisions for patients with COVID-19 quaternary hospital early in the pandemic

The COVID-19 pandemic has highlighted significant disparities in hospital outcomes when focusing on social determinants of health. Better understanding the drivers of these disparities is not only critical for COVID-19 care but also to ensure equitable treatment more generally. In this paper, we look at how hospital admission patterns, both to the medical ward and the intensive care unit (ICU), may have differed by race, ethnicity, and social determinants of health. We conducted a retrospective chart review of all patients who presented to the Emergency Department of a large quaternary hospital between March 8 and June 3, 2020. We built logistic regression models to analyze how race, ethnicity, area deprivation index, English as a primary language, homelessness, and illicit substance use impacted the likelihood of admission while controlling for disease severity and timing of admission in relation to the start of data collection. We had 1302 recorded Emergency Department visits of patients diagnosed with SARS-CoV-2. White, Hispanic, and African American patients made up 39.2%, 37.5%, and 10.4% of the population respectively. Primary language was recorded as English for 41.2% and non-English for 30% of patients. Among the social determinants of health assessed, we found that illicit drug use significantly increased the likelihood for admission to the medical ward (odds ratio 4.4, confidence interval 1.1-17.1, P = .04), and that having a language other than English as a primary language significantly increased the likelihood of ICU admission (odds ratio 2.6, confidence interval 1.2-5.7, P = .02). Illicit drug use was associated with an increased likelihood of medical ward admission, potentially due to clinician concerns for complicated withdrawal or blood-stream infections from intravenous drug use. The increased likelihood of ICU admission associated with a primary language other than English may have been driven by communication difficulties or differences in disease severity that our model did not detect. Further work is required to better understand drivers of disparities in hospital COVID-19 care.

Perceptions of the SARS-CoV2 pandemic: a small comparative survey analysis between language preference populations in a United States community health center

In 2019, a new variant of coronavirus, SARS-CoV-2 (COVID-19) created a global pandemic that has highlighted and exacerbated health disparities. Educating the general public about COVID-19 is one of the primary mitigation strategies amongst health professionals. English is not the preferred language for an estimated 22% of the United States population making effective mass communication efforts difficult to achieve. This study seeks to understand and compare several topics surrounding COVID-19 health communication and healthcare disparities between individuals with English language preference (ELP) and non-English language preference (NELP) within the United States. A survey available in seven languages asking about knowledge and opinions on COVID-19, vaccines, preferred sources of health information, and other questions, was administered February-April 2021 to patients at an urban federally qualified health center that also serves global refugees and immigrants. Descriptive statistics and comparative analysis were performed to identify differences between ELP and NELP individuals. Analysis of 144 surveys, 33 of which were NELP, showed 90.97% of all patients agreed that COVID-19 was a serious disease and 66.67% would receive the COVID-19 vaccine. There were numerous differences between ELP and NELP individuals, including trust in government, symptom identification, preferred source of health information, and feelings that cultural needs had been met. This study has identified several significant differences in patient perceptions relating to the COVID-19 pandemic when comparing NELP to ELP and highlighted areas where improvement can occur. Applying this information, easily utilized targeted resources can be created to quickly intervene and address health disparities among patients seeking care at an urban community health center.

Temporal and spatial trends in suicide-related visits before and during the COVID-19 pandemic in the US, 2018-2021

BACKGROUND

COVID-19 disproportionately impacted mental health in disadvantaged populations and areas. However, disparities in long-term changes in suicide-related visits across the US are unclear. This retrospective study aims to characterize temporal and spatial changes in suicide-related visits in healthcare settings from 2018 to 2021 in the U.S.

METHODS

We use electronic health records for 21,860,370 patients from Healthjump through the COVID-19 Research Database Consortium. Healthjump harmonizes EHR data from over 55 national databases across the US. Suicide ideation and suicide attempts between January 1, 2018 and December 12, 2021 were identified by the diagnosis codes in 6 periods in 2021 compared with the same periods in 2018-2020.

RESULTS

There was 30,019 suicidal ideation, and 7392 suicide attempt visits from January 2018 to November 2021. 15-20-year-olds were the most represented age group at 6302 suicide ideation visits (21.0 % of suicide ideation visits) and 1326 suicide attempt visits (17.9 % of suicide attempt visits), followed by suicide-related visits among 60+ years old. Compared with pre-pandemic periods, youth aged 15-20, females, White, non-Hispanic, and English speakers had increased suicide-related visits, especially suicidal ideation (P < 0.05). Suicide attempts with non-medical substances increased to 28.0 % in the first 6 months of the pandemic in 2020, compared with the prior year (21.5 %). COVID-19 patients had increased suicidal ideation in 2020.

LIMITATIONS

The EHR data is not nationally representative.

CONCLUSIONS

This study found significant and disproportionate increases in suicide related visits over the COVID-19 stages. To prevent the next storms of suicides, future interventions shall accommodate needs among vulnerable groups during and after periods of crisis.

Re-Aiming Equity Evaluation in Clinical Decision Support: A Scoping Review of Equity Assessments in Surgical Decision Support Systems

OBJECTIVE

We critically evaluated the surgical literature to explore the prevalence and describe how equity assessments occur when using clinical decision support systems.

BACKGROUND

Clinical decision support (CDS) systems are increasingly used to facilitate surgical care delivery. Despite formal recommendations to do so, equity evaluations are not routinely performed on CDS systems and underrepresented populations are at risk of harm and further health disparities. We explored surgical literature to determine frequency and rigor of CDS equity assessments and offer recommendations to improve CDS equity by appending existing frameworks.

METHODS

We performed a scoping review up to Augus 25, 2021 using PubMed and Google Scholar for the following search terms: clinical decision support, implementation, RE-AIM, Proctor, Proctor's framework, equity, trauma, surgery, surgical. We identified 1415 citations and 229 abstracts met criteria for review. A total of 84 underwent full review after 145 were excluded if they did not assess outcomes of an electronic CDS tool or have a surgical use case.

RESULTS

Only 6% (5/84) of surgical CDS systems reported equity analyses, suggesting that current methods for optimizing equity in surgical CDS are inadequate. We propose revising the RE-AIM framework to include an Equity element (RE 2 -AIM) specifying that CDS foundational analyses and algorithms are performed or trained on balanced datasets with sociodemographic characteristics that accurately represent the CDS target population and are assessed by sensitivity analyses focused on vulnerable subpopulations.

CONCLUSION

Current surgical CDS literature reports little with respect to equity. Revising the RE-AIM framework to include an Equity element (RE 2 -AIM) promotes the development and implementation of CDS systems that, at minimum, do not worsen healthcare disparities and possibly improve their generalizability.

Public Health Measures and SARS-CoV-2 Cases in the Juvenile Justice System: Implications for Pandemic Response in the Detention Setting

OBJECTIVE

The purpose of this study was to examine severe acute respiratory syndrome-coronavirus-2 case positivity in juvenile justice facilities of two different states alongside institutional, local, and state public health policies during the first 6 months of the coronavirus disease 2019 pandemic.

METHODS

This retrospective chart review examined two large, urban juvenile justice centers in California and Texas. Positive intake or day 12 tests were considered suggestive of community-acquired severe acute respiratory syndrome-coronavirus-2 infection. Researchers examined state and county restrictions, closings, and openings. The study included all of the youths 10 to 18 years residing in the facilities between March and August 2020. The main outcomes measured case positivity in each facility and compared it with community positivity rates and state public health measures.

RESULTS

In total, 530 youth were included (Texas, n = 319; California, n = 211). The Texas facility reported a higher number of positive cases (24) versus the California facility (3) (P < 0.05). Of the positive youth, 70% were asymptomatic, and none required hospitalization. Intake and day 12 tests were positive in <1% of California youth compared with a rate of 4% in Texas (P < 0.05). California and Texas instituted mask mandates in May and July 2020, respectively. California restricted indoor capacity until August, but Texas varied from 25% to 75% capacity through July.

CONCLUSIONS

The Texas facility reported a higher percentage of community-acquired infections compared with California, coinciding with reopening measures in Texas. Texas also enacted a mask mandate later than California. These public health measures, among other factors, likely contributed to higher community rates in Texas, thereby affecting rates among the detained youth.

Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors

The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.

Online information seeking during the COVID-19 pandemic: A cross-country analysis

The aim of this study was to investigate the coronavirus-related web-searching patterns of people from the 10 most affected nations in September 2020. The authors extracted all searches for the sample nations, consisting of the two words ‘COVID-19’ and ‘coronavirus’ and their variations, from Google Trends for the complete year of 2020. The results showed a discrepancy due to the priority of the language used during searches for coronavirus-related information. The time span of the attention level of citizens towards coronavirus-related information was relatively short (about one month). This supports the assumption of the activation model of information exposure that information which generates a negative affect is not welcomed by users. The findings have practical implications for governments and health authorities in, for example, launching information services for citizens in the early months of a pandemic and them remaining as the preferred source of information for citizens.

Self-Isolation and Testing Behaviour During the COVID-19 Pandemic: An Agent-Based Model

Since the beginning of the COVID-19 pandemic, various models of virus spread have been proposed. While most of these models focused on the replication of the interaction processes through which the virus is passed on from infected agents to susceptible ones, less effort has been devoted to the process through which agents modify their behaviour as they adapt to the risks posed by the pandemic. Understanding the way agents respond to COVID-19 spread is important, as this behavioural response affects the dynamics of virus spread by modifying interaction patterns. In this article, we present an agent-based model that includes a behavioural module determining agent testing and isolation propensity in order to understand the role of various behavioural parameters in the spread of COVID-19.

Emerging Health Disparities during the COVID-19 Pandemic

The coronavirus disease 2019 (COVID-19) pandemic has underscored social and racial discrimination in global health, showing that health equity is still a goal to be achieved. Understanding the impact of COVID-19 on public health potential is vital to present a fair opportunity for people of different backgrounds to be as healthy as possible. As such, this communication discusses the emerging health disparities in light of the COVID-19 pandemic and analyzes their implications. Original research, effective health communication, and promotion strategies ought to be leveraged to step closer toward national and international health equity.

COVID-19 Outcomes in a US Cohort of Persons Living with HIV (PLWH)

Reported coronavirus disease 2019 (COVID-19) outcomes in persons living with HIV (PLWH) vary across cohorts. We examined clinical characteristics and outcomes of PLWH with COVID-19 compared with a matched HIV-seronegative cohort in a mid-Atlantic US healthcare system. Multivariate logistic regression was used to explore factors associated with hospitalization and death/mechanical ventilation among PLWH. Among 281 PLWH with COVID-19, the mean age was 51.5 (SD 12.74) years, 63% were male, 86% were Black, and 87% had a HIV viral load <200 copies/mL. Overall, 47% of PLWH versus 24% (p < 0.001) of matched HIV-seronegative individuals were hospitalized. Rates of COVID-19 associated cardiovascular and thrombotic events, AKI, and infections were similar between PLWH and HIV-seronegative individuals. Overall mortality was 6% (n = 18/281) in PLWH versus 3% (n = 33/1124) HIV-seronegative, p < 0.0001. Among admitted patients, mortality was 14% (n = 18/132) for PLWH and 13% (n = 33/269) for HIV-seronegative, p = 0.75. Among PLWH, hospitalization associated with older age aOR 1.04 (95% CI 1.01, 1.06), Medicaid insurance aOR 2.61 (95% CI 1.39, 4.97) and multimorbidity aOR 2.98 (95% CI 1.72, 5.23). Death/mechanical ventilation associated with older age aOR 1.06 (95% CI 1.01, 1.11), Medicaid insurance aOR 3.6 (95% CI 1.36, 9.74), and multimorbidity aOR 4.4 (95% CI 1.55, 15.9) in adjusted analyses. PLWH were hospitalized more frequently than the HIV-seronegative group and had a higher overall mortality rate, but once hospitalized had similar mortality rates. Older age, multimorbidity and insurance status associated with more severe outcomes among PLWH suggesting the importance of targeted interventions to mitigate the effects of modifiable inequities.

Factors Associated with Mortality in Patients with COVID-19 Receiving Prolonged Ventilatory Support

Background: Since its emergence in early 2020, coronavirus disease 2019 (COVID-19)-associated pneumonia has caused a global strain on intensive care unit (ICU) resources with many intubated patients requiring prolonged ventilatory support. Outcomes for patients with COVID-19 who receive prolonged intubation (>21 days) and possible predictors of mortality in this group are not well established. Patients and Methods: Data were prospectively collected from adult patients with COVID-19 requiring mechanical ventilation from March 2020 through December 2021 across a system of 11 hospitals. The primary end point was in-hospital mortality. Factors associated with mortality were evaluated using univariable and multivariable logistic regression analyses. Results: Six hundred six patients were placed on mechanical ventilation for COVID-19 pneumonia during the study period, with in-hospital mortality of 40.3% (n = 244). Increased age (odds ratio [OR], 1.06; 95% confidence interval [CI], 1.03-1.09), increased creatinine (OR, 1.40; 95% CI, 1.08-1.82), and receiving corticosteroids (OR, 2.68; 95% CI, 1.20-5.98) were associated with mortality. Intubations lasting longer than 21 days (n = 140) had a lower in-hospital mortality of 25.7% (n = 36; p < 0.001). Increasing Elixhauser comorbidity index (OR, 1.12; 95% CI, 1.04-1.19) and receiving corticosteroids (OR, 1.92; 95% CI, 1.06-3.47) were associated with need for prolonged ventilation. In this group, increased age (OR, 1.06; 95% CI, 1.01-1.08) and non-English speaking (OR, 3.74; 95% CI, 1.13-12.3) were associated with mortality. Conclusions: In-hospital mortality in mechanically ventilated patients with COVID-19 pneumonia occurs primarily in the first 21 days after intubation, possibly related to the early active inflammatory process. In patients on prolonged mechanical ventilation, increased age and being non-English speaking were associated with mortality.

COVID-19 machine learning model predicts outcomes in older patients from various European countries, between pandemic waves, and in a cohort of Asian, African, and American patients

BACKGROUND

COVID-19 remains a complex disease in terms of its trajectory and the diversity of outcomes rendering disease management and clinical resource allocation challenging. Varying symptomatology in older patients as well as limitation of clinical scoring systems have created the need for more objective and consistent methods to aid clinical decision making. In this regard, machine learning methods have been shown to enhance prognostication, while improving consistency. However, current machine learning approaches have been limited by lack of generalisation to diverse patient populations, between patients admitted at different waves and small sample sizes.

OBJECTIVES

We sought to investigate whether machine learning models, derived on routinely collected clinical data, can generalise well i) between European countries, ii) between European patients admitted at different COVID-19 waves, and iii) between geographically diverse patients, namely whether a model derived on the European patient cohort can be used to predict outcomes of patients admitted to Asian, African and American ICUs.

METHODS

We compare Logistic Regression, Feed Forward Neural Network and XGBoost algorithms to analyse data from 3,933 older patients with a confirmed COVID-19 diagnosis in predicting three outcomes, namely: ICU mortality, 30-day mortality and patients at low risk of deterioration. The patients were admitted to ICUs located in 37 countries, between January 11, 2020, and April 27, 2021.

RESULTS

The XGBoost model derived on the European cohort and externally validated in cohorts of Asian, African, and American patients, achieved AUC of 0.89 (95% CI 0.89-0.89) in predicting ICU mortality, AUC of 0.86 (95% CI 0.86-0.86) for 30-day mortality prediction and AUC of 0.86 (95% CI 0.86-0.86) in predicting low-risk patients. Similar AUC performance was achieved also when predicting outcomes between European countries and between pandemic waves, while the models showed high calibration quality. Furthermore, saliency analysis showed that FiO2 values of up to 40% do not appear to increase the predicted risk of ICU and 30-day mortality, while PaO2 values of 75 mmHg or lower are associated with a sharp increase in the predicted risk of ICU and 30-day mortality. Lastly, increase in SOFA scores also increase the predicted risk, but only up to a value of 8. Beyond these scores the predicted risk remains consistently high.

CONCLUSION

The models captured both the dynamic course of the disease as well as similarities and differences between the diverse patient cohorts, enabling prediction of disease severity, identification of low-risk patients and potentially supporting effective planning of essential clinical resources.

TRIAL REGISTRATION NUMBER

NCT04321265.

Impact of Social Deprivation on Hospitalization and Intensive Care Unit Admission among COVID-19 Patients: A Systematic Review and Meta-Analysis

Background

The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected socially disadvantaged groups; however, the association between socioeconomic status and healthcare utilization among COVID-19 patients remains unclear. Therefore, a systematic review and meta-analysis was conducted to assess the association between socioeconomic status and hospitalization and intensive care unit admission among COVID-19 patients.

Methods

PubMed, Embase, and the Cochrane Register of Controlled Trials were searched for relevant literature (updated to Jun 2022). Studies that investigated the association of social deprivation with hospitalization and intensive care unit admission in COVID-19 patients were included. The primary outcomes included risk of hospitalization and intensive care unit admission, measured by odds ratio.

Results

Eleven studies covering 2,423,095 patients were included in the meta-analysis. Socially disadvantaged patients had higher odds of hospitalization in comparison to socially advantaged patients (odds ratio 1.25, 95% confidence interval: 1.14 to 1.38; P<0.01). The odds of intensive care unit admission among more deprived patients was not significantly different from that of less deprived patients (odds ratio 1.03, 95% confidence interval: 0.78 to 1.35; P=0.85). These findings were proven robust through subgroup and sensitivity analyses.

Conclusion

Socially disadvantaged populations have higher odds of hospitalization if they become infected with COVID-19. More effective medical support and interventions for these vulnerable populations are required to reduce inequity in healthcare utilization and alleviate the burden on healthcare systems.

Neighbourhood-level socio-demographic characteristics and risk of COVID-19 incidence and mortality in Ontario, Canada: A population-based study

OBJECTIVES

We aimed to estimate associations between COVID-19 incidence and mortality with neighbourhood-level immigration, race, housing, and socio-economic characteristics.

METHODS

We conducted a population-based study of 28,808 COVID-19 cases in the provincial reportable infectious disease surveillance systems (Public Health Case and Contact Management System) which includes all known COVID-19 infections and deaths from Ontario, Canada reported between January 23, 2020 and July 28, 2020. Residents of congregate settings, Indigenous communities living on reserves or small neighbourhoods with populations <1,000 were excluded. Comparing neighbourhoods in the 90th to the 10th percentiles of socio-demographic characteristics, we estimated the associations between 18 neighbourhood-level measures of immigration, race, housing and socio-economic characteristics and COVID-19 incidence and mortality using Poisson generalized linear mixed models.

RESULTS

Neighbourhoods with the highest proportion of immigrants (relative risk (RR): 4.0, 95%CI:3.5-4.5) and visible minority residents (RR: 3.3, 95%CI:2.9-3.7) showed the strongest association with COVID-19 incidence in adjusted models. Among individual race groups, COVID-19 incidence was highest among neighbourhoods with the high proportions of Black (RR: 2.4, 95%CI:2.2-2.6), South Asian (RR: 1.9, 95%CI:1.8-2.1), Latin American (RR: 1.8, 95%CI:1.6-2.0) and Middle Eastern (RR: 1.2, 95%CI:1.1-1.3) residents. Neighbourhoods with the highest average household size (RR: 1.9, 95%CI:1.7-2.1), proportion of multigenerational families (RR: 1.8, 95%CI:1.7-2.0) and unsuitably crowded housing (RR: 2.1, 95%CI:2.0-2.3) were associated with COVID-19 incidence. Neighbourhoods with the highest proportion of residents with less than high school education (RR: 1.6, 95%CI:1.4-1.8), low income (RR: 1.4, 95%CI:1.2-1.5) and unaffordable housing (RR: 1.6, 95%CI:1.4-1.8) were associated with COVID-19 incidence. Similar inequities were observed across neighbourhood-level sociodemographic characteristics and COVID-19 mortality.

CONCLUSIONS

Neighbourhood-level inequities in COVID-19 incidence and mortality were observed in Ontario, with excess burden experienced in neighbourhoods with a higher proportion of immigrants, racialized populations, large households and low socio-economic status.

The Role of Community-Level Factors on Disparities in COVID-19 Infection Among American Indian/Alaska Native Veterans

OBJECTIVES

American Indian and Alaska Native (AI/AN) communities have been disproportionately affected by the coronavirus disease 2019 (COVID-19) pandemic. This study examines whether neighborhood characteristics mediate AI/AN versus White-non-Hispanic Veteran COVID-19 infection disparities, and whether mediation differs based on proximity to reservations.

METHODS

Using Veteran Health Administration's (VHA) national database of VHA users evaluated for COVID-19 infection (3/1/2020-8/25/2020), we examined whether census tract neighborhood characteristics (percent households overcrowded, without complete plumbing, without kitchen plumbing, and neighborhood socioeconomic status [n-SES]) mediated racial disparities in COVID-19 infection, using inverse odds-weighted logistic models controlling for individual-level characteristics. Using moderated mediation analyses, we assessed whether neighborhood mediating effects on disparities differed for those residing in counties containing/near federally recognized tribal lands (i.e., Contract Health Service Delivery Area [CHSDA] counties) versus not.

RESULTS

The percent of households without complete plumbing, percent without kitchen plumbing, and n-SES partially mediated AI/AN-White-non-Hispanic COVID-19 infection disparities (accounting for 17-35% of disparity) to a similar extent in CHSDA and non-CHSDA counties. The percent of households without kitchen plumbing had stronger mediating effects for CHSDA than non-CHSDA residents.

CONCLUSIONS

Neighborhood-level social determinants of health may contribute to the disproportionate COVID-19 infection burden on AI/ANs; differences are exacerbated among AI/ANs living near reservations.

Performance of a Chest Radiograph AI Diagnostic Tool for COVID-19: A Prospective Observational Study

Purpose

To conduct a prospective observational study across 12 U.S. hospitals to evaluate real-time performance of an interpretable artificial intelligence (AI) model to detect COVID-19 on chest radiographs.

Materials and Methods

A total of 95 363 chest radiographs were included in model training, external validation, and real-time validation. The model was deployed as a clinical decision support system, and performance was prospectively evaluated. There were 5335 total real-time predictions and a COVID-19 prevalence of 4.8% (258 of 5335). Model performance was assessed with use of receiver operating characteristic analysis, precision-recall curves, and F1 score. Logistic regression was used to evaluate the association of race and sex with AI model diagnostic accuracy. To compare model accuracy with the performance of board-certified radiologists, a third dataset of 1638 images was read independently by two radiologists.

Results

Participants positive for COVID-19 had higher COVID-19 diagnostic scores than participants negative for COVID-19 (median, 0.1 [IQR, 0.0-0.8] vs 0.0 [IQR, 0.0-0.1], respectively; P < .001). Real-time model performance was unchanged over 19 weeks of implementation (area under the receiver operating characteristic curve, 0.70; 95% CI: 0.66, 0.73). Model sensitivity was higher in men than women (P = .01), whereas model specificity was higher in women (P = .001). Sensitivity was higher for Asian (P = .002) and Black (P = .046) participants compared with White participants. The COVID-19 AI diagnostic system had worse accuracy (63.5% correct) compared with radiologist predictions (radiologist 1 = 67.8% correct, radiologist 2 = 68.6% correct; McNemar P < .001 for both).

Conclusion

AI-based tools have not yet reached full diagnostic potential for COVID-19 and underperform compared with radiologist prediction.Keywords: Diagnosis, Classification, Application Domain, Infection, Lung Supplemental material is available for this article.. © RSNA, 2022.

Getting Critical Information During the COVID-19 Pandemic: Experiences of Spanish and Chinese Speakers With Limited English Proficiency

People with limited English proficiency in the United States have suffered disproportionate negative health outcomes during the COVID-19 pandemic. Effective communications are critical tools in addressing inequities insofar as they can motivate adoption of protective behaviors and reduce incidence of disease; however, little is known about experiences of communities with limited English proficiency receiving relevant information during COVID-19 or other outbreaks. To address this gap and provide inputs for communication strategies, we completed a study based on 2 novel and nationally representative surveys conducted between June and August 2020 among Spanish and Chinese speakers with limited English proficiency (n = 764 and n = 355, respectively). Results first showed that Spanish and Chinese speakers did not consistently receive information about protective behaviors from key public health and government institutions early in the pandemic. Second, for such information, Spanish and Chinese speakers used a diverse set of information resources that included family and friends, social media, and traditional media from both inside and outside the United States. Third, Spanish and Chinese speakers faced challenges getting COVID-19 information, including receiving media messages that felt discriminatory toward Latinx or Chinese people. Together, these findings suggest gaps in effectively reaching Spanish and Chinese speakers. Data highlight the important role of bilingual materials to support sharing of information between Spanish or Chinese speakers and English speakers within their social networks, and the need for digital news content for traditional and social media. Finally, efforts are needed to address discriminatory messaging in media and to actively counter it in public health communications.

Racial and Ethnic Disparities in Buprenorphine and Extended-Release Naltrexone Filled Prescriptions During the COVID-19 Pandemic

Importance

COVID-19 disrupted delivery of buprenorphine and naltrexone treatment for opioid use disorder (OUD), and during the pandemic, members of racial and ethnic minority groups experienced increased COVID-19 and opioid overdose risks compared with White individuals. However, whether filled buprenorphine and naltrexone prescriptions varied across racial and ethnic groups during the COVID-19 pandemic remains unknown.

Objective

To investigate whether disruptions in filled buprenorphine and naltrexone prescriptions differed by race and ethnicity and insurance status or payer type.

Design, Setting, and Participants

This cross-sectional study used retail pharmacy claims from May 2019 to June 2021 from the Symphony Health database, which includes 92% of US retail pharmacy claims, with race and ethnicity data spanning all insurance status and payer categories. Interrupted time series were used to estimate levels and trends of dispensed buprenorphine and naltrexone prescriptions before and after pandemic onset. Included individuals were those who filled buprenorphine and extended-release naltrexone prescriptions. Data were analyzed from July 2021 through March 2022.

Main Outcomes and Measures

Weekly rates of dispensed buprenorphine and extended-release naltrexone prescription fills per 1000 patients and proportion of longer (ie, ≥14 days' supply) buprenorphine prescription fills were calculated. Analyses were stratified by patient race and ethnicity and further by insurance status and payer type for White and Black patients.

Results

A total of 1 556 860 individuals who filled buprenorphine prescriptions (4359 Asian [0.3%], 94 657 Black [6.1%], 55 369 Hispanic [3.6%], and 664 779 White [42.7%]) and 127 506 individuals who filled extended-release naltrexone prescriptions (344 Asian [0.3%], 8186 Black [6.4%], 5343 Hispanic [4.2%], and 53 068 White [41.6%]) from May 6, 2019, to June 5, 2021, were analyzed. Prepandemic increases in buprenorphine fill rate flattened for all groups after COVID-19 onset (30.5 percentage point difference in trend; P < .001) compared with prepandemic trends. Significant level decreases in buprenorphine fills (ranging from 2.5% for Black patients; P = .009 to 4.0% for Hispanic patients; P = .009) at pandemic onset were observed for members of racial and ethnic minority groups but not White patients. At pandemic onset, rate of buprenorphine fills decreased in level for Medicare and cash-paying patients but with greater decreases for Black patients (Medicare: 10.0%; P < .001; cash: 20.0%; P < .001) than White patients (Medicare: 3.5%; P = .004; cash: 15.0%; P < .001). No decreases were found among Medicaid patients. Unlike buprenorphine, extended-release naltrexone had uniform level (from 10.0% for White patients with private insurance; P < .001 to 23.3% for Black patients with Medicare; P < .001) and trend (from 15.5 percentage points for White patients with Medicaid; P = .001 to 52.0 percentage points for Black patients with private insurance; P < .001) decreases across groups.

Conclusions and Relevance

This study found that the COVID-19 pandemic was associated with immediate decreases in filled buprenorphine prescriptions by members of racial and ethnic minority groups but not White individuals. These findings suggest that members of racial and ethnic minority groups had larger losses in buprenorphine access during the pandemic across payer types.

Nurse-sensitive indicators during COVID-19

Purpose

Nurses are on the forefront of delivering care to patients hospitalized with COVID‐19. Nurses’ impact on patient care can be discerned through assessment and documentation strategies, including structured and unstructured narratives, clinical pathways, flowsheets, and problem‐based approaches. To date, there are no published reports regarding nursing assessment and documentation during the COVID‐19 pandemic using an assessment framework to capture clinical decision making, nursing diagnoses, and key social determinant of health (SDoH) data. Hence, the purpose of this investigation was to conduct an exploratory nursing documentation audit of patients hospitalized with COVID‐19 during the first surge to identify types and frequency of nurse‐sensitive indicators, including SDoH.

Method

This pilot study utilized a retrospective chart review design at a single academic medical center, utilizing Gordon's Eleven Functional Health Patterns (FHP) framework to extract clinical, social, and nursing assessment data for patients hospitalized with COVID‐19. Descriptive statistics were computed for continuous variables and counts/percentages for categorical variables.

Findings

Data from 94 patient records were analyzed. Most patients were male (59.6%), with a mean age of 58 years. Nearly 15% of patients were Black and 12.8% were Hispanic, most residing in four geographic areas. Nine of the 11 FHPs were reflected in nurse‐sensitive indicators documented in the electronic health record. SDoH data were inconsistently documented, including race, education, history of neglect/abuse, and occupation.

Conclusion

The FHP framework captured many nurse‐sensitive indicators during the first COVID‐19 surge, although screening for and documenting SDoH data were limited.

Implications for nursing practice

Findings can influence the development of nursing assessment and documentation during crisis care delivery that are inclusive of distinct sociodemographic factors, in addition to clinical factors, to provide comprehensive, culturally sensitive care. Such documentation will enhance the use of nursing knowledge guided by a nursing framework to make visible the essential contributions of nurses to healthcare delivery.

Social Determinants of Disease: HIV and COVID-19 Experiences

PURPOSE OF REVIEW

The differential impact of the COVID-19 and HIV pandemics on marginalized communities has renewed calls for more robust and deeper investigation into structural and social causes of health inequities contributing to these infections, including underlying factors related to systematic racism. Using the Social Determinants of Health (SDOH) framework, we analyzed parallel and divergent factors associated with COVID-19 and HIV/AIDS and the prevalence of disparate disease in diverse communities. We utilized PRISMA guidelines to identify relevant literature (N = 210 articles) that resulted in a review of 125 articles included in our synthesis.

RECENT FINDINGS

With racial health inequities as a core contributor to disease vulnerability, we also identified other factors such as economic stability, social and community support, the neighborhood and built environment, healthcare access and quality, and education access and quality as important socioecological considerations toward achieving health equity. Our review identifies structural and systematic factors that drive HIV and COVID-19 transmission. Our review highlights the importance of not solely focusing on biomedical interventions as solutions to ending HIV and COVID-19, but rather call for building a more just public health and social service safety net that meets the needs of people at the intersection of multiple vulnerabilities.

Neighbourhood-level socio-demographic characteristics and risk of COVID-19 incidence and mortality in Ontario, Canada: A population-based study

OBJECTIVES

We aimed to estimate associations between COVID-19 incidence and mortality with neighbourhood-level immigration, race, housing, and socio-economic characteristics.

METHODS

We conducted a population-based study of 28,808 COVID-19 cases in the provincial reportable infectious disease surveillance systems (Public Health Case and Contact Management System) which includes all known COVID-19 infections and deaths from Ontario, Canada reported between January 23, 2020 and July 28, 2020. Residents of congregate settings, Indigenous communities living on reserves or small neighbourhoods with populations <1,000 were excluded. Comparing neighbourhoods in the 90th to the 10th percentiles of socio-demographic characteristics, we estimated the associations between 18 neighbourhood-level measures of immigration, race, housing and socio-economic characteristics and COVID-19 incidence and mortality using Poisson generalized linear mixed models.

RESULTS

Neighbourhoods with the highest proportion of immigrants (relative risk (RR): 4.0, 95%CI:3.5-4.5) and visible minority residents (RR: 3.3, 95%CI:2.9-3.7) showed the strongest association with COVID-19 incidence in adjusted models. Among individual race groups, COVID-19 incidence was highest among neighbourhoods with the high proportions of Black (RR: 2.4, 95%CI:2.2-2.6), South Asian (RR: 1.9, 95%CI:1.8-2.1), Latin American (RR: 1.8, 95%CI:1.6-2.0) and Middle Eastern (RR: 1.2, 95%CI:1.1-1.3) residents. Neighbourhoods with the highest average household size (RR: 1.9, 95%CI:1.7-2.1), proportion of multigenerational families (RR: 1.8, 95%CI:1.7-2.0) and unsuitably crowded housing (RR: 2.1, 95%CI:2.0-2.3) were associated with COVID-19 incidence. Neighbourhoods with the highest proportion of residents with less than high school education (RR: 1.6, 95%CI:1.4-1.8), low income (RR: 1.4, 95%CI:1.2-1.5) and unaffordable housing (RR: 1.6, 95%CI:1.4-1.8) were associated with COVID-19 incidence. Similar inequities were observed across neighbourhood-level sociodemographic characteristics and COVID-19 mortality.

CONCLUSIONS

Neighbourhood-level inequities in COVID-19 incidence and mortality were observed in Ontario, with excess burden experienced in neighbourhoods with a higher proportion of immigrants, racialized populations, large households and low socio-economic status.

Estimation of Coronavirus Disease 2019 Hospitalization Costs From a Large Electronic Administrative Discharge Database, March 2020-July 2021

Background

Information on the costs of inpatient care for patients with coronavirus disease 2019 (COVID-19) is very limited. This study estimates the per-patient cost of inpatient care for adult COVID-19 patients seen at >800 US hospitals.

Methods

Patients aged ≥18 years with ≥1 hospitalization during March 2020–July 2021 with a COVID-19 diagnosis code in a large electronic administrative discharge database were included. We used validated costs when reported; otherwise, costs were calculated using charges multiplied by cost-to-charge ratios. We estimated costs of inpatient care per patient overall and by severity indicator, age, sex, underlying medical conditions, and acute complications of COVID-19 using a generalized linear model with log link function and gamma distribution.

Results

The overall cost among 654673 patients hospitalized with COVID-19 was $16.2 billion. Estimated per-patient hospitalization cost was $24 826. Among surviving patients, estimated per-patient cost was $13 090 without intensive care unit (ICU) admission or invasive mechanical ventilation (IMV), $21 222 with ICU admission alone, and $59 742 with IMV. Estimated per-patient cost among patients who died was $27 017. Adjusted cost differential was higher among patients with certain underlying conditions (eg, chronic kidney disease [$12 391], liver disease [$8878], cerebrovascular disease [$7267], and obesity [$5933]) and acute complications (eg, acute respiratory distress syndrome [$43 912], pneumothorax [$25 240], and intracranial hemorrhage [$22 280]).

Conclusions

The cost of inpatient care for COVID-19 patients was substantial through the first 17 months of the pandemic. These estimates can be used to inform policy makers and planners and cost-effectiveness analysis of public health interventions to alleviate the burden of COVID-19.

The omicron variant of SARS-CoV-2: Understanding the known and living with unknowns

The recently discovered Omicron variant of SARS-CoV-2 has rapidly burst into the public and scientific eye, being detected in more than 26 countries around the world. Given its more than 50 mutations, there is widespread concern about its public health impact, leading the World Health Organization to designate it a variant of concern. This Commentary provides a summary of current knowledge and unknowns about this viral variant as of December 2, 2021 and summarizes the key questions that need to be rapidly answered.

Major disparities in COVID-19 test positivity for patients with non-English preferred language even after accounting for race and social factors in the United States in 2020

Background

The COVID-19 pandemic has further exposed inequities in our society, demonstrated by disproportionate COVID-19 infection rate and mortality in communities of color and low-income communities. One key area of inequity that has yet to be explored is disparities based on preferred language.

Methods

We conducted a retrospective cohort study of 164,368 adults tested for COVID-19 in a large healthcare system across Washington, Oregon, and California from March – July 2020. Using electronic health records, we constructed multi-level models that estimated the odds of testing positive for COVID-19 by preferred language, adjusting for age, race/ethnicity, and social factors. We further investigated interaction between preferred language and both race/ethnicity and state. Analysis was performed from October–December 2020.

Results

Those whose preferred language was not English had higher odds of having a COVID-19 positive test (OR 3.07, p < 0.001); this association remained significant after adjusting for age, race/ethnicity, and social factors. We found significant interaction between language and race/ethnicity and language and state, but the odds of COVID-19 test positivity remained greater for those whose preferred language was not English compared to those whose preferred language was English within each race/ethnicity and state.

Conclusions

People whose preferred language is not English are at greater risk of testing positive for COVID-19 regardless of age, race/ethnicity, geography, or social factors – demonstrating a significant inequity. Research demonstrates that our public health and healthcare systems are centered on English speakers, creating structural and systemic barriers to health. Addressing these barriers are long overdue and urgent for COVID-19 prevention.

Implementation of an Anticoagulation Practice Guideline for COVID-19 via a Clinical Decision Support System in a Large Academic Health System and Its Evaluation: Observational Study

BACKGROUND

Studies evaluating strategies for the rapid development, implementation, and evaluation of clinical decision support (CDS) systems supporting guidelines for diseases with a poor knowledge base, such as COVID-19, are limited.

OBJECTIVE

We developed an anticoagulation clinical practice guideline (CPG) for COVID-19, which was delivered and scaled via CDS across a 12-hospital Midwest health care system. This study represents a preplanned 6-month postimplementation evaluation guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework.

METHODS

The implementation outcomes evaluated were reach, adoption, implementation, and maintenance. To evaluate effectiveness, the association of CPG adherence on hospital admission with clinical outcomes was assessed via multivariable logistic regression and nearest neighbor propensity score matching. A time-to-event analysis was conducted. Sensitivity analyses were also conducted to evaluate the competing risk of death prior to intensive care unit (ICU) admission. The models were risk adjusted to account for age, gender, race/ethnicity, non-English speaking status, area deprivation index, month of admission, remdesivir treatment, tocilizumab treatment, steroid treatment, BMI, Elixhauser comorbidity index, oxygen saturation/fraction of inspired oxygen ratio, systolic blood pressure, respiratory rate, treating hospital, and source of admission. A preplanned subgroup analysis was also conducted in patients who had laboratory values (D-dimer, C-reactive protein, creatinine, and absolute neutrophil to absolute lymphocyte ratio) present. The primary effectiveness endpoint was the need for ICU admission within 48 hours of hospital admission.

RESULTS

A total of 2503 patients were included in this study. CDS reach approached 95% during implementation. Adherence achieved a peak of 72% during implementation. Variation was noted in adoption across sites and nursing units. Adoption was the highest at hospitals that were specifically transformed to only provide care to patients with COVID-19 (COVID-19 cohorted hospitals; 74%-82%) and the lowest in academic settings (47%-55%). CPG delivery via the CDS system was associated with improved adherence (odds ratio [OR] 1.43, 95% CI 1.2-1.7; P<.001). Adherence with the anticoagulation CPG was associated with a significant reduction in the need for ICU admission within 48 hours (OR 0.39, 95% CI 0.30-0.51; P<.001) on multivariable logistic regression analysis. Similar findings were noted following 1:1 propensity score matching for patients who received adherent versus nonadherent care (21.5% vs 34.3% incidence of ICU admission within 48 hours; log-rank test P<.001).

CONCLUSIONS

Our institutional experience demonstrated that adherence with the institutional CPG delivered via the CDS system resulted in improved clinical outcomes for patients with COVID-19. CDS systems are an effective means to rapidly scale a CPG across a heterogeneous health care system. Further research is needed to investigate factors associated with adherence at low and high adopting sites and nursing units.

Death Toll of COVID-19 on Asian Americans: Disparities Revealed

The coronavirus disease 2019 (COVID-19) pandemic has underscored the structural inequities facing communities of color and its consequences in lives lost. However, little is known about the COVID-related disparities facing Asian Americans amidst the heightened racism and violence against this community. We analyze the mortality toll of COVID-19 on Asian Americans using multiple measures. In 2020, one in seven Asian American deaths was attributable to COVID-19. We find that while Asian Americans make up a small proportion of COVID-19 deaths in the USA, they experience significantly higher excess all-cause mortality (3.1 times higher), case fatality rate (as high as 53% higher), and percentage of deaths attributed to COVID-19 (2.1 times higher) compared to non-Hispanic Whites. Mounting evidence suggest that disproportionately low testing rates, greater disease severity at care presentation, socioeconomic factors, and racial discrimination contribute to the observed disparities. Improving data reporting and uniformly confronting racism are key components to addressing health inequities facing communities of color.

Outpatient and inpatient anticoagulation therapy and the risk for hospital admission and death among COVID-19 patients

BACKGROUND

Coronavirus disease 2019 (COVID-19) is associated with a hypercoagulable state. Limited data exist informing the relationship between anticoagulation therapy and risk for COVID-19 related hospitalization and mortality.

METHODS

We evaluated all patients over the age of 18 diagnosed with COVID-19 in a prospective cohort study from March 4th to August 27th, 2020 among 12 hospitals and 60 clinics of M Health Fairview system (USA). We investigated the relationship between (1) 90-day anticoagulation therapy among outpatients before COVID-19 diagnosis and the risk for hospitalization and mortality and (2) Inpatient anticoagulation therapy and mortality risk.

FINDINGS

Of 6195 patients, 598 were immediately hospitalized and 5597 were treated as outpatients. The overall case-fatality rate was 2•8% (n = 175 deaths). Among the patients who were hospitalized, the inpatient mortality was 13%. Among the 5597 COVID-19 patients initially treated as outpatients, 160 (2.9%) were on anticoagulation and 331 were eventually hospitalized (5.9%). In a multivariable analysis, outpatient anticoagulation use was associated with a 43% reduction in risk for hospital admission, HR (95% CI = 0.57, 0.38-0.86), p = 0.007, but was not associated with mortality, HR (95% CI=0.88, 0.50 - 1.52), p = 0.64. Inpatients who were not on anticoagulation (before or after hospitalization) had an increased risk for mortality, HR (95% CI = 2.26, 1.17-4.37), p = 0.015.

INTERPRETATION

Outpatients with COVID-19 who were on outpatient anticoagulation at the time of diagnosis experienced a 43% reduced risk of hospitalization. Failure to initiate anticoagulation upon hospitalization or maintaining outpatient anticoagulation in hospitalized COVID-19 patients was associated with increased mortality risk.

FUNDING

No funding was obtained for this study.

Disparities in COVID-19 Outcomes by Race, Ethnicity, and Socioeconomic Status: A Systematic-Review and Meta-analysis

IMPORTANCE

COVID-19 has disproportionately affected racial and ethnic minority groups, and race and ethnicity have been associated with disease severity. However, the association of socioeconomic determinants with racial disparities in COVID-19 outcomes remains unclear.

OBJECTIVE

To evaluate the association of race and ethnicity with COVID-19 outcomes and to examine the association between race, ethnicity, COVID-19 outcomes, and socioeconomic determinants.

DATA SOURCES

A systematic search of PubMed, medRxiv, bioRxiv, Embase, and the World Health Organization COVID-19 databases was performed for studies published from January 1, 2020, to January 6, 2021.

STUDY SELECTION

Studies that reported data on associations between race and ethnicity and COVID-19 positivity, disease severity, and socioeconomic status were included and screened by 2 independent reviewers. Studies that did not have a satisfactory quality score were excluded. Overall, less than 1% (0.47%) of initially identified studies met selection criteria.

DATA EXTRACTION AND SYNTHESIS

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Associations were assessed using adjusted and unadjusted risk ratios (RRs) and odds ratios (ORs), combined prevalence, and metaregression. Data were pooled using a random-effects model.

MAIN OUTCOMES AND MEASURES

The main measures were RRs, ORs, and combined prevalence values.

RESULTS

A total of 4 318 929 patients from 68 studies were included in this meta-analysis. Overall, 370 933 patients (8.6%) were African American, 9082 (0.2%) were American Indian or Alaska Native, 101 793 (2.4%) were Asian American, 851 392 identified as Hispanic/Latino (19.7%), 7417 (0.2%) were Pacific Islander, 1 037 996 (24.0%) were White, and 269 040 (6.2%) identified as multiracial and another race or ethnicity. In age- and sex-adjusted analyses, African American individuals (RR, 3.54; 95% CI, 1.38-9.07; P = .008) and Hispanic individuals (RR, 4.68; 95% CI, 1.28-17.20; P = .02) were the most likely to test positive for COVID-19. Asian American individuals had the highest risk of intensive care unit admission (RR, 1.93; 95% CI, 1.60-2.34, P < .001). The area deprivation index was positively correlated with mortality rates in Asian American and Hispanic individuals (P < .001). Decreased access to clinical care was positively correlated with COVID-19 positivity in Hispanic individuals (P < .001) and African American individuals (P < .001).

CONCLUSIONS AND RELEVANCE

In this study, members of racial and ethnic minority groups had higher risks of COVID-19 positivity and disease severity. Furthermore, socioeconomic determinants were strongly associated with COVID-19 outcomes in racial and ethnic minority populations.

Rates of Influenza-Associated Hospitalization, Intensive Care Unit Admission, and In-Hospital Death by Race and Ethnicity in the United States From 2009 to 2019

IMPORTANCE

Racial and ethnic minority groups, such as Black, Hispanic, American Indian or Alaska Native, and Asian or Pacific Islander persons, often experience higher rates of severe influenza disease.

OBJECTIVE

To describe rates of influenza-associated hospitalization, intensive care unit (ICU) admission, and in-hospital death by race and ethnicity over 10 influenza seasons.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data from the Influenza-Associated Hospitalization Surveillance Network (FluSurv-NET), which conducts population-based surveillance for laboratory-confirmed influenza-associated hospitalizations in selected counties, representing approximately 9% of the US population. Influenza hospitalizations from the 2009 to 2010 season to the 2018 to 2019 season were analyzed. Data were analyzed from October 2020 to July 2021.

MAIN OUTCOMES AND MEASURES

The main outcomes were age-adjusted and age-stratified rates of influenza-associated hospitalization, ICU admission, and in-hospital death by race and ethnicity overall and by influenza season.

RESULTS

Among 113 352 persons with an influenza-associated hospitalization (34 436 persons [32.0%] aged ≥75 years; 61 009 [53.8%] women), 70 225 persons (62.3%) were non-Hispanic White (White), 24 850 persons (21.6%) were non-Hispanic Black (Black), 11 903 persons (10.3%) were Hispanic, 5517 persons (5.1%) were non-Hispanic Asian or Pacific Islander, and 857 persons (0.7%) were non-Hispanic American Indian or Alaska Native. Among persons aged younger than 75 years and compared with White persons of the same ages, Black persons were more likely to be hospitalized (eg, age 50-64 years: rate ratio [RR], 2.50 95% CI, 2.43-2.57) and to be admitted to an ICU (eg, age 50-64 years: RR, 2.09; 95% CI, 1.96-2.23). Among persons aged younger than 50 years and compared with White persons of the same ages, American Indian or Alaska Native persons were more likely to be hospitalized (eg, age 18-49 years: RR, 1.72; 95% CI, 1.51-1.96) and to be admitted to an ICU (eg, age 18-49 years: RR, 1.84; 95% CI, 1.40-2.42). Among children aged 4 years or younger and compared with White children, hospitalization rates were higher in Black children (RR, 2.21; 95% CI, 2.10-2.33), Hispanic children (RR, 1.87; 95% CI, 1.77-1.97), American Indian or Alaska Native children (RR, 3.00; 95% CI, 2.55-3.53), and Asian or Pacific Islander children (RR, 1.26; 95% CI, 1.16-1.38), as were rates of ICU admission (Black children: RR, 2.74; 95% CI, 2.43-3.09; Hispanic children: RR, 1.96; 95% CI, 1.73-2.23; American Indian and Alaska Native children: RR, 3.51; 95% CI, 2.45-5.05). In this age group and compared with White children, in-hospital death rates were higher among Hispanic children (RR, 2.98; 95% CI, 1.23-7.19), Black children (RR, 3.39; 95% CI, 1.40-8.18), and Asian or Pacific Islander children (RR, 4.35; 95% CI, 1.55-12.22). Few differences were observed in rates of severe influenza-associated outcomes by race and ethnicity among adults aged 75 years or older. For example, in this age group, compared with White adults, hospitalization rates were slightly higher only among Black adults (RR, 1.05; 95% CI 1.02-1.09). Overall, Black persons had the highest age-adjusted hospitalization rate (68.8 [95% CI, 68.0-69.7] hospitalizations per 100 000 population) and ICU admission rate (11.6 [95% CI, 11.2-11.9] admissions per 100 000 population).

CONCLUSIONS AND RELEVANCE

This cross-sectional study found racial and ethnic disparities in rates of severe influenza-associated disease. These data identified subgroups for whom improvements in influenza prevention efforts could be targeted.

A Prospective Observational Study to Investigate Performance of a Chest X-ray Artificial Intelligence Diagnostic Support Tool Across 12 U.S. Hospitals

Importance

An artificial intelligence (AI)-based model to predict COVID-19 likelihood from chest x-ray (CXR) findings can serve as an important adjunct to accelerate immediate clinical decision making and improve clinical decision making. Despite significant efforts, many limitations and biases exist in previously developed AI diagnostic models for COVID-19. Utilizing a large set of local and international CXR images, we developed an AI model with high performance on temporal and external validation.

Objective

Investigate real-time performance of an AI-enabled COVID-19 diagnostic support system across a 12-hospital system.

Design

Prospective observational study.

Setting

Labeled frontal CXR images (samples of COVID-19 and non-COVID-19) from the M Health Fairview (Minnesota, USA), Valencian Region Medical ImageBank (Spain), MIMIC-CXR, Open-I 2013 Chest X-ray Collection, GitHub COVID-19 Image Data Collection (International), Indiana University (Indiana, USA), and Emory University (Georgia, USA).

Participants

Internal (training, temporal, and real-time validation): 51,592 CXRs; Public: 27,424 CXRs; External (Indiana University): 10,002 CXRs; External (Emory University): 2002 CXRs.

Main Outcome and Measure

Model performance assessed via receiver operating characteristic (ROC), Precision-Recall curves, and F1 score.

Results

Patients that were COVID-19 positive had significantly higher COVID-19 Diagnostic Scores (median .1 [IQR: 0.0-0.8] vs median 0.0 [IQR: 0.0-0.1], p < 0.001) than patients that were COVID-19 negative. Pre-implementation the AI-model performed well on temporal validation (AUROC 0.8) and external validation (AUROC 0.76 at Indiana U, AUROC 0.72 at Emory U). The model was noted to have unrealistic performance (AUROC > 0.95) using publicly available databases. Real-time model performance was unchanged over 19 weeks of implementation (AUROC 0.70). On subgroup analysis, the model had improved discrimination for patients with "severe" as compared to "mild or moderate" disease, p < 0.001. Model performance was highest in Asians and lowest in whites and similar between males and females.

Conclusions and Relevance

AI-based diagnostic tools may serve as an adjunct, but not replacement, for clinical decision support of COVID-19 diagnosis, which largely hinges on exposure history, signs, and symptoms. While AI-based tools have not yet reached full diagnostic potential in COVID-19, they may still offer valuable information to clinicians taken into consideration along with clinical signs and symptoms.

Changes in pediatric trauma during COVID-19 stay-at-home epoch at a tertiary pediatric hospital

BACKGROUND

Trauma is the leading cause of morbidity and mortality in the pediatric population. However, during the societal disruptions secondary to the coronavirus (COVID-19) stay-at-home regulations, there have been reported changes to the pattern and severity of pediatric trauma. We review our two-institution experience.

METHODS

Pediatric trauma emergency department (ED) encounters from the National Trauma Registry for a large, tertiary, metropolitan level 1 pediatric trauma center and pediatric burn admission at the regional burn center were extracted for children less than 19 years from March 15th thru May 15th during the years 2015-2020. The primary outcome was the difference in encounters during the COVID-19 (2020) epoch versus the pre-COVID-19 epoch (2015-2019).

RESULTS

There were 392 pediatric trauma encounters during the COVID-19 epoch as compared to 451, 475, 520, 460, 432 (mean 467.6) during the pre-COVID-19 epoch. Overall trauma admissions and ED trauma encounters were significantly lower (p < 0.001) during COVID-19. Burn injury admissions (p < 0.001) and penetrating trauma encounters (p = 0.002) increased during the COVID-19 epoch while blunt trauma encounters decreased (p < 0.001). Trauma occurred among more white (p = 0.01) and privately insured (p < 0.001) children, but no difference in suspected abuse, injury severity, mortality, age, or gender were detected. Sub-analysis showed significant decreases in motor vehicle crashes (p < 0.001), pedestrians struck by automobile (p < 0.001), all-terrain vehicle (ATV)/motorcross/bicycle/skateboard involved injuries (p = 0.02), falls (p < 0.001), and sports related injuries (p < 0.001). Fewer injuries occurring in the playground or home play equipment such as trampolines neared significance (p = 0.05). Interpersonal violence (assault, NAT, self-harm) was lower during the COVID-19 era (p = 0.04). For burn admissions, there was a significant increase in flame burns (p < 0.001).

CONCLUSIONS

Stay-at-home regulations alter societal patterns, leading to decreased overall and blunt traumas. However, the proportion of penetrating and burn injuries increased. Owing to increased stressors and time spent at home, healthcare professionals should keep a high suspicion for abuse and neglect.