Hospitalization Associated With Comorbid Psychiatric and Substance Use Disorders Among Adults With COVID-19 Treated in US Emergency Departments From April 2020 to August 2021

Importance

During the COVID-19 pandemic, US emergency department (ED) visits for psychiatric disorders (PDs) and drug overdoses increased. Psychiatric disorders and substance use disorders (SUDs) independently increased the risk of COVID-19 hospitalization, yet their effect together is unknown.

Objective

To assess how comorbid PD and SUD are associated with the probability of hospitalization among ED patients with COVID-19.

Design, Setting, and Participants

This retrospective cross-sectional study analyzed discharge data for adults (age ≥18 years) with a COVID-19 diagnosis treated in 970 EDs and inpatient hospitals in the United States from April 2020 to August 2021.

Exposures

Any past diagnosis of (1) SUD from opioids, stimulants, alcohol, cannabis, cocaine, sedatives, or other substances and/or (2) PD, including attention-deficit/hyperactivity disorder (ADHD), anxiety, bipolar disorder, major depression, other mood disorder, posttraumatic stress disorder (PTSD), or schizophrenia.

Main Outcomes and Measures

The main outcome was any hospitalization. Differences in probability of hospitalization were calculated to assess its association with both PD and SUD compared with PD alone, SUD alone, or neither condition.

Results

Of 1 274 219 ED patients with COVID-19 (mean [SD] age, 54.6 [19.1] years; 667 638 women [52.4%]), 18.6% had a PD (mean age, 59.0 years; 37.7% men), 4.6% had a SUD (mean age, 50.1 years; 61.7% men), and 2.3% had both (mean age, 50.4 years; 53.1% men). The most common PDs were anxiety (12.9%), major depression (9.8%), poly (≥2) PDs (6.4%), and schizophrenia (1.4%). The most common SUDs involved alcohol (2.1%), cannabis (1.3%), opioids (1.0%), and poly (≥2) SUDs (0.9%). Prevalence of SUD among patients with PTSD, schizophrenia, other mood disorder, or ADHD each exceeded 21%. Based on significant specific PD-SUD pairs (Q < .05), probability of hospitalization of those with both PD and SUD was higher than those with (1) neither condition by a weighted mean of 20 percentage points (range, 6 to 36; IQR, 16 to 25); (2) PD alone by 12 percentage points (range, -4 to 31; IQR, 8 to 16); and (3) SUD alone by 4 percentage points (range, -7 to 15; IQR, -2 to 7). Associations varied by types of PD and SUD. Substance use disorder was a stronger predictor of hospitalization than PD.

Conclusions and Relevance

This study found that patients with both PD and SUD had a greater probability of hospitalization, compared with those with either disorder alone or neither disorder. Substance use disorders appear to have a greater association than PDs with the probability of hospitalization. Overlooking possible coexisting PD and SUD in ED patients with COVID-19 can underestimate the likelihood of hospitalization. Screening and assessment of both conditions are needed.

Hospitalizations for COVID-19 Among US People Experiencing Incarceration or Homelessness

IMPORTANCE

People experiencing incarceration (PEI) and people experiencing homelessness (PEH) have an increased risk of COVID-19 exposure from congregate living, but data on their hospitalization course compared with that of the general population are limited.

OBJECTIVE

To compare COVID-19 hospitalizations for PEI and PEH with hospitalizations among the general population.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional analysis used data from the Premier Healthcare Database on 3415 PEI and 9434 PEH who were evaluated in the emergency department or were hospitalized in more than 800 US hospitals for COVID-19 from April 1, 2020, to June 30, 2021.

EXPOSURES

Incarceration or homelessness.

MAIN OUTCOMES AND MEASURES

Hospitalization proportions were calculated. and outcomes (intensive care unit admission, invasive mechanical ventilation [IMV], mortality, length of stay, and readmissions) among PEI and PEH were compared with outcomes for all patients with COVID-19 (not PEI or PEH). Multivariable regression was used to adjust for potential confounders.

RESULTS

In total, 3415 PEI (2952 men [86.4%]; mean [SD] age, 50.8 [15.7] years) and 9434 PEH (6776 men [71.8%]; mean [SD] age, 50.1 [14.5] years) were evaluated in the emergency department for COVID-19 and were hospitalized more often (2170 of 3415 [63.5%] PEI; 6088 of 9434 [64.5%] PEH) than the general population (624 470 of 1 257 250 [49.7%]) (P < .001). Both PEI and PEH hospitalized for COVID-19 were more likely to be younger, male, and non-Hispanic Black than the general population. Hospitalized PEI had a higher frequency of IMV (410 [18.9%]; adjusted risk ratio [aRR], 1.16; 95% CI, 1.04-1.30) and mortality (308 [14.2%]; aRR, 1.28; 95% CI, 1.11-1.47) than the general population (IMV, 88 897 [14.2%]; mortality, 84 725 [13.6%]). Hospitalized PEH had a lower frequency of IMV (606 [10.0%]; aRR, 0.64; 95% CI, 0.58-0.70) and mortality (330 [5.4%]; aRR, 0.53; 95% CI, 0.47-0.59) than the general population. Both PEI and PEH had longer mean (SD) lengths of stay (PEI, 9 [10] days; PEH, 11 [26] days) and a higher frequency of readmission (PEI, 128 [5.9%]; PEH, 519 [8.5%]) than the general population (mean [SD] length of stay, 8 [10] days; readmission, 28 493 [4.6%]).

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, a higher frequency of COVID-19 hospitalizations for PEI and PEH underscored the importance of adhering to recommended prevention measures. Expanding medical respite may reduce hospitalizations in these disproportionately affected populations.

Underlying Medical Conditions and Severe Illness Among 540,667 Adults Hospitalized With COVID-19, March 2020-March 2021

INTRODUCTION

Severe COVID-19 illness in adults has been linked to underlying medical conditions. This study identified frequent underlying conditions and their attributable risk of severe COVID-19 illness.

METHODS

We used data from more than 800 US hospitals in the Premier Healthcare Database Special COVID-19 Release (PHD-SR) to describe hospitalized patients aged 18 years or older with COVID-19 from March 2020 through March 2021. We used multivariable generalized linear models to estimate adjusted risk of intensive care unit admission, invasive mechanical ventilation, and death associated with frequent conditions and total number of conditions.

RESULTS

Among 4,899,447 hospitalized adults in PHD-SR, 540,667 (11.0%) were patients with COVID-19, of whom 94.9% had at least 1 underlying medical condition. Essential hypertension (50.4%), disorders of lipid metabolism (49.4%), and obesity (33.0%) were the most common. The strongest risk factors for death were obesity (adjusted risk ratio [aRR] = 1.30; 95% CI, 1.27-1.33), anxiety and fear-related disorders (aRR = 1.28; 95% CI, 1.25-1.31), and diabetes with complication (aRR = 1.26; 95% CI, 1.24-1.28), as well as the total number of conditions, with aRRs of death ranging from 1.53 (95% CI, 1.41-1.67) for patients with 1 condition to 3.82 (95% CI, 3.45-4.23) for patients with more than 10 conditions (compared with patients with no conditions).

CONCLUSION

Certain underlying conditions and the number of conditions were associated with severe COVID-19 illness. Hypertension and disorders of lipid metabolism were the most frequent, whereas obesity, diabetes with complication, and anxiety disorders were the strongest risk factors for severe COVID-19 illness. Careful evaluation and management of underlying conditions among patients with COVID-19 can help stratify risk for severe illness.

Underlying Medical Conditions Associated With Severe COVID-19 Illness Among Children

IMPORTANCE

Information on underlying conditions and severe COVID-19 illness among children is limited.

OBJECTIVE

To examine the risk of severe COVID-19 illness among children associated with underlying medical conditions and medical complexity.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study included patients aged 18 years and younger with International Statistical Classification of Diseases, Tenth Revision, Clinical Modification code U07.1 (COVID-19) or B97.29 (other coronavirus) during an emergency department or inpatient encounter from March 2020 through January 2021. Data were collected from the Premier Healthcare Database Special COVID-19 Release, which included data from more than 800 US hospitals. Multivariable generalized linear models, controlling for patient and hospital characteristics, were used to estimate adjusted risk of severe COVID-19 illness associated with underlying medical conditions and medical complexity.

EXPOSURES

Underlying medical conditions and medical complexity (ie, presence of complex or noncomplex chronic disease).

MAIN OUTCOMES AND MEASURES

Hospitalization and severe illness when hospitalized (ie, combined outcome of intensive care unit admission, invasive mechanical ventilation, or death).

RESULTS

Among 43 465 patients with COVID-19 aged 18 years or younger, the median (interquartile range) age was 12 (4-16) years, 22 943 (52.8%) were female patients, and 12 491 (28.7%) had underlying medical conditions. The most common diagnosed conditions were asthma (4416 [10.2%]), neurodevelopmental disorders (1690 [3.9%]), anxiety and fear-related disorders (1374 [3.2%]), depressive disorders (1209 [2.8%]), and obesity (1071 [2.5%]). The strongest risk factors for hospitalization were type 1 diabetes (adjusted risk ratio [aRR], 4.60; 95% CI, 3.91-5.42) and obesity (aRR, 3.07; 95% CI, 2.66-3.54), and the strongest risk factors for severe COVID-19 illness were type 1 diabetes (aRR, 2.38; 95% CI, 2.06-2.76) and cardiac and circulatory congenital anomalies (aRR, 1.72; 95% CI, 1.48-1.99). Prematurity was a risk factor for severe COVID-19 illness among children younger than 2 years (aRR, 1.83; 95% CI, 1.47-2.29). Chronic and complex chronic disease were risk factors for hospitalization, with aRRs of 2.91 (95% CI, 2.63-3.23) and 7.86 (95% CI, 6.91-8.95), respectively, as well as for severe COVID-19 illness, with aRRs of 1.95 (95% CI, 1.69-2.26) and 2.86 (95% CI, 2.47-3.32), respectively.

CONCLUSIONS AND RELEVANCE

This cross-sectional study found a higher risk of severe COVID-19 illness among children with medical complexity and certain underlying conditions, such as type 1 diabetes, cardiac and circulatory congenital anomalies, and obesity. Health care practitioners could consider the potential need for close observation and cautious clinical management of children with these conditions and COVID-19.

Risk of Clinical Severity by Age and Race/Ethnicity Among Adults Hospitalized for COVID-19-United States, March-September 2020

Background

Older adults and people from certain racial and ethnic groups are disproportionately represented in coronavirus disease 2019 (COVID-19) hospitalizations and deaths.

Methods

Using data from the Premier Healthcare Database on 181813 hospitalized adults diagnosed with COVID-19 during March–September 2020, we applied multivariable log-binomial regression to assess the associations between age and race/ethnicity and COVID-19 clinical severity (intensive care unit [ICU] admission, invasive mechanical ventilation [IMV], and death) and to determine whether the impact of age on clinical severity differs by race/ethnicity.

Results

Overall, 84497 (47%) patients were admitted to the ICU, 29078 (16%) received IMV, and 27864 (15%) died in the hospital. Increased age was strongly associated with clinical severity when controlling for underlying medical conditions and other covariates; the strength of this association differed by race/ethnicity. Compared with non-Hispanic White patients, risk of death was lower among non-Hispanic Black patients (adjusted risk ratio, 0.96; 95% CI, 0.92–0.99) and higher among Hispanic/Latino patients (risk ratio [RR], 1.15; 95% CI, 1.09–1.20), non-Hispanic Asian patients (RR, 1.16; 95% CI, 1.09–1.23), and patients of other racial and ethnic groups (RR, 1.13; 95% CI, 1.06–1.21). Risk of ICU admission and risk of IMV were elevated among some racial and ethnic groups.

Conclusions

These results indicate that age is a driver of poor outcomes among hospitalized persons with COVID-19. Additionally, clinical severity may be elevated among patients of some racial and ethnic minority groups. Public health strategies to reduce severe acute respiratory syndrome coronavirus 2 infection rates among older adults and racial and ethnic minorities are essential to reduce poor outcomes.

Hydroxychloroquine and Chloroquine Prescribing Patterns by Provider Specialty Following Initial Reports of Potential Benefit for COVID-19 Treatment - United States, January-June 2020

Hydroxychloroquine and chloroquine, primarily used to treat autoimmune diseases and to prevent and treat malaria, received national attention in early March 2020, as potential treatment and prophylaxis for coronavirus disease 2019 (COVID-19) (1). On March 20, the Food and Drug Administration (FDA) issued an emergency use authorization (EUA) for chloroquine phosphate and hydroxychloroquine sulfate in the Strategic National Stockpile to be used by licensed health care providers to treat patients hospitalized with COVID-19 when the providers determine the potential benefit outweighs the potential risk to the patient.* Following reports of cardiac and other adverse events in patients receiving hydroxychloroquine for COVID-19 (2), on April 24, 2020, FDA issued a caution against its use^† and on June 15, rescinded its EUA for hydroxychloroquine from the Strategic National Stockpile.^§ Following the FDA's issuance of caution and EUA rescindment, on May 12 and June 16, the federal COVID-19 Treatment Guidelines Panel issued recommendations against the use of hydroxychloroquine or chloroquine to treat COVID-19; the panel also noted that at that time no medication could be recommended for COVID-19 pre- or postexposure prophylaxis outside the setting of a clinical trial (3). However, public discussion concerning the effectiveness of these drugs on outcomes of COVID-19 (4,5), and clinical trials of hydroxychloroquine for prophylaxis of COVID-19 continue.^¶ In response to recent reports of notable increases in prescriptions for hydroxychloroquine or chloroquine (6), CDC analyzed outpatient retail pharmacy transaction data to identify potential differences in prescriptions dispensed by provider type during January-June 2020 compared with the same period in 2019. Before 2020, primary care providers and specialists who routinely prescribed hydroxychloroquine, such as rheumatologists and dermatologists, accounted for approximately 97% of new prescriptions. New prescriptions by specialists who did not typically prescribe these medications (defined as specialties accounting for ≤2% of new prescriptions before 2020) increased from 1,143 prescriptions in February 2020 to 75,569 in March 2020, an 80-fold increase from March 2019. Although dispensing trends are returning to prepandemic levels, continued adherence to current clinical guidelines for the indicated use of these medications will ensure their availability and benefit to patients for whom their use is indicated (3,4), because current data on treatment and pre- or postexposure prophylaxis for COVID-19 indicate that the potential benefits of these drugs do not appear to outweigh their risks.

County-Level Opioid Prescribing in the United States, 2015 and 2017

This study examines trends in opioid prescribing at the US national and county levels during 2015 and 2017.

Trends and Patterns of Geographic Variation in Opioid Prescribing Practices by State, United States, 2006-2017

IMPORTANCE

Risk of opioid use disorder, overdose, and death from prescription opioids increases as dosage, duration, and use of extended-release and long-acting formulations increase. States are well suited to respond to the opioid crisis through legislation, regulations, enforcement, surveillance, and other interventions.

OBJECTIVE

To estimate temporal trends and geographic variations in 6 key opioid prescribing measures in 50 US states and the District of Columbia.

DESIGN, SETTING, AND PARTICIPANTS

Population-based cross-sectional analysis of opioid prescriptions filled nationwide at US retail pharmacies between January 1, 2006, and December 31, 2017. Data were obtained from the IQVIA Xponent database. All US residents who had an opioid prescription filled at a US retail pharmacy were included.

MAIN OUTCOMES AND MEASURES

Primary outcomes were annual amount of opioids prescribed in morphine milligram equivalents (MME) per person; mean duration per prescription in days; and 4 separate prescribing rates-for prescriptions 3 or fewer days, those 30 days or longer, those with a high daily dosage (≥90 MME), and those with extended-release and long-acting formulations.

RESULTS

Between 2006 and 2017, an estimated 233.7 million opioid prescriptions were filled in retail pharmacies in the United States each year. For all states combined, 4 measures decreased: (1) mean (SD) amount of opioids prescribed (mean [SD] decrease, 12.8% [12.6%]) from 628.4 (178.0) to 543.4 (158.6) MME per person, a statistically significant decrease in 23 states; (2) high daily dosage (mean [SD] decrease, 53.1% [13.6%]) from 12.3 (3.4) to 5.6 (1.7) per 100 persons, a statistically significant decrease in 49 states; (3) short-term (≤3 days) duration (mean [SD] decrease, 43.1% [9.4%]) from 18.0 (5.4) to 10.0 (2.5) per 100 persons, a statistically significant decrease in 48 states; and (4) extended-release and long-acting formulations (mean [SD] decrease, 14.7% [13.7%]) from 7.2 (1.9) to 6.0 (1.7) per 100 persons, a statistically significant decrease in 27 states. Two measures increased, each associated with the duration of prescription dispensed: (1) mean (SD) prescription duration (mean [SD] increase, 37.6% [6.9%]) from 13.0 (1.2) to 17.9 (1.4) days, a statistically significant increase in every state; and (2) prescriptions for a term of 30 days or longer (mean [SD] increase, 37.7% [28.9%]) from 18.3 (7.7) to 24.9 (10.7) per 100 persons, a statistically significant increase in 39 states. Two- to 3-fold geographic differences were observed across states, measured by comparing the ratio of each state's 90th to 10th percentile for each measure.

CONCLUSIONS AND RELEVANCE

In this study, across 12 years, the mean duration and prescribing rate for long-term prescriptions of opioids increased, whereas the amount of opioids prescribed per person and prescribing rate for high-dosage prescriptions, short-term prescriptions, and extended-release and long-acting formulations decreased. Some decreases were significant, but results were still high. Two- to 3-fold state variation in 5 measures occurred in most states. This information may help when state-specific intervention programs are being designed.