IMPORTANCE Black patients are overrepresented in the number of COVID-19 infections, hospitalizations, and deaths in the US. Reasons for this disparity may be due to underlying comorbidities or sociodemographic factors that require further exploration. OBJECTIVE To systematically determine patient characteristics associated with racial/ethnic disparities in COVID-19 outcomes. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study used comparative groups of patients tested or treated for COVID-19 at the University of Michigan from March 10, 2020, to April 22, 2020, with an outcome update through July 28, 2020. A group of randomly selected untested individuals were included for comparison. Examined factors included race/ethnicity, age, smoking, alcohol consumption, comorbidities, body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), and residential-level socioeconomic characteristics. EXPOSURE In-house polymerase chain reaction (PCR) tests, commercial antibody tests, nasopharynx or oropharynx PCR deployed by the Michigan Department of Health and Human Services and reverse transcription-PCR tests performed in external labs. MAIN OUTCOMES AND MEASURES The main outcomes were being tested for COVID-19, having test results positive for COVID-19 or being diagnosed with COVID-19, being hospitalized for COVID-19, requiring intensive care unit (ICU) admission for COVID-19, and COVID-19-related mortality (including inpatient and outpatient). Medical comorbidities were defined from the International Classification of Diseases, Ninth Revision, and International Classification of Diseases, Tenth Revision, codes and were aggregated into a comorbidity score. Associations with COVID-19 outcomes were examined using odds ratios (ORs). RESULTS Of 5698 patients tested for COVID-19 (mean [SD] age, 47.4 [20.9] years; 2167 [38.0%] men; mean [SD] BMI, 30.0 [8.0]), most were non-Hispanic White (3740 patients [65.6%]) or non-Hispanic Black (1058 patients [18.6%]). The comparison group included 7168 individuals who were not tested (mean [SD] age, 43.1 [24.1] years; 3257 [45.4%] men; mean [SD] BMI, 28.5 [7.1]). Among 1139 patients diagnosed with COVID-19, 492 (43.2%) were White and 442 (38.8%) were Black; 523 (45.9%) were hospitalized, 283 (24.7%) were admitted to the ICU, and 88 (7.7%) died. Adjusting for age, sex, socioeconomic status, and comorbidity score, Black patients were more likely to be hospitalized compared with White patients (OR, 1.72 [95% CI, 1.15-2.58]; P = .009). In addition to older age, male sex, and obesity, living in densely populated areas was associated with increased risk of hospitalization (OR, 1.10 [95% CI, 1.01-1.19]; P = .02). In the overall population, higher risk of hospitalization was also observed in patients with preexisting type 2 diabetes (OR, 1.82 [95% CI, 1.25-2.64]; P = .02) and kidney disease (OR, 2.87 [95% CI, 1.87-4.42]; P < .001). Compared with White (continued) Key Points Question What sociodemographic and underlying health conditions are associated w...

Background: We performed a phenome-wide association study to identify pre-existing conditions related to Coronavirus disease 2019 (COVID-19) prognosis across the medical phenome and how they vary by race. Methods: The study is comprised of 53,853 patients who were tested/diagnosed for COVID-19 between 10 March and 2 September 2020 at a large academic medical center. Results: Pre-existing conditions strongly associated with hospitalization were renal failure, pulmonary heart disease, and respiratory failure. Hematopoietic conditions were associated with intensive care unit (ICU) admission/mortality and mental disorders were associated with mortality in non-Hispanic Whites. Circulatory system and genitourinary conditions were associated with ICU admission/mortality in non-Hispanic Blacks. Conclusions: Understanding pre-existing clinical diagnoses related to COVID-19 outcomes informs the need for targeted screening to support specific vulnerable populations to improve disease prevention and healthcare delivery.

Background Acute diarrhoeal disease management often requires rehydration alone without antibiotics. However, non-indicated antibiotics are frequently ordered and this is an important driver of antimicrobial resistance. The mHealth Diarrhoea Management (mHDM) trial aimed to establish whether electronic decision support improves rehydration and antibiotic guideline adherence in resource-limited settings.Methods A cluster randomised controlled trial was done at ten district hospitals in Bangladesh. Inclusion criteria were patients aged 2 months or older with uncomplicated acute diarrhoea. Admission orders were observed without intervention in the pre-intervention period, followed by randomisation to electronic (rehydration calculator) or paper formatted WHO guidelines for the intervention period. The primary outcome was rate of intravenous fluid ordered as a binary variable. Generalised linear mixed-effect models, accounting for hospital clustering, served as the analytical framework; the analysis was intention to treat. The trial is registered with ClinicalTrials.gov (NCT03154229) and is completed. Findings From March 11 to Sept 10, 2018, 4975 patients (75•6%) of 6577 screened patients were enrolled. The intervention effect for the primary outcome showed no significant differences in rates of intravenous fluids ordered as a function of decision-support type. Intravenous fluid orders decreased by 0•9 percentage points for paper electronic decision support and 4•2 percentage points for electronic decision support, with a 4•2-point difference between decision-support types in the intervention period (paper 98•7% [95% CI 91•8-99•8] vs electronic 94•5% [72•2-99•1]; p interaction =0•31). Adverse events such as complications and mortality events were uncommon and could not be statistically estimated. Interpretation Although intravenous fluid orders did not change, electronic decision support was associated with increases in the volume of intravenous fluid ordered and decreases in antibiotics ordered, which are consistent with WHO guidelines.

Background: Laboratory-based respiratory polymerase chain reaction (PCR) panels are rarely used in outpatient pediatric practice due to prolonged turn-around times and cost of medical equipment. The BioFire FilmArray Respiratory Panel EZ (RP EZ) is a Clinical Laboratory Improvement Amendments–waived respiratory pathogen PCR panel which rapidly tests for 14 common respiratory organisms. The aim of this study was to identify the distribution of organisms seen in pediatric clinics and to determine if utilization of this point-of-care test improved disease management, while exploring impact on clinic workflow. Methods: From January 2018 through January 2019, when clinically appropriate, patients were tested by the RP EZ and/or antigen tests (Clinic A) or antigen test only (Clinic B). Residual samples from Clinic B antigen tests were frozen and later tested on the RP EZ for definitive pathogen identification. Patient data and prescription records were extracted from the electronic health record. Results: A total of 430 patients had RP EZ tests performed, and at least 1 organism was detected in 70.4% of patients. The most common organisms identified were human rhinovirus/enterovirus, influenza, and respiratory syncytial virus. Appropriate treatment occurred for 93.6% of patients when the RP EZ was performed (Clinic A) versus 87.9% of patients who had only antigen tests performed (Clinic B, P = 0.0445). Utilization of RP EZ testing also significantly reduced appointment duration time (48.0 versus 54.9 minutes, P = 0.0009). Three false-positive influenza B results were identified by antigen testing. Conclusions: A point-of-care PCR panel improved patient care by providing an accurate diagnosis and shortened appointment duration.

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