Search

OBJECTIVES Healthcare utilization after bronchiolitis hospitalization is incompletely understood. We aimed to characterize readmissions and outpatient visits within 1 year after hospital discharge. METHODS Retrospective multicenter observational cohort study of children under 24-months old admitted with bronchiolitis between January 1, 2010 and December 12, 2019 to the Pediatric Health Information Systems database. A single-center nested subset using linked electronic health records allowed analysis of outpatient visits. RESULTS There were 308 306 admissions for bronchiolitis among 271 115 patients across 47 hospitals between 2010–2019. The percent of patients readmitted within 30 days after discharge was 6.0% (16 167 of 271 115), and 17.8% (48 332 of 271 115) of patients were readmitted within 1 year. 22.9% (16 919 of 74 001) of patients admitted to an ICU and 26.8% (7865 of 29 378) of patients undergoing mechanical ventilation were readmitted within 1 year. There were 1438 patients with outpatient healthcare data available. There were a median (interquartile range) of 9 (6–13) outpatient visits per patient within 1 year after discharge. Outpatient healthcare use increased for 4 months following bronchiolitis hospitalization compared with previously reported age-matched controls. Higher income, white race, commercial insurance, complex chronic conditions, ICU admission, and mechanical ventilation were associated with higher outpatient utilization. Higher quartiles of outpatient use were associated with readmission for bronchiolitis and all-cause readmissions. CONCLUSIONS Readmissions in the year after bronchiolitis hospitalization are common, and outpatient healthcare use is increased for 4 months following discharge. Prospective study is needed to track long-term outcomes of infants with bronchiolitis.

BACKGROUND During the coronavirus disease 2019 pandemic, many women physicians experienced increased caregiver responsibilities, potentially leading to worsened gender inequities. METHODS We surveyed faculty and trainees at a quaternary-care children’s hospital regarding work environment, household obligations, and academic productivity to examine differential effects on productivity by gender and parenting status. We used descriptive statistics for demographics and analyzed Likert-scale responses with χ2 or Fisher’s exact tests. We performed multivariable logistic regression to determine factors associated with self-reported academic productivity. We analyzed free-response comments using thematic analysis. RESULTS The August 2021 survey was completed by 366 respondents (65% women; 46% response rate). Women were significantly more likely to report decreased academic productivity than men (66% [146/222] vs 30% [38/129], P CONCLUSIONS The coronavirus disease 2019 pandemic has differentially impacted men and women physicians, with women physician parents more likely to report decreased academic productivity than men with children. Unreliable childcare was a significant contributor to this disparity. Institutions must prioritize initiatives to improve gender equity in medicine.

The objective of this study was to evaluate patient-specific factors associated with dexmedetomidine dose requirements during continuous infusion. A retrospective cross-sectional analysis of electronic health record-derived data spanning 10 years for patients admitted with a primary respiratory diagnosis at a quaternary children's hospital and who received a dexmedetomidine continuous infusion (n = 346 patients) was conducted. Penalized regression was used to select demographic, clinical, and medication characteristics associated with a median daily dexmedetomidine dose. Identified characteristics were included in multivariable linear regression models and sensitivity analyses. Critically ill children had a median hourly dexmedetomidine dose of 0.5 mcg/kg/h (range: 0.1–1.8), median daily dose of 6.7 mcg/kg/d (range: 0.9–38.4), and median infusion duration of 1.6 days (range: 0.25–5.0). Of 26 variables tested, 15 were selected in the final model with days of dexmedetomidine infusion (β: 1.9; 95% confidence interval [CI]: 1.6, 2.3), median daily morphine milligram equivalents dosing (mg/kg/d) (β: 0.3; 95% CI: 0.1, 0.5), median daily ketamine dosing (mg/kg/d) (β: 0.2; 95% CI: 0.1, 0.3), male sex (β: −1.1; 95% CI: −2.0, −0.2), and non-Black reported race (β: −1.2; 95% CI: −2.3, −0.08) significantly associated with median daily dexmedetomidine dose. Approximately 56% of dose variability was explained by the model. Readily obtainable information such as demographics, concomitant medications, and duration of infusion accounts for over half the variability in dexmedetomidine dosing. Identified factors, as well as additional environmental and genetic factors, warrant investigation in future studies to inform precision dosing strategies.

Supplemental Digital Content is available in the text., Introduction: The Centers for Disease Control and Prevention recommends tracking risk-adjusted antimicrobial prescribing. Prior studies have used prescribing variation to drive quality improvement initiatives without adjusting for severity of illness. The present study aimed to determine the relationship between antimicrobial prescribing and risk-adjusted ICU mortality in the Pediatric Health Information Systems (PHIS) database, assessed by IBM-Watson risk of mortality. A nested analysis sought to assess an alternative risk model incorporating laboratory data from federated electronic health records. Methods: Retrospective cohort study of pediatric ICU patients in PHIS between 1/1/2010 and 12/31/2019, excluding patients admitted to a neonatal ICU, and a nested study of PHIS+ from 1/1/2010 to 12/31/2012. Hospital antimicrobial prescription volumes were assessed for association with risk-adjusted mortality. Results: The cohort included 953,821 ICU encounters (23,851 [2.7%] nonsurvivors). There was 4-fold center-level variability in antimicrobial use. ICU antimicrobial use was not correlated with risk-adjusted mortality assessed using IBM-Watson. A risk model incorporating laboratory data available in PHIS+ significantly outperformed IBM-Watson (c-statistic 0.940 [95% confidence interval 0.933–0.947] versus 0.891 [0.881–0.901]; P < 0.001, area under the precision recall curve 0.561 versus 0.297). Risk-adjusted mortality was inversely associated with antimicrobial prescribing in this smaller cohort using both the PHIS+ and Watson models (P = 0.05 and P < 0.01, respectively). Conclusions: Antimicrobial prescribing among pediatric ICUs in the PHIS database is variable and not associated with risk-adjusted mortality as assessed by IBM-Watson. Expanding existing administrative databases to include laboratory data can achieve more meaningful insights when assessing multicenter antibiotic prescribing practices.