Jeremy Y Feng1,2, Sara L Toomey3,4, Alan M Zaslavsky5, Mari M Nakamura3,4,6, Mark A Schuster3,4,7. 1. Divisions of General Pediatrics and jeremy.feng@childrens.harvard.edu. 2. Harvard Medical School, Harvard University, Boston, Massachusetts; and. 3. Divisions of General Pediatrics and. 4. Departments of Pediatrics and. 5. Health Care Policy, Harvard Medical School, Harvard University, Boston, Massachusetts. 6. Infectious Diseaseas, Boston Children's Hospital, Boston, Massachusetts. 7. Kaiser Permanente School of Medicine, Pasadena, California.
Abstract
BACKGROUND AND OBJECTIVES: Reducing readmissions is a major health care system goal. There is a gap in our understanding of pediatric readmission patterns after mental health (MH) admissions. With this study, we aimed to characterize the prevalence of readmissions after MH admissions, to identify patient-level factors and costs associated with readmissions, and to assess variation in readmission rates across hospitals. METHODS: Using the 2014 Healthcare Cost and Utilization Project all-payer Nationwide Readmissions Database, we conducted a retrospective cohort analysis of 253 309 admissions for 5- to 17-year-olds at acute-care hospitals in 22 states. We calculated 30-day unplanned readmission rates, lengths of stay, and costs by primary admission diagnosis. We used hierarchical regression models to assess differences in readmission rates by patient characteristics, primary diagnoses, and comorbid chronic conditions, and to estimate the variation in case mix-adjusted rates across hospitals. RESULTS: MH stays accounted for 18.7% (n = 47 397) of index admissions. The 30-day readmission rate for MH admissions was higher than for non-MH admissions (8.0% vs 6.2%; P < .001). Children who were ≤14 years old, had non-MH chronic conditions, and/or had public insurance were more likely to be readmitted than their peers (P < .001 for each). Adjusted rates varied across hospitals (P < .001) and were 97.9% greater for hospitals 1 SD above versus below (11.2% vs 5.6%) the mean. Adjusted readmission rates, lengths of stay, and costs differed by diagnosis (P < .001). CONCLUSIONS: The 30-day readmission rate was significantly higher after MH than non-MH admissions. Adjusted MH readmission rates varied substantially among hospitals, suggesting potential room for improvement.
BACKGROUND AND OBJECTIVES: Reducing readmissions is a major health care system goal. There is a gap in our understanding of pediatric readmission patterns after mental health (MH) admissions. With this study, we aimed to characterize the prevalence of readmissions after MH admissions, to identify patient-level factors and costs associated with readmissions, and to assess variation in readmission rates across hospitals. METHODS: Using the 2014 Healthcare Cost and Utilization Project all-payer Nationwide Readmissions Database, we conducted a retrospective cohort analysis of 253 309 admissions for 5- to 17-year-olds at acute-care hospitals in 22 states. We calculated 30-day unplanned readmission rates, lengths of stay, and costs by primary admission diagnosis. We used hierarchical regression models to assess differences in readmission rates by patient characteristics, primary diagnoses, and comorbid chronic conditions, and to estimate the variation in case mix-adjusted rates across hospitals. RESULTS: MH stays accounted for 18.7% (n = 47 397) of index admissions. The 30-day readmission rate for MH admissions was higher than for non-MH admissions (8.0% vs 6.2%; P < .001). Children who were ≤14 years old, had non-MH chronic conditions, and/or had public insurance were more likely to be readmitted than their peers (P < .001 for each). Adjusted rates varied across hospitals (P < .001) and were 97.9% greater for hospitals 1 SD above versus below (11.2% vs 5.6%) the mean. Adjusted readmission rates, lengths of stay, and costs differed by diagnosis (P < .001). CONCLUSIONS: The 30-day readmission rate was significantly higher after MH than non-MH admissions. Adjusted MH readmission rates varied substantially among hospitals, suggesting potential room for improvement.
Authors: Thaciana Dos Santos Alcântara; Fernando Castro de Araújo Neto; Helena Ferreira Lima; Dyego Carlos S Anacleto de Araújo; Júlia Mirão Sanchez; Giulyane Targino Aires-Moreno; Carina de Carvalho Silvestre; Divaldo P de Lyra Junior Journal: Int J Clin Pharm Date: 2020-11-11
Authors: Stephanie Doupnik; Jonathan Rodean; Bonnie T Zima; Tumaini R Coker; Diana Worsley; Kris P Rehm; James C Gay; Matt Hall; Steve Marcus Journal: J Hosp Med Date: 2018-11 Impact factor: 2.960