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J Asthma ; 55(7): 695-704, 2018 07.
Article in English | MEDLINE | ID: mdl-28837382

ABSTRACT

OBJECTIVE: Previous single-center studies have reported that up to 40% of children hospitalized for asthma will be readmitted. The study objectives are to investigate the prevalence and timing of 30-day readmissions in children hospitalized with asthma, and to identify factors associated with 30-day readmissions. METHODS: Data (n = 12,842) for children aged 6-18 years hospitalized for asthma were obtained from the 2013 Nationwide Readmission Database (NRD). The primary study outcome was time to readmission within 30 days after discharge attributable to any cause. Several predictors associated with the risk of admission were included: patient (age, sex, median household income, insurance type, county location, and pediatric chronic complex condition), admission (type, day, emergency services utilization, length of stay (LOS), and discharge disposition), and hospital (ownership, bed size, and teaching status). Cox's proportional hazards model was used to identify predictors. RESULTS: Of 12,842 asthma-related index hospitalizations, 2.5% were readmitted within 30-days post-discharge. Time to event models identified significantly higher risk of readmission among asthmatic children aged 12-18 years, those who resided in micropolitan counties, those with >4-days LOS during index hospitalization, those who were hospitalized in an urban hospital, who had unfavorable discharge (hazard ratio 2.53, 95% confidence interval 1.33-4.79), and those who were diagnosed with a pediatric complex chronic condition, respectively, than children in respective referent categories. CONCLUSION: A multi-dimensional approach including effective asthma discharge action plans and follow-up processes, home-based asthma education, and neighborhood/community-level efforts to address disparities should be integrated into the routine clinical care of asthma children.


Subject(s)
Asthma/therapy , Patient Readmission/statistics & numerical data , Adolescent , Child , Databases, Factual/statistics & numerical data , Female , Health Services Accessibility/statistics & numerical data , Healthcare Disparities/statistics & numerical data , Humans , Income/statistics & numerical data , Length of Stay/statistics & numerical data , Male , Proportional Hazards Models , Risk Factors , Time Factors , United States
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