Abstract

Background and objectives: Hospital readmission rate helps to highlight the effectiveness of post-discharge care. There remains a paucity of plausible age-based categorization especially for ages below one year for hospital readmission rates.Methods: Data from the 2017 Healthcare Cost and Utilization Project National Readmissions Database was analyzed for ages 0-18 years. Logistic regression analysis was performed to identify predictors for unplanned early readmissions. Results: We identified 5,529,389 inpatient pediatric encounters which were further divided into age group cohorts. The overall rate of readmissions was identified at 3.2%. Beyond infancy, the readmission rate was found to be 6.7%. Across all age groups, the major predictors of unplanned readmission were cancers, diseases affecting transplant recipients and sickle cell patients. It was determined that reflux, milk protein allergy, hepatitis and inflammatory bowel diseases were significant diagnoses leading to readmission. Anxiety, depression and suicidal ideation depicted higher readmission rates in those older than 13 years. Across ages one to four years, dehydration, asthma and bronchiolitis were negative predictors of unplanned readmission. Conclusions: Thirty-day unplanned readmissions remain a problem leading to billions of taxpayer dollars lost per annum. Effective strategies for mandatory outpatient follow-up may help the financial aspect of care while also enhancing the quality of care.

Highlights

  • Readmission rates have long been used by clinicians, hospital systems, and health care commissions as a quality indicator

  • Thirty-day unplanned readmissions remain a problem leading to billions of taxpayer dollars lost per annum

  • The National Readmission Database (NRD) is a collection of all-age, all-payer discharges represented at the national level from U.S nonfederal hospitals produced by the Healthcare Cost and Utilization Project of the Agency for Healthcare Research and Quality [8]

Read more

Summary

Introduction

Readmission rates have long been used by clinicians, hospital systems, and health care commissions as a quality indicator. It has been suggested that pediatric data is becoming increasingly concentrated in large academic centers [5]. There is an increasing percentage of patients who are medically insured and there is a better patient-centered medical home provision along with accountable and coordinated care at multiple academic facilities [6]. Due to the improvement in neonatalperinatal healthcare strategies, a vast majority of children live longer with their chronic ailments and develop long-term consequences of the disease. This leads to an increase in the rate of unplanned readmissions [7]. There remains a paucity of plausible age-based categorization especially for ages below one year for hospital readmission rates

Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call