title: National characteristics and predictors of neurologic 30-day readmissions.
abstract: OBJECTIVE
  To examine national 30-day readmission rates for patients hospitalized with neurologic disorders.
  
  
  METHODS
  Using the University HealthSystem Consortium (UHC) database, we identified 554,399 index neurologic admissions from October 2011 through January 2015. We collected information regarding age, race, insurance payer, Medicare severity diagnosis-related group, and severity of illness. We examined readmission by diagnosis and performed multivariable logistic regression to determine predictors of readmission.
  
  
  RESULTS
  The unplanned readmission rate was 11.0%. Rates of unplanned readmission were highest for patients with peripheral nerve disorders (21.9%), CNS neoplasms (21.0%), nonhypertensive encephalopathy (15.5%), arterial stenosis (15.4%), and bacterial CNS infections (14.5%). In multivariable analysis, higher severity of illness and public health insurance coverage predicted higher rates of 30-day readmission.
  
  
  CONCLUSIONS
  We found significant variation in readmission rates for different neurologic disorders. These data provide insight into management of neurologic disease nationally, offering policymakers realistic goals for standards of care and challenging health care providers to develop systems-based solutions that will improve transitions of care for those at highest risk of readmission with neurologic disease.
authors.affiliation: From the Department of Neurology, University of California, San Francisco. Elan.Guterman@ucsf.edu.
authors.forename: Elan L
authors.initials: EL
authors.lastname: Guterman
authors.affiliation: From the Department of Neurology, University of California, San Francisco.
authors.forename: Vanja C
authors.initials: VC
authors.lastname: Douglas
authors.affiliation: From the Department of Neurology, University of California, San Francisco.
authors.forename: Maulik P
authors.initials: MP
authors.lastname: Shah
authors.affiliation: From the Department of Neurology, University of California, San Francisco.
authors.forename: Tennille
authors.initials: T
authors.lastname: Parsons
authors.affiliation: From the Department of Neurology, University of California, San Francisco.
authors.forename: Julio
authors.initials: J
authors.lastname: Barba
authors.affiliation: From the Department of Neurology, University of California, San Francisco.
authors.forename: S Andrew
authors.initials: SA
authors.lastname: Josephson
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002493:Central Nervous System Diseases / Q000453:epidemiology* / Q000628:therapy*; D016208:Databases, Factual; D006801:Humans; D007348:Insurance, Health / Q000706:statistics & numerical data; D016015:Logistic Models; D008875:Middle Aged; D015999:Multivariate Analysis; D010359:Patient Readmission / Q000706:statistics & numerical data*; D012720:Severity of Illness Index; D014481:United States / Q000453:epidemiology; D055815:Young Adult