title: The price of bouncing back: one-year mortality and payments for acute stroke patients with 30-day bounce-backs.
abstract: OBJECTIVE
  To examine 1-year mortality and healthcare payments of stroke patients experiencing zero, one and two or more bounce-backs within 30 days of discharge.
  
  
  METHODS
  Retrospective analysis of administrative data.
  
  
  METHODS
  Four hundred twenty-two hospitals in the southern and eastern United States.
  
  
  METHODS
  Eleven thousand seven hundred twenty-nine Medicare beneficiaries aged 65 and older surviving at least 30 days with acute ischemic stroke in 2000.
  
  
  METHODS
  One-year mortality and predicted total healthcare payments were calculated using log-normal parametric survival analysis and quantile regression, respectively. Models included sociodemographics, prior medical history, stroke severity, length of stay, and discharge site.
  
  
  RESULTS
  Crude survival at 1 year for the zero, one and two or more bounce-back groups was 83%, 67%, and 55%, respectively. The one bounce-back group had 49% shorter (time ratio (TR)=0.51, 95% confidence interval (CI)=0.46-0.56) and the two or more bounce-backs group had 68% shorter (TR=0.32, 95% CI=0.27-0.38) adjusted 1-year survival time than the zero bounce-back group. For high- and low-cost patients, adjusted predicted payments were greater with each additional bounce-back experienced.
  
  
  CONCLUSIONS
  Acute stroke patients experiencing bounce-backs within 30 days have strikingly poorer survival and higher healthcare payments over the subsequent year than their counterparts with no bounce-backs. Bounce-backs may serve as a simple predictor for identifying stroke patients at extremely high risk for poor outcomes.
authors.affiliation: Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin, USA. ajk@medicine.wisc.edu
authors.forename: Amy J H
authors.initials: AJ
authors.lastname: Kind
authors.forename: Maureen A
authors.initials: MA
authors.lastname: Smith
authors.forename: Jinn-Ing
authors.initials: JI
authors.lastname: Liou
authors.forename: Nancy
authors.initials: N
authors.lastname: Pandhi
authors.forename: Jennifer R
authors.initials: JR
authors.lastname: Frytak
authors.forename: Michael D
authors.initials: MD
authors.lastname: Finch
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data*; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008484:Medicaid / Q000191:economics; D006278:Medicare / Q000191:economics; D010359:Patient Readmission / Q000191:economics*; D011383:Progressive Patient Care / Q000191:economics; D012044:Regression Analysis; D012189:Retrospective Studies; D012307:Risk Factors; D020521:Stroke / Q000150:complications / Q000191:economics* / Q000208:ethnology / Q000401:mortality*; D015996:Survival Rate; D014481:United States / Q000453:epidemiology