title: Functional Status and Hospital Readmissions Using the Medical Expenditure Panel Survey.
abstract: BACKGROUND
  Hospital readmissions are expensive and they may signal poor quality of care. Whether functional status is related to hospital readmissions using a representative U.S sample remains unexplored .
  
  
  OBJECTIVE
  We aimed to assess the relationship between functional status and all-cause 30-day hospital readmissions using a representative sample of the US population.
  
  
  METHODS
  This was a retrospective observational study (2003-2011).
  
  
  METHODS
  The study included 3,772 patients who completed the SF-12 before being hospitalized. Three hundred and eighteen (8.4%) were readmitted within 30 days after being discharged.
  
  
  METHODS
  The Medical Expenditure Panel Survey (MEPS) was employed. Functional status was measured with the Short-Form 12-Item Health Survey Version 2® (SF-12). The probability of being readmitted was estimated using a logistic model controlling for demographic characteristics, comorbid conditions, insurance coverage, physical (PCS) and mental (MCS) summaries of the SF-12, reason for hospitalization, length of hospital stay, region, and residential area.
  
  
  RESULTS
  A one-unit difference in PCS reduced the odds of readmission by 2% (odds ratio 0.98 [95% CI, 0.97 to 0.99]; p < 0.001), which implies an 18% reduction in the odds of readmissions for a ten-unit difference (one standard deviation) in PCS. The c-statistic of the model was 0.72.
  
  
  CONCLUSIONS
  Baseline physical function is associated with hospital readmissions. The SF-12 improves the ability to identify patients at high risk of hospital readmission.
authors.affiliation: Center for the Assessment of Pharmaceutical Practices (CAPP), Department of Health Policy and Management, Boston University School of Public Health, Boston, MA, USA.
authors.forename: Marina
authors.initials: M
authors.lastname: Soley-Bori
authors.forename: Rene
authors.initials: R
authors.lastname: Soria-Saucedo
authors.forename: Colleen M
authors.initials: CM
authors.lastname: Ryan
authors.forename: Jeffrey C
authors.initials: JC
authors.lastname: Schneider
authors.forename: Alex B
authors.initials: AB
authors.lastname: Haynes
authors.forename: Paul
authors.initials: P
authors.lastname: Gerrard
authors.forename: Howard J
authors.initials: HJ
authors.lastname: Cabral
authors.forename: Keith D
authors.initials: KD
authors.lastname: Lillemoe
authors.forename: Lewis E
authors.initials: LE
authors.lastname: Kazis
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D015897:Comorbidity; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006304:Health Status; D006305:Health Status Indicators; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D010359:Patient Readmission / Q000191:economics / Q000706:statistics & numerical data*; D010809:Physical Fitness; D012189:Retrospective Studies; D014481:United States; D055815:Young Adult