title: Patient Characteristics and Differences in Hospital Readmission Rates.
abstract: OBJECTIVE
  Medicare penalizes hospitals with higher than expected readmission rates by up to 3% of annual inpatient payments. Expected rates are adjusted only for patients' age, sex, discharge diagnosis, and recent diagnoses.
  
  
  OBJECTIVE
  To assess the extent to which a comprehensive set of patient characteristics accounts for differences in hospital readmission rates.
  
  
  METHODS
  Using survey data from the nationally representative Health and Retirement Study (HRS) and linked Medicare claims for HRS participants enrolled in Medicare who were hospitalized from 2009 to 2012 (n = 8067 admissions), we assessed 29 patient characteristics from survey data and claims as potential predictors of 30-day readmission when added to standard Medicare adjustments of hospital readmission rates. We then compared the distribution of these characteristics between participants admitted to hospitals with higher vs lower hospital-wide readmission rates reported by Medicare. Finally, we estimated differences in the probability of readmission between these groups of participants before vs after adjusting for the additional patient characteristics.
  
  
  METHODS
  All-cause readmission within 30 days of discharge.
  
  
  RESULTS
  Of the additional 29 patient characteristics assessed, 22 significantly predicted readmission beyond standard adjustments, and 17 of these were distributed differently between hospitals in the highest vs lowest quintiles of publicly reported hospital-wide readmission rates (P ≤ .04 for all comparisons). Almost all of these differences (16 of 17) indicated that participants admitted to hospitals in the highest quintile of readmission rates were more likely to have characteristics that were associated with a higher probability of readmission. The difference in the probability of readmission between participants admitted to hospitals in the highest vs lowest quintile of hospital-wide readmission rates was reduced by 48% from 4.41 percentage points with standard adjustments used by Medicare to 2.29 percentage points after adjustment for all patient characteristics assessed (reduction in difference: -2.12; 95% CI, -3.33 to -0.67; P = .003).
  
  
  CONCLUSIONS
  Patient characteristics not included in Medicare's current risk-adjustment methods explained much of the difference in readmission risk between patients admitted to hospitals with higher vs lower readmission rates. Hospitals with high readmission rates may be penalized to a large extent based on the patients they serve.
authors.affiliation: Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts2Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
authors.forename: Michael L
authors.initials: ML
authors.lastname: Barnett
authors.affiliation: Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts3Mongan Institute for Health Care Policy, Massachusetts General Hospital, Boston.
authors.forename: John
authors.initials: J
authors.lastname: Hsu
authors.affiliation: Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts2Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
authors.forename: J Michael
authors.initials: JM
authors.lastname: McWilliams
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D003953:Diagnosis-Related Groups / Q000191:economics / Q000706:statistics & numerical data; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D006278:Medicare / Q000191:economics / Q000706:statistics & numerical data; D008875:Middle Aged; D010043:Outcome and Process Assessment, Health Care / Q000379:methods; D010351:Patient Discharge / Q000706:statistics & numerical data*; D010359:Patient Readmission / Q000191:economics / Q000706:statistics & numerical data; D018570:Risk Assessment; D012737:Sex Factors; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires; D014481:United States