title: Readmission penalties and health insurance expansions: a dispatch from Massachusetts.
abstract: BACKGROUND
  Payers are penalizing hospitals for high readmission rates. It is unknown whether major changes in population insurance coverage can affect readmission rates, despite the Affordable Care Act's coverage expansions coming into effect this year.
  
  
  OBJECTIVE
  To evaluate the impact of a large-scale insurance expansion on hospital readmissions, using Massachusetts' 2006 health reform as a natural experiment.
  
  
  METHODS
  Difference-in-difference time-series design.
  
  
  METHODS
  All Massachusetts acute-care hospitals.
  
  
  METHODS
  Inpatient visits from 2004 to 2010.
  
  
  METHODS
  Primary outcome was the hospital 30-day readmission rate. Readmissions to any Massachusetts hospital were tracked.
  
  
  RESULTS
  Decreases in uninsurance rates during and after reform were largely limited to the hospital quartile with the highest prereform uninsurance rates (from 14% uninsured at the start of the reform to 2.9% by the end of the study period). The other hospitals collectively experienced a smaller decline in their uninsured admissions (5.9% at the start of reform to 2.5% by the end of the study period). According to difference-in-difference regression analysis, the highest uninsured hospital quartile experienced a modest increase in their unadjusted readmission rate of 0.6 percentage points (95% confidence interval: 0.1%-1.1%) during the reform period as compared to the other hospital quartiles (P = 0.01). This represents a relative increase of 4.5% in the readmission rate. Risk-adjusted readmission rates showed no corresponding change.
  
  
  CONCLUSIONS
  The Affordable Care Act's insurance expansion may be associated with an increase in unadjusted readmission rates among hospitals that cared for disproportionate numbers of uninsured patients. Risk-adjustment appears to take this effect into account.
authors.affiliation: School of Medicine, Washington University, St. Louis, Missouri.
authors.forename: Christopher
authors.initials: C
authors.lastname: Chen
authors.forename: Gabriel
authors.initials: G
authors.lastname: Scheffler
authors.forename: Amitabh
authors.initials: A
authors.lastname: Chandra
mesh_terms: D000328:Adult; D004469:Economics, Hospital / Q000331:legislation & jurisprudence / Q000639:trends; D005260:Female; D018166:Health Care Reform / Q000191:economics* / Q000331:legislation & jurisprudence; D054624:Health Status Disparities; D006801:Humans; D019458:Insurance Coverage / Q000191:economics* / Q000331:legislation & jurisprudence / Q000639:trends; D007348:Insurance, Health / Q000191:economics* / Q000331:legislation & jurisprudence / Q000639:trends; D008297:Male; D008404:Massachusetts; D017057:Medically Uninsured / Q000331:legislation & jurisprudence / Q000706:statistics & numerical data*; D006278:Medicare / Q000191:economics / Q000331:legislation & jurisprudence / Q000639:trends; D008875:Middle Aged; D058991:Patient Protection and Affordable Care Act / Q000191:economics* / Q000592:standards; D010359:Patient Readmission / Q000191:economics* / Q000331:legislation & jurisprudence / Q000639:trends; D012044:Regression Analysis; D012051:Reimbursement Mechanisms / Q000191:economics / Q000331:legislation & jurisprudence / Q000639:trends; D012959:Socioeconomic Factors; D014481:United States; D055815:Young Adult