title: Do well-publicized risk-adjusted outcomes reports affect hospital volume?
abstract: BACKGROUND
  Report cards on hospital performance are common but have uncertain impact.
  
  
  OBJECTIVE
  The objective of this study was to determine whether hospitals recognized as performance outliers experience volume changes after publication of a report card. Secondary objectives were to test whether favorable outliers attract more patients with related conditions, or from outside their catchment areas; and whether disadvantaged groups are less responsive to report cards.
  
  
  METHODS
  We used a time-series analysis using linear and autoregressive models.
  
  
  METHODS
  We studied patients admitted to nonfederal hospitals designated as outliers in reports on coronary bypass surgery (CABG) mortality in New York, acute myocardial infarction (AMI) mortality in California, and postdiskectomy complications in California.
  
  
  METHODS
  We studied observed versus expected hospital volume for topic and related conditions and procedures, by month/quarter after a report card, with and without stratification by age, race/ethnicity, insurance, and catchment area. Potential confounders included statewide prevalence, prereport hospital volume and market share, and unrelated volume.
  
  
  RESULTS
  In California, low-mortality and high-mortality outliers did not experience changes in AMI volume after adjusting for autocorrelation. Low-complication outliers for lumbar diskectomy experienced slightly increased volume in autoregressive models. No other cohorts demonstrated consistent trends. In New York, low-mortality outliers experienced significantly increased CABG volume in the first month after publication, whereas high-mortality outliers experienced decreased volume in the second month. The strongest effects were among white patients and those with HMO coverage in California, and among white or other patients and those with Medicare in New York.
  
  
  CONCLUSIONS
  Volume effects were modest, transient, and largely limited to white Medicare patients in New York.
authors.affiliation: Division of General Medicine, Department of Internal Medicine, and the Center for Health Services Research in Primary Care, University of California, Davis School of Medicine, Sacramento, 95817, USA. psromano@ucdavis.edu
authors.forename: Patrick S
authors.initials: PS
authors.lastname: Romano
authors.forename: Hong
authors.initials: H
authors.lastname: Zhou
mesh_terms: D000368:Aged; D002140:California / Q000453:epidemiology; D001026:Coronary Artery Bypass / Q000401:mortality; D017586:Diskectomy / Q000009:adverse effects; D006279:Health Maintenance Organizations / Q000706:statistics & numerical data; D006302:Health Services Research; D017052:Hospital Mortality; D006761:Hospitals / Q000706:statistics & numerical data; D006801:Humans; D033181:Information Dissemination; D019458:Insurance Coverage / Q000706:statistics & numerical data; D016018:Least-Squares Analysis; D016014:Linear Models; D008137:Longitudinal Studies; D006278:Medicare / Q000706:statistics & numerical data; D008875:Middle Aged; D009203:Myocardial Infarction / Q000401:mortality; D009518:New York / Q000453:epidemiology; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D010342:Patient Acceptance of Health Care / Q000523:psychology / Q000706:statistics & numerical data; D010343:Patient Admission / Q000706:statistics & numerical data; D011237:Predictive Value of Tests; D011787:Quality of Health Care / Q000706:statistics & numerical data*; D012044:Regression Analysis; D020379:Risk Adjustment / Q000706:statistics & numerical data*