title: Predictors of Gaps in Patient Safety and Quality in U.S. Hospitals.
abstract: OBJECTIVE
  To explore predictors of gaps between observed and best possible Hospital Compare scores in U.S. hospitals.
  
  
  METHODS
  American Hospital Association Annual Survey; Area Resource Files; Centers for Medicare and Medicaid Services Medicare Provider and Analysis Review; and Hospital Compare data.
  
  
  METHODS
  Using Stochastic Frontier Analysis and secondary cross-sectional data, gaps between the best possible and actual scores of Hospital Compare quality measures were estimated. Poisson regressions were used to ascertain financial, organizational, and market predictors of those gaps.
  
  
  METHODS
  Data were cleaned and matched based on hospital Medicare IDs. All U.S. hospitals that matched on analysis variables in 2007 were in the study (1,823-2,747, depending upon gap variable).
  
  
  RESULTS
  Most hospitals have a greater than 10 percent gap in quality indicators. Payer mix, registered nurse staffing, size, case mix index, accreditation, being a teaching hospital, market competition, urban location, and region were strong predictors of gaps, although the direction of the association with gaps was not uniform across outcomes.
  
  
  CONCLUSIONS
  A significant percentage of hospitals have gaps between their best possible and observed quality scores. It may be better to use gap scores than observed scores in payments systems. More SFA research is needed to know how to lower gaps through changes in hospital and market characteristics.
authors.affiliation: Health Services Administration Program, Department of Health Management & Informatics, College of Health and Public Affairs, University of Central Florida, Orlando, FL.
authors.forename: Lynn
authors.initials: L
authors.lastname: Unruh
authors.affiliation: Department of Economics, College of Business Administration, University of Central Florida, Orlando, FL.
authors.forename: Richard
authors.initials: R
authors.lastname: Hofler
mesh_terms: D000068:Accreditation; D003430:Cross-Sectional Studies; D003953:Diagnosis-Related Groups; D006302:Health Services Research; D006784:Hospitals, Teaching; D006801:Humans; D006278:Medicare / Q000706:statistics & numerical data; D009741:Nursing Staff, Hospital / Q000706:statistics & numerical data*; D061214:Patient Safety; D019984:Quality Indicators, Health Care / Q000706:statistics & numerical data*; D011795:Surveys and Questionnaires; D014481:United States; D014505:Urban Population
keywords: Stochastic Frontier Analysis; predictors of gaps in hospital quality