title: Hospital characteristics and quality of care.
abstract: OBJECTIVE
  To compare quality of care measured by explicit criteria, implicit review, and sickness-adjusted outcomes at different types of hospitals.
  
  
  METHODS
  Further analysis of data retrospectively abstracted from medical records to evaluate the effects of prospective payment on quality of care for hospitalized Medicare patients.
  
  
  METHODS
  Hospitals in five states were sampled to represent the national Medicare admissions along many dimensions.
  
  
  METHODS
  A total of 14,008 elderly patients with one of the following five diseases: congestive heart failure, acute myocardial infarction, pneumonia, stroke, or hip fracture. These patients were randomly sampled from those with these diseases in 297 hospitals in two time periods, 1981 to 1982 and 1985 to 1986.
  
  
  METHODS
  Explicit criteria, implicit review, and mortality within 30 days of admission adjusted for sickness at admission.
  
  
  RESULTS
  Quality of care ratings for hospital types are similar using explicit criteria, implicit review, and outcomes adjusted for sickness at admission. Quality differences between types of hospitals were large, with the lowest group estimated to have four percentage points higher mortality than major teaching hospitals in a cohort of patients with average mortality of 16%. Quality varies from state to state, but teaching, larger, and more urban hospitals have better quality in general than nonteaching, small, and rural hospitals. Hospital quality persists over time, but small nonteaching hospitals narrowed the gap with better quality hospitals between 1981 and 1986.
  
  
  CONCLUSIONS
  The different measures led to consistent and plausible relationships between quality and hospital characteristics. Thus, valid information about hospital quality can be obtained. We need to develop ways to use such information to improve care.
authors.affiliation: Health Program of RAND, Santa Monica, CA.
authors.forename: E B
authors.initials: EB
authors.lastname: Keeler
authors.forename: L V
authors.initials: LV
authors.lastname: Rubenstein
authors.forename: K L
authors.initials: KL
authors.lastname: Kahn
authors.forename: D
authors.initials: D
authors.lastname: Draper
authors.forename: E R
authors.initials: ER
authors.lastname: Harrison
authors.forename: M J
authors.initials: MJ
authors.lastname: McGinty
authors.forename: W H
authors.initials: WH
authors.lastname: Rogers
authors.forename: R H
authors.initials: RH
authors.lastname: Brook
mesh_terms: D000465:Algorithms; D017052:Hospital Mortality; D006761:Hospitals / Q000592:standards* / Q000706:statistics & numerical data; D006780:Hospitals, Rural / Q000592:standards / Q000706:statistics & numerical data; D006784:Hospitals, Teaching / Q000592:standards / Q000706:statistics & numerical data; D006786:Hospitals, Urban / Q000592:standards / Q000706:statistics & numerical data; D008484:Medicaid; D010043:Outcome and Process Assessment, Health Care / Q000191:economics / Q000706:statistics & numerical data; D010343:Patient Admission / Q000706:statistics & numerical data; D011445:Prospective Payment System; D014481:United States / Q000453:epidemiology