title: Can medical school-affiliated hospitals compete with private hospitals in the age of managed care? An 11-state, population-based analysis of 351,201 patients undergoing cholecystectomy.
abstract: BACKGROUND
  The purpose of this study was to use an 11-state, population-based hospital discharge database to assess the charges for care of patients undergoing cholecystectomy at both medical school affiliated hospitals (MSAHs) and private hospitals (nonMSAHs). It was our hypothesis that MSAHs could indeed provide efficient, competitively priced patient care.
  
  
  METHODS
  Data were obtained from the Healthcare Cost Utilization Project of the Agency for Health Care and Policy Research. The database tracks information on all hospitalized patients from 11 states for the years 1988-1992.
  
  
  RESULTS
  Represented in the study were 849 nonMSAHs (82%) and 191 MSAHs (18%). During the 5 years of the study, 351,201 patients underwent cholecystectomy. The mean charges and the lengths of stay were similar in the two diagnosis related groups (DRGs) studied (197,198). The analysis demonstrated that during this same period, MSAHs led in both the adoption of laparoscopic cholecystectomy and decreased use of intraoperative cholangiography.
  
  
  CONCLUSIONS
  Others have reported that MSAHs cannot compete with nonMSAHs in providing competitively priced care. The present study shows that for cholecystectomy, charges and length of hospital stay are comparable in MSAHs and nonMSAHs. This study supports the hypothesis that the leadership provided at United States medical schools may also extend to the area of cost-efficient care and hints at further areas of improvement.
authors.affiliation: University of North Carolina School of Medicine, Chapel Hill 27599-7210, USA.
authors.forename: R
authors.initials: R
authors.lastname: Rutledge
mesh_terms: D002758:Cholangiography / Q000706:statistics & numerical data; D002763:Cholecystectomy / Q000191:economics*; D017081:Cholecystectomy, Laparoscopic / Q000191:economics / Q000706:statistics & numerical data; D015986:Confounding Factors, Epidemiologic; D003362:Cost-Benefit Analysis; D003953:Diagnosis-Related Groups / Q000191:economics; D005260:Female; D017722:Hospital Charges; D016304:Hospitals, Private / Q000191:economics*; D006784:Hospitals, Teaching / Q000191:economics*; D006801:Humans; D007902:Length of Stay; D008297:Male; D008329:Managed Care Programs / Q000191:economics*; D008875:Middle Aged; D016343:Monitoring, Intraoperative / Q000706:statistics & numerical data; D017678:Sex Distribution; D014481:United States