title: The effects of medical group practice and physician payment methods on costs of care.
abstract: OBJECTIVE
  To assess the effects of payment methods on the costs of care in medical group practices.
  
  
  METHODS
  Eighty-six clinics providing services for a Blue Cross managed care program during 1995. The clinics were analyzed to determine the relationship between payment methods and cost of care. Cost and patient data were obtained from Blue Cross records, and medical group practice clinic data were obtained by a survey of those organizations.
  
  
  METHODS
  The effects of clinic and physician payment methods on per member per year (PMPY) adjusted patient costs are evaluated using a two-stage regression model. Patient costs are adjusted for differences in payment schedules; patient age, gender, and ACG; clinic organizational variables are included as explanatory variables.
  
  
  METHODS
  Patient cost data were extracted from Blue Cross claims files, and patient and physician data from their enrollee and provider data banks. Medical group practice data were obtained by a mailed survey with telephone follow-up.
  
  
  RESULTS
  Capitation payment is correlated with lower patient care costs. When combined with fee-for-service with withhold provisions, this effect is smaller indicating that these two clinic payment methods are not interchangeable. Clinics with more physician compensation based on measures of resource use or based on some share of the net revenue of the clinic have lower patient care costs than those with more compensation related to productivity or based on salary. Salary compensation is strongly associated with higher costs. The use of physician profiles and clinical guidelines is associated with lower costs, but referral management systems have no such effect. The lower cost clinics are the smaller, multispecialty clinics.
  
  
  CONCLUSIONS
  This study indicates that payment methods at both the medical group practice and physician levels influence the cost of care. However, the methods by which that influence is manifest is not clear. Although the organizational structure of clinics and their use of managed care programs appear to play a role, this influence is less than expected.
authors.affiliation: Division of Health Services Research and Policy, School of Public Health, University of Minnesota, Minneapolis 55455, USA.
authors.forename: J E
authors.initials: JE
authors.lastname: Kralewski
authors.forename: E C
authors.initials: EC
authors.lastname: Rich
authors.forename: R
authors.initials: R
authors.lastname: Feldman
authors.forename: B E
authors.initials: BE
authors.lastname: Dowd
authors.forename: T
authors.initials: T
authors.lastname: Bernhardt
authors.forename: C
authors.initials: C
authors.lastname: Johnson
authors.forename: W
authors.initials: W
authors.lastname: Gold
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D054598:Blue Cross Blue Shield Insurance Plans / Q000191:economics; D002204:Capitation Fee; D002648:Child; D002675:Child, Preschool; D018588:Fee-for-Service Plans; D005260:Female; D006123:Group Practice / Q000191:economics* / Q000706:statistics & numerical data; D017048:Health Care Costs / Q000706:statistics & numerical data*; D006279:Health Maintenance Organizations / Q000191:economics* / Q000706:statistics & numerical data; D006302:Health Services Research / Q000379:methods; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D008910:Minnesota; D012044:Regression Analysis; D012051:Reimbursement Mechanisms; D020414:Risk Sharing, Financial / Q000191:economics* / Q000706:statistics & numerical data; D012456:Salaries and Fringe Benefits