title: Overprescribing of lipid lowering agents.
abstract: BACKGROUND
  Undertreatment of hyperlipidemia has received considerable attention. However, little is known about trends in overprescribing of lipid lowering agents. We examined these trends and their associations with physician, practice, and organisational factors.
  
  
  METHODS
  2034 physicians were surveyed twice: baseline (1996-7) and follow up (1998-9). On each occasion they were asked: "For what percentage of 50 year old men without other cardiac risk factors would you recommend an oral agent for total cholesterol of 240, LDL 150, and HDL 50 after 6 months on a low cholesterol diet?" During the survey period the National Cholesterol Education Program guidelines did not recommend prescribing for these patients. Binomial and multinomial logistic regressions assessed baseline overprescribing and longitudinal changes in overprescribing, accounting for complex sampling.
  
  
  RESULTS
  39% of physicians recommended prescribing at baseline (round 1), increasing at follow up (round 2) to 51% (p < 0.001). Physicians who were more likely to overprescribe at baseline were less likely to be board certified (odds ratio (OR) 0.49, 95% confidence interval (CI) 0.38 to 0.63; p < 0.001), were in solo or two-physician practices (OR 1.88, 95% CI 1.46 to 2.41; p < 0.001), had more revenue from Medicare (OR 1.10, 95% CI 1.03 to 1.17; p = 0.004) or Medicaid (OR 1.09, 95% CI 1.01 to 1.18; p = 0.03), or were family physicians (OR 1.87, 95% CI 1.35 to 2.58; p < 0.001). Physicians with large increases in overprescibing were more likely than those with small increases in overprescribing to be international medical graduates (OR 2.09, 95% CI 1.20 to 3.64; p = 0.011) and to spend more hours in patient care (OR 1.14, 95% CI 1.03 to 1.26; p = 0.016).
  
  
  CONCLUSIONS
  Overprescribing of lipid lowering agents is commonplace and increased. At baseline and longitudinally, overprescribing was primarily associated with physician and practice characteristics and not with organisational factors.
authors.affiliation: Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, 505 WARF Bldg, 610 Walnut St, Madison, WI 53726-2397, USA. maureensmith@wisc.edu
authors.forename: M A
authors.initials: MA
authors.lastname: Smith
authors.forename: E D
authors.initials: ED
authors.lastname: Cox
authors.forename: J M
authors.initials: JM
authors.lastname: Bartell
mesh_terms: D008076:Cholesterol, HDL / Q000097:blood / Q000187:drug effects; D008078:Cholesterol, LDL / Q000097:blood / Q000187:drug effects; D018752:Diet, Fat-Restricted; D011307:Drug Prescriptions; D017723:Drug Utilization Review; D004501:Education, Medical; D019538:Health Care Surveys; D006300:Health Services Misuse / Q000706:statistics & numerical data*; D006801:Humans; D006949:Hyperlipidemias / Q000188:drug therapy; D000960:Hypolipidemic Agents / Q000627:therapeutic use*; D008297:Male; D008511:Medicine / Q000145:classification / Q000706:statistics & numerical data*; D008875:Middle Aged; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D011331:Private Practice / Q000145:classification / Q000706:statistics & numerical data; D012044:Regression Analysis; D013038:Specialization; D011795:Surveys and Questionnaires; D014481:United States
chemical_list: D008076:Cholesterol, HDL; D008078:Cholesterol, LDL; D000960:Hypolipidemic Agents