title: Multiple measurement of serum lipids in the elderly.
abstract: BACKGROUND
  Although there is considerable interest in underutilization of lipid testing, little is known about the prevalence and factors associated with overtesting of serum lipids.
  
  
  METHODS
  We assessed the number of different days in which outpatient lipid testing was performed in a 5% national sample of patients with parts A and B Medicare in 2006. Covariates included patient characteristics (age, race, prior diagnosis of lipid disorder, and other indications for lipid testing), number of usual care physicians (UCP), type of UCP, total outpatient physician encounters, and health referral region (HRR) characteristics (average per-patient Medicare expenditures and percent of patients seeing multiple UCPs).
  
  
  RESULTS
  Among the 1,151,891 patients, 11.9% underwent 3 or more outpatient measurements of serum lipids. In multivariable analyses, the total number of UCPs providing care for the patient was associated with multiple lipid testing, independent of patient characteristics, indications for lipid testing, and total outpatient encounters. There was a strong association among HRRs between the rate of multiple lipid testing and average Medicare expenditures (r = 0.56). This was reduced after including the percentage of patients with more than 2 medical subspecialist UCPs in the HRR in a partial correlation (r = 0.31).
  
  
  CONCLUSIONS
  Multiple lipid testing is associated with the presence of multiple providers, independent of indications for testing, comorbidity, and total physician visits. Much of the association of multiple lipid testing with medical expenditures at the level of HRR appears to be explained by differences in exposure to multiple providers.
authors.affiliation: Department of Internal Medicine, University of Texas Medical Branch, Galveston, TX, USA. jsgoodwi@utmb.edu
authors.forename: James S
authors.initials: JS
authors.lastname: Goodwin
authors.forename: Adib
authors.initials: A
authors.lastname: Asrabadi
authors.forename: Bret
authors.initials: B
authors.lastname: Howrey
authors.forename: Sharon
authors.initials: S
authors.lastname: Giordano
authors.forename: Yong-Fang
authors.initials: YF
authors.lastname: Kuo
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000553:Ambulatory Care / Q000706:statistics & numerical data*; D001774:Blood Chemical Analysis / Q000706:statistics & numerical data*; D005260:Female; D019538:Health Care Surveys; D005102:Health Expenditures / Q000706:statistics & numerical data; D006300:Health Services Misuse / Q000706:statistics & numerical data*; D006801:Humans; D007344:Insurance Claim Reporting / Q000706:statistics & numerical data; D016018:Least-Squares Analysis; D008055:Lipids / Q000097:blood*; D016015:Logistic Models; D008297:Male; D016344:Medicare Part A / Q000706:statistics & numerical data; D016345:Medicare Part B / Q000706:statistics & numerical data; D015999:Multivariate Analysis; D018579:Patient Selection; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D014481:United States
chemical_list: D008055:Lipids