title: Relative impact of patient and clinic factors on adherence to primary care preventive service guidelines: an exploratory study.
abstract: BACKGROUND
  Preventive care service use is commonly compared across health plans, clinics, or individual providers, yet little is known about the influence of the clinic versus patient factors on utilization of these services.
  
  
  OBJECTIVE
  To measure the relative influence of the facility (clinic) versus patient factors (demographic, behavioral and functional characteristics) on patients' utilization of mammography, Pap smears, cholesterol screening, and retinal exams for those with diabetes.
  
  
  METHODS
  Retrospective analysis, using administrative and patient survey data.
  
  
  METHODS
  Enrollees in 2 University-based clinics and a county hospital-based clinic serving a predominantly low-income population with limited access to health care. Eligibility for cervical cancer screening, screening mammography, cholesterol screening, or annual retinal exam (diabetes) was defined by age, sex, and diagnosis.
  
  
  METHODS
  Multivariate models, one using readily available administrative data, and another using detailed health status and behavior data gathered from a clinics-wide survey.
  
  
  RESULTS
  Unadjusted screening rates for three of four procedures were significantly and substantially lower at the county hospital based clinic than the two University-based clinics. After adjusting for patient characteristics, utilization of three screening services at the county hospital remained significantly below the University-based clinics (Odds Ratios [95% CI]: mammogram 0.15 [0.06-0.35]; Pap smear 0.32 [0.21-0.50]; cholesterol 0.19 [0.09-0.38]; diabetes retinal exam10.68 [0.93-3.01]). The models with detailed survey data performed only marginally better than the models using only administrative data.
  
  
  CONCLUSIONS
  Patient characteristics were much less important than the clinic for predicting whether patients received primary care preventive services. Our results suggest that case mix adjustment is unlikely to explain away discrepancies in performance between clinics or provider groups.
authors.affiliation: Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109-1024, USA. sramsey@fhcrc.org
authors.forename: S D
authors.initials: SD
authors.lastname: Ramsey
authors.forename: A D
authors.initials: AD
authors.lastname: Cheadle
authors.forename: W E
authors.initials: WE
authors.lastname: Neighbor
authors.forename: E
authors.initials: E
authors.lastname: Gore
authors.forename: P
authors.initials: P
authors.lastname: Temple
authors.forename: T
authors.initials: T
authors.lastname: Staiger
authors.forename: H I
authors.initials: HI
authors.lastname: Goldberg
mesh_terms: D000328:Adult; D002784:Cholesterol / Q000097:blood; D005128:Eye Diseases / Q000175:diagnosis; D005260:Female; D019983:Guideline Adherence / Q000706:statistics & numerical data*; D006766:Hospitals, County / Q000592:standards / Q000706:statistics & numerical data; D006785:Hospitals, University / Q000592:standards / Q000706:statistics & numerical data; D006801:Humans; D016013:Likelihood Functions; D016015:Logistic Models; D008297:Male; D008327:Mammography / Q000706:statistics & numerical data; D008403:Mass Screening / Q000706:statistics & numerical data; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D010044:Outpatient Clinics, Hospital / Q000592:standards / Q000706:statistics & numerical data*; D065006:Papanicolaou Test; D010342:Patient Acceptance of Health Care / Q000706:statistics & numerical data*; D017410:Practice Guidelines as Topic; D011314:Preventive Health Services / Q000592:standards / Q000706:statistics & numerical data*; D011320:Primary Health Care / Q000592:standards*; D014626:Vaginal Smears / Q000706:statistics & numerical data; D014861:Washington
chemical_list: D002784:Cholesterol