title: Predicting persistently high primary care use.
abstract: OBJECTIVE
  We wanted to identify risk factors for persistently high use of primary care.
  
  
  METHODS
  We analyzed outpatient office visits to practitioners in family medicine, general internal medicine, general pediatrics, and obstetrics for 1997-1999 among patients in a small Midwestern city covered by a fee-for-service insurance plan with no co-payments for physician visits and no requirement for referral to specialty care. Logistic regression was used to predict which patients with 10 or more primary care visits in 1997 would repeat high use in 1998 based on demographic and diagnostic categories (adjusted clinical groups [ACGs]). A confirmatory data set (high primary care use in 1998 persistent into 1999) was used to evaluate the model.
  
  
  RESULTS
  Two percent of the 54,074 patients had 10 or more primary care visits in 1997, and of these, almost 19% had 10 or more visits in the next year. Among adults, 4 ambulatory diagnosis groups (ADGs) were simultaneously positive predictors of repeated high primary care visits: unstable chronic medical conditions, see and reassure conditions, minor time-limited psychosocial conditions, and minor signs and symptoms. Meanwhile, pregnancy was negatively associated. The area under the receiver operating characteristic (ROC) curve was 0.794 for adults in the developmental data set and 0.752 in the confirmatory data set, indicating a moderately accurate assessment. A satisfactory model was not developed for pediatric patients.
  
  
  CONCLUSIONS
  Many persistently high primary care users appear to be overserviced but underserved, with underlying problems not addressed by a medical approach. Some may benefit from psychosocial support, whereas others may be good candidates for disease management interventions.
authors.affiliation: Division of Health Care Policy & Research, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN 55905, USA. naessens.james@mayo.edu
authors.forename: James M
authors.initials: JM
authors.lastname: Naessens
authors.forename: Macaran A
authors.initials: MA
authors.lastname: Baird
authors.forename: Holly K
authors.initials: HK
authors.lastname: Van Houten
authors.forename: David J
authors.initials: DJ
authors.lastname: Vanness
authors.forename: Claudia R
authors.initials: CR
authors.lastname: Campbell
mesh_terms: D000328:Adult; D002648:Child; D018588:Fee-for-Service Plans; D005260:Female; D005544:Forecasting; D006801:Humans; D016015:Logistic Models; D008297:Male; D011320:Primary Health Care / Q000706:statistics & numerical data* / Q000639:trends