title: Predictive power of a risk-assessment questionnaire across different disease states: results in an elderly managed care enrolled population.
abstract: OBJECTIVE
  To examine the predictive power of self-reported assessment questionnaire data to explain changes in healthcare service utilization and expenditures of a population of Medicare health maintenance organization enrollees during a 2-year period.
  
  
  METHODS
  A prospective cohort study with a 2-year postenrollment follow-up period. Multiple robust regression analyses were conducted to examine associations among self-reported health status variables obtained from responses to the questionnaire.
  
  
  METHODS
  Participants were administered a voluntary comprehensive questionnaire at enrollment that collected self-reported information on morbidity, health status, perceptions of health, and healthcare service utilization during the preenrollment year. Questionnaire responses were combined with actual 2-year postenrollment claims data. For the complete follow-up period, 4128 patients were available.
  
  
  RESULTS
  Participants with such chronic conditions as depression and diabetes were likelier than the average enrollee to have higher healthcare service utilization. Self-reported health status predictors examined in this study explained a larger percentage of the variance (as much as 20%) in such chronic conditions as cancer and depression. Despite evidence of underreporting of preenrollment healthcare service utilization, these variables were highly predictive of actual postenrollment utilization patterns.
  
  
  CONCLUSIONS
  Self-reported health status information collected at baseline is as predictive of postenrollment risk as are currently used traditional approaches that require archival healthcare service utilization data. In addition, this approach is sensitive to changes in healthcare service utilization across differing morbidity states in older adults.
authors.affiliation: Health Services Research Center, Department of Public Health Sciences, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA. rbalkris@wfubmc.edu
authors.forename: R
authors.initials: R
authors.lastname: Balkrishnan
authors.forename: R T
authors.initials: RT
authors.lastname: Anderson
mesh_terms: D000203:Activities of Daily Living / Q000145:classification; D000368:Aged; D015331:Cohort Studies; D004194:Disease / Q000145:classification; D005260:Female; D006279:Health Maintenance Organizations / Q000706:statistics & numerical data*; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data; D006305:Health Status Indicators; D006801:Humans; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data*; D011446:Prospective Studies; D012044:Regression Analysis; D018570:Risk Assessment / Q000379:methods*; D011795:Surveys and Questionnaires; D014481:United States / Q000453:epidemiology