title: Measuring use and cost of care for patients with mood disorders: the utilization and cost inventory.
abstract: BACKGROUND
  Researchers conducting cost-outcome studies must account for all materially relevant care that subjects receive from their care providers. However, access to provider records is often limited. This article describes and tests the Utilization and Cost Inventory (UAC-I), a structured patient interview designed to measure costs of care when access to provider records is limited.
  
  
  METHODS
  UAC-I was tested on 212 consenting adult veterans with mood disorder attending a VA medical center. Counts (inpatient days and outpatient encounters) and costs (dollars) computed from survey responses were compared with estimates from medical records and an alternative structured questionnaire.
  
  
  RESULTS
  The agreement between inpatient costs computed from provider records and from UAC-I responses, assessed using the intraclass correlation coefficient (ICC), was 0.66, 95% confidence interval (CI), 0.30-0.84; the bias was -3.7%, 95% CI, -48 to 41. The ICC for the service data (inpatient days) was 0.97, 95% CI, 0.95-0.99; the bias was <1%, 95% CI, -14 to 15. The ICC for outpatient costs computed from provider records and from UAC-I responses was 0.53 95% CI, 0.38-0.65; the bias was <1%, 95% CI, -27 to 27. The ICC for outpatient encounters was 0.74, 95% CI, 0.65-0.80; the bias was <1%, 95% CI, -16 to 18.
  
  
  CONCLUSIONS
  These results indicate that it may be feasible for cost-outcome studies to compare patient groups for inpatient and outpatient costs computed from patient self-reports.
authors.affiliation: Department of Clinical Sciences and Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA. Michael.Kashner@va.gov
authors.forename: T Michael
authors.initials: TM
authors.lastname: Kashner
authors.forename: Michael D
authors.initials: MD
authors.lastname: Stensland
authors.forename: Lisa
authors.initials: L
authors.lastname: Lind
authors.forename: Annie
authors.initials: A
authors.lastname: Wicker
authors.forename: A John
authors.initials: AJ
authors.lastname: Rush
authors.forename: Richard M
authors.initials: RM
authors.lastname: Golden
authors.forename: Steven S
authors.initials: SS
authors.lastname: Henley
mesh_terms: D000328:Adult; D000553:Ambulatory Care / Q000191:economics / Q000706:statistics & numerical data; D003362:Cost-Benefit Analysis; D003695:Delivery of Health Care / Q000191:economics / Q000706:statistics & numerical data; D005240:Feasibility Studies; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data*; D006302:Health Services Research; D006306:Health Surveys; D006801:Humans; D007902:Length of Stay / Q000191:economics / Q000706:statistics & numerical data; D008297:Male; D008605:Mental Health Services / Q000191:economics* / Q000706:statistics & numerical data*; D008875:Middle Aged; D017059:Models, Econometric; D019964:Mood Disorders / Q000191:economics* / Q000453:epidemiology / Q000523:psychology; D017063:Outcome Assessment, Health Care; D010343:Patient Admission / Q000191:economics / Q000706:statistics & numerical data; D010348:Patient Care Team / Q000191:economics / Q000706:statistics & numerical data; D011795:Surveys and Questionnaires; D014481:United States; D014600:Utilization Review / Q000706:statistics & numerical data; D014728:Veterans / Q000523:psychology* / Q000706:statistics & numerical data