title: The impact of unrecognized bipolar disorders among patients treated for depression with antidepressants in the fee-for-services California Medicaid (Medi-Cal) program: a 6-year retrospective analysis.
abstract: BACKGROUND
  The cost of unrecognized bipolar disorders over time is unknown.
  
  
  METHODS
  Ten years of data from the California Medicaid program were used to identify depressed patients initiating new episodes of antidepressant therapy and with 6+ years of post-treatment data. Recognized bipolar (RBP) patients received a BP diagnosis or used mood stabilizers in the pre-index period. Unrecognized bipolar (UBP) patients received an initial BP diagnosis or used a mood stabilizer in the post-index period. Depression-only (MDD) patients had no BP diagnosis or mood stabilizer use. Three analyses were conducted: (1) regression models of cost per year, (2) a regression model of aggregate cost over 6 years and (3) a time trend analysis of the costs for UBP patients.
  
  
  RESULTS
  14,809 patients were identified: RBP 14.5%, UBP 28.2% and MDD 57.3%. The growth in costs per month for UBP patients over 6 years (171%) far exceeds the growth for RBP and MDD patients (82% and 95%, respectively). RBP and MDD patients cost 2316 dollars and 1681 dollars less per year in the 6th year relative to UBP patients (p<0.0001 for both estimates). The cost per month increased by 91 dollars for each month of delayed diagnosis (p=0.011). Costs for UBP patients increased by 10 dollars per month prior to their initial BP diagnosis (p<0.001) and by -1.01 dollars thereafter (p=0.006 for the change in slope).
  
  
  CONCLUSIONS
  Classification of patients based on diagnosis or mood stabilizer use using paid claims data is inexact.
  
  
  CONCLUSIONS
  Early diagnosis of bipolar disorders may significantly reduce health care cost.
authors.affiliation: Department of Pharmaceutical Economics and Policy, School of Pharmacy, University of Southern California, Los Angeles, CA 90089-9004, USA. jmccombs@usc.edu
authors.forename: Jeffrey S
authors.initials: JS
authors.lastname: McCombs
authors.forename: Jeonghoon
authors.initials: J
authors.lastname: Ahn
authors.forename: Thomas
authors.initials: T
authors.lastname: Tencer
authors.forename: Lizheng
authors.initials: L
authors.lastname: Shi
mesh_terms: D000328:Adult; D000368:Aged; D000927:Anticonvulsants / Q000191:economics* / Q000627:therapeutic use; D000928:Antidepressive Agents / Q000191:economics* / Q000627:therapeutic use; D018692:Antimanic Agents / Q000191:economics* / Q000627:therapeutic use; D001714:Bipolar Disorder / Q000175:diagnosis* / Q000188:drug therapy / Q000191:economics*; D002140:California; D003365:Costs and Cost Analysis; D003865:Major Depressive Disorder / Q000175:diagnosis* / Q000188:drug therapy / Q000191:economics*; D003951:Diagnostic Errors / Q000191:economics*; D016527:Drug Costs / Q000706:statistics & numerical data; D042241:Early Diagnosis; D018588:Fee-for-Service Plans / Q000191:economics*; D005260:Female; D006760:Hospitalization / Q000191:economics; D006801:Humans; D007345:Insurance Claim Review; D008297:Male; D008484:Medicaid / Q000191:economics*; D008875:Middle Aged; D012044:Regression Analysis; D013221:State Health Plans / Q000191:economics*; D014481:United States
chemical_list: D000927:Anticonvulsants; D000928:Antidepressive Agents; D018692:Antimanic Agents