title: Medical expenditures associated with major depressive disorder among privately insured working-age adults with diagnosed diabetes in the United States, 2008.
abstract: OBJECTIVE
  We aimed at estimating excess medical expenditures associated with major depressive disorder (MDD) among working-age adults diagnosed with diabetes, disaggregated by treatment mode: insulin-treated diabetes (ITDM) or non-insulin-treated diabetes (NITDM).
  
  
  METHODS
  We analyzed data for over 500,000 individuals with diagnosed diabetes from the 2008 U.S. MarketScan claims database. We grouped diabetic patients first by treatment mode (ITDM or NITDM), then by MDD status (with or without MDD), and finally by whether those with MDD used antidepressant medication. We estimated annual mean excess outpatient, inpatient, prescription drug, and total expenditures using regression models, controlling for demographics, types of health coverage, and comorbidities.
  
  
  RESULTS
  Among persons having ITDM, the estimated annual total mean expenditure for those with no MDD (the comparison group) was $19,625. For those with MDD, the expenditures were $12,406 (63%) larger if using antidepressant medication and $7322 (37%) larger if not using antidepressant medication. Among persons having NITDM, the corresponding estimated expenditure for the comparison group was $10,746, the excess expenditures were $10,432 (97%) larger if using antidepressant medication and $5579 (52%) larger if not using antidepressant medication, respectively. Inpatient excess expenditures were the largest of total excess expenditure for those with ITDM and MDD treated with antidepressant medication; for all others with diabetes and MDD, outpatient expenditures were the largest excess expenditure.
  
  
  CONCLUSIONS
  Among working-age adults with diabetes, MDD was associated with substantial excess medical expenditures. Implementing the effective interventions demonstrated in clinical trials and treatment guidelines recommended by professional organizations might reduce the economic burden of MDD in this population.
authors.affiliation: Division of Diabetes Translation, US Centers for Disease Control and Prevention, Atlanta, GA 30341, United States. gqm2@cdc.gov
authors.forename: Sundar S
authors.initials: SS
authors.lastname: Shrestha
authors.forename: Ping
authors.initials: P
authors.lastname: Zhang
authors.forename: Rui
authors.initials: R
authors.lastname: Li
authors.forename: Theodore J
authors.initials: TJ
authors.lastname: Thompson
authors.forename: Daniel P
authors.initials: DP
authors.lastname: Chapman
authors.forename: Lawrence
authors.initials: L
authors.lastname: Barker
mesh_terms: D017677:Age Distribution; D000928:Antidepressive Agents / Q000191:economics / Q000627:therapeutic use*; D015897:Comorbidity; D017281:Cost of Illness; D003430:Cross-Sectional Studies; D003865:Major Depressive Disorder / Q000188:drug therapy / Q000191:economics / Q000453:epidemiology*; D003924:Diabetes Mellitus, Type 2 / Q000188:drug therapy / Q000191:economics / Q000453:epidemiology*; D005260:Female; D005382:Financing, Personal / Q000706:statistics & numerical data; D017048:Health Care Costs / Q000706:statistics & numerical data*; D005102:Health Expenditures / Q000706:statistics & numerical data; D006760:Hospitalization; D006801:Humans; D007004:Hypoglycemic Agents / Q000191:economics / Q000627:therapeutic use*; D007328:Insulin / Q000191:economics / Q000627:therapeutic use*; D008297:Male; D008875:Middle Aged; D055553:Prescription Drugs; D017678:Sex Distribution; D013997:Time Factors; D014481:United States / Q000453:epidemiology
chemical_list: D000928:Antidepressive Agents; D007004:Hypoglycemic Agents; D007328:Insulin; D055553:Prescription Drugs