Abstract
Objective: To understand factors driving the economic burden of major depressive disorder (MDD) patients with different treatment regimens, by evaluating the relationship between medical profiles and treatment costs.
Methods: Claims data for US privately insured employees (1999–2004) were analysed. Analysis included adult employees with ≥1 diagnosis of MDD and ≥1 prescription for specific antidepressants following a 6-month washout period. Patients were first classified into treatment pattern groups (switchers/discontinuers/maintainers/augmenters), then stratified into mutually exclusive treatment groups — nonstable, stable and intermediate — based on evidence of stability in treatment therapy. Rates of mental and physical co-morbidities, injuries/accidents, substance abuse and urgent care use were analysed across treatment pattern groups. Direct (medical/drug) costs were calculated per patient per year and disaggregated into depression- and non-depression-related components. A two-part multivariate model controlled for baseline characteristics. Costs were also estimated for patients withMDD only, patients with MDD and generalized anxiety disorder (GAD), and patients with MDD and any type of anxiety.
Results: Annual per patient adjusted costs (year 2005 values) were significantly lower among stable patients ($US6215) than among intermediate ($US7317) and nonstable patients ($US9948; p < 0.001). Stable patients also had lower depression- and non-depression-related costs. Patients with MDD and comorbid GAD or any type of anxiety had significantly higher costs than MDD-only patients.
Conclusions: Nonstability of treatment is associated with higher comorbidity rates, more urgent care use and higher total, depression- and non-depressionrelated direct costs. The stable group represents continuity of care and is associated with significant cost savings. Co-morbidities are associated with increased costs.
Similar content being viewed by others
Notes
Antidepressants identified as claims for bupropion, monoamine oxidase inhibitors, noradrenaline re-uptake inhibitors, noradenergic and specific serotonergic antidepressants, SSRIs, SNRIs, tetracyclic or tricyclic antidepressants.
References
Greenberg PE, Kessler RC, Birnbaum HG, et al. The economic burden of depression in the United States: how did it change between 1990 and 2000? J Clin Psychiatry 2003; 64 (12): 1465–75
Kessler RC, Berglund P, Demler O, et al., National Comorbidity Survey Replication. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA 2003 Jun 18; 289 (23); 3095–105
Luppa M, Heinrich S, Angermeyer MC, et al. Cost-of-illness studies of depression: a systematic review. J Affect Disord 2007 Feb; 98 (1–2): 29–43. Epub 2006 Sep 6
Berto P, D’Ilario D, Ruffo P, et al. Depression: cost-of-illness studies in the international literature, a review. J Ment Health Policy Econ 2000 Mar 1; 3 (1): 3–10
Greenberg PE, Stiglin LE, Finkelstein SN, et al. The economic burden of depression in 1990. J Clin Psychiatry 1993; 54 (11): 405–18
Doshi JA, Cen L, Polsky D. Depression and retirement in late middle-aged U.S. workers. Health Serv Res 2008 Apr; 43 (2): 693–713
Crown WH, Finkelstein S, Berndt ER, et al. The impact of treatment-resistant depression on health care utilization and costs. J Clin Psychiatry 2002 Nov; 63 (11): 963–71
Corey-Lisle PK, Birnbaum H, Greenberg PE, et al. Identification of a claims data “signature” and economic consequences for treatment-resistant depression. J Clin Psychiatry 2002 Aug; 63 (8): 717–26
Rush AJ, Trivedi MH, Wisniewski SR, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry 2006 Nov 1; 163 (11): 1905–17
Greenberg PE, Corey-Lisle PK, Birnbaum H, et al. Economic implications of treatment-resistant depression among employees. Pharmacoeconomics 2004; 22 (6): 363–73
Russell JM, Hawkins K, Ozminkowski RJ, et al. The cost consequences of treatment-resistant depression. J Clin Psychiatry 2004; 65: 341–7
Pearson SD, Katzelnick DJ, Simon GE, et al. Depression among high utilizers of medical care. J Gen Intern Med 1999; 14: 461–8
Thompson D, Buesching D, Gregor KJ, et al. Patterns of antidepressant use and their relation to costs of care. Am J Manag Care 1996; 2: 1239–46
Cantrell CR, Eaddy MT, Shah MB, et al. Methods for evaluating patient adherence to antidepressant therapy: a real-world comparison of adherence and economic outcomes. Med Care 2006 Apr; 44 (4): 300–3
Antidepressant medication management. The state of health care quality. Washington (DC): National Committee for Quality Assurance, 2006
Burton WN, Chen CY, Conti DJ, et al. The association of antidepressant medication adherence with employee disability absences. Am J Manag Care 2007; 13 (2): 105–12
Akincigil A, Bowblis JR, Levin C, et al. Adherence to antidepressant treatment among privately insured patients diagnosed with depression. Med Care 2007 Apr; 45 (4): 363–9
Robinson RL, Long SR, Chang S, et al. Higher costs and therapeutic factors associated with adherence to NCQA HEDIS antidepressant medication management measures: analysis of administrative claims. J Manag Care Pharm 2006 Jan-Feb; 12 (1): 43–54
Birnbaum HG, Greenberg PE, Tang J, et al. Antidepressant treatment patterns and costs among U.S. employees. J Med Econ 2009; 12 (1): 36–45
Sood N, Treglia M, Obenchain RL, et al. Determinants of antidepressant treatment outcome. Am J Manag Care 2000 Dec; 6 (12): 1327–36
Gilmer WS, Trivedi MH, Rush AJ, et al. Factors associated with chronic depressive episodes: a preliminary report from the STAR-D project. Acta Psychiatr Scand 2005 Dec; 112 (6): 425–33
Simon GE, Revicki D, Heiligenstein J, et al. Recovery from depression, work productivity, and health care costs among primary care patients. Gen Hosp Psychiatry 2000; 22: 153–62
Simon GE, Chisholm D, Treglia M, et al., the LIDO Group. Course of depression, health services costs, and work productivity in an international primary care study. Gen Hosp Psychiatry 2002; 24: 328–35
Sobocki P, Ekman M, Agren H, et al. The mission is remission: health economic consequences of achieving full remission with antidepressant treatment for depression. Int J Clin Pract 2006; 60: 791–8
Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992 Jun; 45 (6): 613–9
Ballenger JC. Clinical guidelines for establishing remission in patients with depression and anxiety. J Clin Psychiatry 1999; 60 Suppl. 22: 29–34
Wedderburn RWM. Quasi-likelihood functions, generalized linear models, and the Gauss-Newton method. Biometrika 1974; 61: 439–47
Manning WG, Mullahy J. Estimating log models: to transform or not to transform? J Health Econ 2001; 20: 461–94
Manning WG. The logged dependent variable, heteroscedasticity, and the retransformation problem. J Health Econ 1998; 17: 283–95
Trivedi MH, Rush AJ, Wisniewski SR, et al., STAR*D Study Team. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry 2006; 163: 28–40
Rost K, Pyne JM, Dickinson LM, et al. Cost-effectiveness of enhancing primary care depression management on an ongoing basis. Ann Fam Med 2005 Jan-Feb; 3 (1): 7–14
Acknowledgements
This research was supported by funding from sanofi-aventis to Analysis Group, Inc., and was presented at the 2007 American Psychiatric Association Annual Meeting, San Diego, CA, USA 19–24 May 2007. Camille Reygrobellet is an employee of sanofi-aventis. Howard Birnbaum, Rym Ben-Hamadi, Paul Greenberg, Matthew Hsieh and Jackson Tang are employees of Analysis Group, Inc.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Birnbaum, H.G., Ben-Hamadi, R., Greenberg, P.E. et al. Determinants of Direct Cost Differences among US Employees with Major Depressive Disorders Using Antidepressants. Pharmacoeconomics 27, 507–517 (2009). https://doi.org/10.2165/00019053-200927060-00006
Published:
Issue Date:
DOI: https://doi.org/10.2165/00019053-200927060-00006