Burden of treatment-resistant depression in Medicare: A retrospective claims database analysis

Autoři: Dominic Pilon aff001;  Kruti Joshi aff002;  John J. Sheehan aff002;  Miriam L. Zichlin aff003;  Peter Zuckerman aff003;  Patrick Lefebvre aff001;  Paul E. Greenberg aff003
Působiště autorů: Analysis Group, Inc., Montréal, QC, Canada aff001;  Janssen Scientific Affairs, LLC., Titusville, NJ, United States of America aff002;  Analysis Group, Inc., Boston, MA, United States of America aff003
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0223255



Previous studies have assessed the incremental economic burden of treatment-resistant depression (TRD) versus non-treatment-resistant major depressive disorder (i.e., non-TRD MDD) in commercially-insured and Medicaid-insured patients, but none have focused on Medicare-insured patients.


To assess healthcare resource utilization (HRU) and costs of patients with TRD versus non-TRD MDD or without major depressive disorder (MDD; i.e., non-MDD) in a Medicare-insured population.


Adult patients were retrospectively identified from the Chronic Condition Warehouse de-identified 100% Medicare database (01/2010-12/2016). MDD was defined as ≥1 MDD diagnosis and ≥1 claim for an antidepressant. Patients initiated on a third antidepressant following two antidepressant treatment regimens of adequate dose and duration were considered to have TRD. The index date was defined as the date of the first antidepressant claim for the TRD and non-TRD MDD cohorts, and as a randomly imputed date for the non-MDD cohort. Patients with TRD were matched 1:1 to non-TRD MDD patients and randomly selected non-MDD patients based on propensity scores. Analyses were also performed for a subset of patients aged ≥65.


Of 29,543 patients with MDD, 3,225 (10.9%) met the study definition of TRD; 157,611 were included in the non-MDD cohort. Matched patients with TRD and non-TRD MDD were, on average, 58.9 and 59.0 years old, respectively. The TRD cohort had higher per-patient-per-year (PPPY) HRU than the non-TRD MDD (e.g., inpatient visits: incidence rate ratio [IRR] = 1.36) and non-MDD cohorts (e.g., inpatient visits: IRR = 1.84, all P<0.001). The TRD cohort had significantly higher total PPPY healthcare costs than the non-TRD MDD cohort ($25,517 vs. $20,425, adjusted cost difference = $3,385) and non-MDD cohort ($25,517 vs. $14,542, adjusted cost difference = $4,015, all P<0.001). Similar results were found for the subset of patients ≥65.


Among Medicare-insured patients, those with TRD had higher HRU and costs compared to those with non-TRD MDD and non-MDD.

Klíčová slova:

Antidepressants – Critical care and emergency medicine – Depression – Diagnostic medicine – Health economics – Inpatients – Medicare – Outpatients


1. National Institute of Mental Health (NIMH). Major Depression 2017 [Available from: https://www.nimh.nih.gov/health/statistics/major-depression.shtml.

2. Centers for Medicare & Medicaid Services. CMS Fast Facts 2019 [Available from: Available from: https://www.cms.gov/fastfacts/.

3. Greenberg PE, Fournier AA, Sisitsky T, Pike CT, Kessler RC. The economic burden of adults with major depressive disorder in the United States (2005 and 2010). J Clin Psychiatry. 2015;76(2):155–62. doi: 10.4088/JCP.14m09298 25742202

4. Susbtance Abuse and Mental Health Services Administration. Prohections of National Expenditures for Treatment of Mental and Susbtance Use Disorders, 2010–2020 Rockville, MD [Available from: Available from: https://store.samhsa.gov/system/files/sma14-4883.pdf.

5. Work Group on Major Depressive Disorder. Practice Guidelines For the Treatment of Patients With Major Depressive Disorder—Third Edition: American Psychiatric Association; 2010 [Available from: Available from: http://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/mdd.pdf.

6. Mrazek DA, Hornberger JC, Altar CA, Degtiar I. A review of the clinical, economic, and societal burden of treatment-resistant depression: 1996–2013. Psychiatric services. 2014;65(8):977–87. doi: 10.1176/appi.ps.201300059 24789696

7. Rush AJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Stewart JW, Warden D et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR* D report. American Journal of Psychiatry. 2006;163(11):1905–17. doi: 10.1176/ajp.2006.163.11.1905 17074942

8. Mihanovic M, Restek-Petrovic B, Bodor D, Molnar S, Oreskovic A, Presecki P. Suicidality and side effects of antidepressants and antipsychotics. Psychiatr Danub. 2010;22(1):79–84. 20305596

9. Peet M. Induction of mania with selective serotonin re-uptake inhibitors and tricyclic antidepressants. Br J Psychiatry. 1994;164(4):549–50. doi: 10.1192/bjp.164.4.549 8038948

10. Gaynes B, Asher G, Gartlehner G, Hoffman V, Green J, Boland J et al. Definition of Treatment-Resistant Depression in the Medicare Population. Rockville, MD: Agency for Healthcare Research and Quality; 2018.

11. Conway CR, George MS, Sackeim HA. Toward an Evidence-Based, Operational Definition of Treatment-Resistant Depression: When Enough Is Enough. JAMA Psychiatry. 2017;74(1):9–10. doi: 10.1001/jamapsychiatry.2016.2586 27784055

12. Amos TB, Tandon N, Lefebvre P, Pilon D, Kamstra RL, Pivneva I et al. Direct and Indirect Cost Burden and Change of Employment Status in Treatment-Resistant Depression: A Matched-Cohort Study Using a US Commercial Claims Database. J Clin Psychiatry. 2018;79(2).

13. Cepeda MS, Reps J, Fife D, Blacketer C, Stang P, Ryan P. Finding treatment-resistant depression in real-world data: How a data-driven approach compares with expert-based heuristics. Depress Anxiety. 2018;35(3):220–8. doi: 10.1002/da.22705 29244906

14. Cepeda MS, Reps J, Ryan P. Finding factors that predict treatment-resistant depression: Results of a cohort study. Depress Anxiety. 2018.

15. Corey-Lisle PK, Birnbaum HG, Greenberg PE, Marynchenko MB, Claxton AJ. Identification of a claims data "signature" and economic consequences for treatment-resistant depression. J Clin Psychiatry. 2002;63(8):717–26. doi: 10.4088/jcp.v63n0810 12197453

16. Ivanova JI, Birnbaum HG, Kidolezi Y, Subramanian G, Khan SA, Stensland MD. Direct and indirect costs of employees with treatment-resistant and non-treatment-resistant major depressive disorder. Curr Med Res Opin. 2010;26(10):2475–84. doi: 10.1185/03007995.2010.517716 20825269

17. Olfson M, Amos TB, Benson C, McRae J, Marcus SC. Prospective Service Use and Health Care Costs of Medicaid Beneficiaries with Treatment-Resistant Depression. J Manag Care Spec Pharm. 2018;24(3):226–36. doi: 10.18553/jmcp.2018.24.3.226 29485948

18. Pilon D, Sheehan JJ, Szukis H, Singer D, Jacques P, Lejeune D et al. Medicaid spending burden among beneficiaries with treatment-resistant depression. J Comp Eff Res. 2019;8(6):381–92. doi: 10.2217/cer-2018-0140 30734581

19. Joshi K, Zhdanava M, Pilon D, Lefebvre P, Sheehan JJ. Health Care Use and Associated Cost Among Patients With Treatment-resistant Depression Across US Payers: A Comprehensive Analysis. Academy of Managed Care Pharmacy 2019 meeting; San Diego, CA2019.

20. Olchanski N, McInnis Myers M, Halseth M, Cyr PL, Bockstedt L, Gross TF et al. The economic burden of treatment-resistant depression. Clin Ther. 2013;35(4):512–22. doi: 10.1016/j.clinthera.2012.09.001 23490291

21. Benson C, Huang A, Amos T, Wang L, Baser O. Economic Burden of Illness Among US Veterans With Treatment-Resistant Depression Psych Congress 2018; 2018; Orlando, FL.

22. U.S. Department of Health and Human Services. Who is eligible for Medicare? 2019 [Available from: Available from: https://www.hhs.gov/answers/medicare-and-medicaid/who-is-elibible-for-medicare/index.html.

23. Hasin DS, Sarvet AL, Meyers JL, Stinson FS, Grant BF. Epidemiology of adult DSM-5 major depressive disorder and its specifiers in the United States. JAMA psychiatry. 2018;75(4):336–46. doi: 10.1001/jamapsychiatry.2017.4602 29450462

24. Fiske A, Wetherell JL, Gatz M. Depression in older adults. Annu Rev Clin Psychol. 2009;5:363–89. doi: 10.1146/annurev.clinpsy.032408.153621 19327033

25. SAMHSA—Substance Abuse and Mental Health Services Administration. National Survey on Drug Use and Health 2016—Table 8.56B [Available from: Available from: https://www.samhsa.gov/data/sites/default/files/cbhsq-reports/NSDUHDetailedTabs2017/NSDUHDetailedTabs2017.htm#tab8-56A.

26. Mitchell AJ, Subramaniam H. Prognosis of depression in old age compared to middle age: a systematic review of comparative studies. Am J Psychiatry. 2005;162(9):1588–601. doi: 10.1176/appi.ajp.162.9.1588 16135616

27. US Census Bureau. Census Regions and Divisions of the United States [Available from: http://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf.

28. Quan H, Sundararajan V, Halfon P et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Medical care. 2005:1130–9. doi: 10.1097/01.mlr.0000182534.19832.83 16224307

29. Elixhauser A, Steiner C, Kruzikas D. HCUP Methods Series Report # 2004–1—Comorbidity Software Documentation Rockville, MD, USA 2004 [Available from: http://www.hcup-us.ahrq.gov/reports/ComorbiditySoftwareDocumentationFinal.pdf.

30. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5®): American Psychiatric Pub; 2013.

31. Bradley B, Backus D, Gray E. Depression in the older adult: What should be considered? Ment Health Clin. 2016;6(5):222–8. doi: 10.9740/mhc.2016.09.222 29955474

32. Papakostas GI, Petersen T, Sonawalla SB et al. Serum cholesterol in treatment-resistant depression. Neuropsychobiology. 2003;47(3):146–51. doi: 10.1159/000070584 12759558

33. Sonawalla SB, Papakostas GI, Petersen TJ, Yeung AS, Smith MM, Sickinger AH et al. Elevated cholesterol levels associated with nonresponse to fluoxetine treatment in major depressive disorder. Psychosomatics. 2002;43(4):310–6. doi: 10.1176/appi.psy.43.4.310 12189257

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