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Research Article
29 November 2024

Antidepressant therapeutic strategies and health care utilization in patients with depression

Publication: Journal of Managed Care & Specialty Pharmacy
Volume 30, Number 12

Abstract

BACKGROUND:

Individuals with depression who do not respond to initial antidepressant may switch to a different antidepressant, add a second antidepressant, or add an atypical antipsychotic. Previous studies comparing these strategies’ efficacy and safety reported conflicting results, and the impact of these strategies on subsequent health care utilization is unknown.

OBJECTIVE:

To compare health care utilization between individuals with depression who switched antidepressants, added a second antidepressant (ie, combination), or added an atypical antipsychotic (ie, augmentation) following their initial antidepressant.

METHODS:

This retrospective cohort study used a 25% random sample of the IQVIA PharMetrics Plus for Academics health plan claims database. The study cohort included individuals aged 10-64 years who newly initiated an antidepressant at any point from January 2016 to December 2020. New use was defined as no evidence of an antidepressant in the 180 days preceding the antidepressant dispensing. Individuals had to have a depression diagnosis and a treatment change in the 180 days following the initial antidepressant. The index date was the date of the first observed antidepressant change, which was defined as a switch, combination, or augmentation. Health care utilization, measured as the number of outpatient visits, any all-cause hospitalization, and any emergency department (ED) visit, was assessed in the 180 days after the index date. Negative binomial regression models evaluated the rate ratio of the number of outpatient visits. Logistic regression models estimated the odds ratio of a hospitalization, and modified Poisson regression estimated the relative risk of an ED visit. Models were adjusted for demographics, clinical characteristics, and previous health care utilization.

RESULTS:

Among 3,847 individuals with depression who had the first treatment change following the initial antidepressant, we identified 2,418 (62.9%) who switched, 1,268 (33.0%) who combined, and 161 (4.2%) who augmented their antidepressant. The augmentation group had a significantly higher rate of outpatient visits than the combination group (adjusted rate ratio = 1.14, 95% CI = 1.04-1.25). There was no statistically significant difference in hospitalizations or ED visits between the switch and augmentation vs combination groups.

CONCLUSIONS:

Augmentation comprised 4% of our antidepressant cohort but had higher outpatient health care utilization than those who combined treatment.

Plain language summary

Individuals with depression who switch to a different antidepressant or add a second antidepressant to their initial antidepressant have similar use of outpatient, inpatient, and emergency department visits within 180 days of follow-up. Individuals who augment their initial antidepressant with an atypical antipsychotic medication have higher use of outpatient visits relative to those who combine with an antidepressant.

Implications for managed care pharmacy

Individuals who add an atypical antipsychotic to their antidepressant may have more impairment because of depression and require more outpatient health care services than those who combine treatment with an antidepressant. There were no differences across the 3 treatment strategies in terms of hospitalization or emergency department visits. Augmentation strategies should be reserved for individuals on antidepressant medications for at least 84 days (acute phase treatment) or for at least 180 days (continuation phase treatment).

Supplementary Material

Supplemental Material (24-212_supplement.pdf)
Supplemental Material

REFERENCES

1.
Goodwin RD, Dierker LC, Wu M, Galea S, Hoven CW, Weinberger AH. Trends in U.S. depression prevalence from 2015 to 2020: The widening treatment gap. Am J Prev Med. 2022;63(5):726-33.
2.
Mojtabai R, Olfson M, Han B. National trends in the prevalence and treatment of depression in adolescents and young adults. Pediatrics. 2016;138(6):e20161878.
3.
Walter HJ, Bukstein OG, Abright AR, et al. Clinical practice guideline for the assessment and treatment of children and adolescents with anxiety disorders. J Am Acad Child Adolesc Psychiatry. 2020;59(10):1107-24.
4.
Qaseem A, Owens DK, Etxeandia-Ikobaltzeta I, Tufte J, Cross JT Jr, Wilt TJ; Clinical Guidelines Committee of the American College of Physicians. Nonpharmacologic and pharmacologic treatments of adults in the acute phase of major depressive disorder: A living clinical guideline from the American College of Physicians. Ann Intern Med. 2023;176(2):239-52.
5.
Ohayon MM, McCue M, Krystal A, et al. Longitudinal study to assess antidepressant treatment patterns and outcomes in individuals with depression in the general population. J Affect Disord. 2023;321:272-8.
6.
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(1):28-40.
7.
Gauthier G, Guérin A, Zhdanava M, et al. Treatment patterns, healthcare resource utilization, and costs following first-line antidepressant treatment in major depressive disorder: A retrospective US claims database analysis. BMC Psychiatry. 2017;17(1):222.
8.
Zhu L, Ferries E, Suthoff E, Namjoshi M, Bera R. Economic burden and antidepressant treatment patterns among patients with major depressive disorder in the United States. JMCP. 2022;28(11-a Suppl):S2-13.
9.
American Psychological Association. Clinical Practice Guideline for the Treatment of Depression across Three Age Cohorts. American Psychological Association; 2019. Accessed March 20, 2024. https://www.apa.org/depression-guideline
10.
Gaynes BN, Dusetzina SB, Ellis AR, et al. Treating depression after initial treatment failure: directly comparing switch and augmenting strategies in STAR*D. J Clin Psychopharmacol. 2012;32(1):114-9.
11.
Lenze EJ, Mulsant BH, Roose SP, et al. Antidepressant augmentation versus switch in treatment-resistant geriatric depression. N Engl J Med. 2023;388(12):1067-79.
12.
Mohamed S, Johnson GR, Chen P, et al; and the VAST-D Investigators. Effect of antidepressant switching vs augmentation on remission among patients with major depressive disorder unresponsive to antidepressant treatment: The VAST-D Randomized Clinical Trial. JAMA. 2017;318(2):132-45.
13.
Gerhard T, Stroup TS, Correll CU, et al. Mortality risk of antipsychotic augmentation for adult depression. Wright JM, ed. PLoS ONE. 2020;15(9):e0239206.
14.
Davies P, Ijaz S, Williams CJ, Kessler D, Lewis G, Wiles N. Pharmacological interventions for treatment-resistant depression in adults. Cochrane Database Syst Rev. 2019;12(12):CD010557.
15.
Greenberg PE, Fournier AA, Sisitsky T, et al. The economic burden of adults with major depressive disorder in the United States (2010 and 2018). PharmacoEconomics. 2021;39(6):653-65.
16.
Strawn JR, Mills JA, Poweleit EA, Ramsey LB, Croarkin PE. Adverse effects of antidepressant medications and their management in children and adolescents. Pharmacotherapy. 2023;43(7):675-90.
17.
Dwyer JB, Bloch MH. Antidepressants for pediatric patients. Curr Psychiatr. 2019;18(9):26-42F.
18.
Turner K. MCHP SAS Macro Code - ICD-10 Charlson Index - _CharlsonICD10.sas.txt. May 11, 2006. Accessed March 29, 2024. http://mchp-appserv.cpe.umanitoba.ca/Upload/SAS/_CharlsonICD10.sas.txt
19.
Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159(7):702-6.
20.
Sørensen A, Juhl Jørgensen K, Munkholm K. Clinical practice guideline recommendations on tapering and discontinuing antidepressants for depression: A systematic review. Ther Adv Psychopharmacol. 2022;12:20451253211067656.

Information & Authors

Information

Published In

cover image Journal of Managed Care & Specialty Pharmacy
Journal of Managed Care & Specialty Pharmacy
Volume 30Number 12December 2024
Pages: 1455 - 1466

History

Published online: 29 November 2024
Published in print: December 2024

Authors

Affiliations

Phuong Tran, MPH* [email protected]
University of Maryland School of Pharmacy, Baltimore.
Susan dosReis, PhD
University of Maryland School of Pharmacy, Baltimore.
Eberechukwu Onukwugha, PhD
University of Maryland School of Pharmacy, Baltimore.
Haeyoung Lee, PharmD
University of Maryland School of Pharmacy, Baltimore.
Julia F. Slejko, PhD
University of Maryland School of Pharmacy, Baltimore.

Notes

*
AUTHOR CORRESPONDENCE: Phuong Tran, +1.667.910.2829; [email protected]
Dr Slejko reports grants from PhRMA Foundation, National Health Council, and Genentech and consulting fees from Boehringer Ingelheim and Sage Therapeutics, outside the submitted work. Dr dosReis reports grants from GlaxoSmithKline and National Institute of Health and consulting fees from Alexion, outside the submitted work. Dr Onukwugha reports grants from Organon LLC and BeiGene Ltd, and consulting fees from PhRMA Foundation, The Center for Innovation and Value Initiative, outside the submitted work.

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