Cost burden of treatment resistance in patients with depression.
THE AMERICAN JOURNAL OF MANAGED CARE 2010;
16:370-377. [PMID:
20469957]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
OBJECTIVE
To develop a claims-based scale for treatment-resistant depression (TRD) and estimate the associated direct cost burden.
STUDY DESIGN
Retrospective, observational study of patients receiving antidepressant therapy between January 2000 and June 2007 (N = 78,477).
METHODS
The Massachusetts General Hospital (MGH) clinical staging method for treatment resistance (assigning points for adequate trials of antidepressant medication, upward dose titration, extended duration, augmentation, and electroconvulsive therapy) was applied to claims data from the MarketScan Research Databases over a 24-month time period. Direct expenditures were measured over a subsequent 12-month period. Patients identified as having TRD (MGH score >or=3.5) (n = 22,593) were matched to depressed patients without TRD using propensity score methods. Regression models estimated the relationship between TRD and expenditures, controlling for sociodemographics, health plan type, and health status. Similar regression models estimated costs for an antidepressant-only version of the scale (MGH-AD).
RESULTS
Treatment resistance among depressed patients was associated with 40% higher medical care costs (P <.001). The MGH-AD score was associated with an increasing gradient in direct costs. Annual costs for patients with mild TRD (MGH-AD 3.5-4) were $1530 higher than those for non-TRD patients, and costs for patients with complex TRD (MGH-AD >or=6.5) were $4425 higher than those for non-TRD patients (all P <.001). A 1-point increase in the MGH-AD score was associated with a $590 increase in annual costs (P <.001).
CONCLUSIONS
Early identification of TRD patients, using a claims-based algorithm, may support targeted interventions for these patients.
Collapse