Identification of a claims data "signature" and economic consequences for treatment-resistant depression.
BACKGROUND
Major depressive disorder (MDD) is a debilitating condition with significant economic consequences. Conservative estimates indicate that between 10% and 20% of all individuals with MDD are treatment resistant. The objectives for this study were (1) to use current treatment strategies identified in the literature to evaluate the validity of studying treatment-resistant depression (TRD) using claims data and (2) to estimate cost differences between TRD-likely and TRD-unlikely patients identified by use of treatment patterns.


METHODS
The data source consisted of medical, pharmaceutical, and disability claims from a Fortune 100 manufacturer for 1996 through 1998 (N = 125,242 continuously enrolled beneficiaries between the ages of 18 and 64 years). The sample included individuals with medical or disability claims for MDD (NMDD = 4186). A treatment pattern algorithm was applied to classify adult MDD patients into TRD-likely (NTRD = 487) and TRD-unlikely groups. Resource utilization and costs were compared among TRD-likely and TRD-unlikely patients and a random sample of average beneficiaries (i.e., 10% of all beneficiaries) for 1998.


RESULTS
Consistent with the epidemiologic literature, the algorithm classified 12% of the MDD sample as TRD-likely. Mean annual costs were $10,954 for TRD-likely patients, $5025 for TRD-unlikely patients, and $3006 for average beneficiaries. TRD-likely patients used almost twice as many medical services as did TRD-unlikely patients and incurred significantly greater indirect costs (p < .0001).


CONCLUSIONS
It is feasible to use an administrative dataset to develop a claim-based treatment algorithm to identify TRD-likely patients. Resource utilization by TRD-likely patients was substantial, not only for direct treatment of depression but also for treatment of comorbid medical conditions. Additionally, TRD imposed on employers substantial indirect costs resulting from high rates of depression-associated disability.
Corey-Lisle
Patricia K
PK
Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN 46285, USA. trishacl@lilly.com
Birnbaum
Howard G
HG
Greenberg
Paul E
PE
Marynchenko
Maryna B
MB
Claxton
Ami J
AJ
D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D002985:Clinical Protocols / Q000145:classification; D003365:Costs and Cost Analysis; D003866:Depressive Disorder / Q000191:economics* / Q000453:epidemiology* / Q000628:therapy; D004565:Electroconvulsive Therapy / Q000191:economics / Q000706:statistics & numerical data; D005260:Female; D006264:Health Benefit Plans, Employee / Q000191:economics / Q000706:statistics & numerical data; D017048:Health Care Costs; D006296:Health Services / Q000191:economics / Q000706:statistics & numerical data; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D008996:Monoamine Oxidase Inhibitors / Q000191:economics / Q000627:therapeutic use; D017410:Practice Guidelines as Topic; D012494:Sampling Studies; D016896:Treatment Outcome
D008996:Monoamine Oxidase Inhibitors