Objective: Estimate (1) prevalence of major depressive disorder (MDD) diagnosis; (2) risk factors associated with MDD diagnosis; (3) time at which MDD is diagnosed post-spinal cord injury (SCI); and (4) interaction of inferred mobility status (IMS) in a commercially insured population over 3 years.
Design: Retrospective longitudinal cohort design.
Setting: A commercial insurance claims database from January 1, 2010 to December 31, 2013.
Participants: Individuals with an index cervical or thoracic SCI in 2011 or 2012, without history of MDD ≤30 days pre-SCI (N=1409).
Intervention: Not applicable.
Main outcome measures: Prevalence of, risk factors associated with, and time to MDD diagnosis post-SCI. A stratified survival analysis using IMS, based upon durable medical equipment (DME) claims, was also completed.
Results: Post-SCI, 294 out of 1409 (20.87%) were diagnosed with new-onset MDD. Significant (P<.05) risk factors included: employment, length of index hospitalization, discharge from index hospitalization with healthcare services, rehabilitation services post-SCI, and 2 of 5 IMS comparisons. Median time to MDD was 86 days. Survival analysis demonstrated a significant difference between 6 of 10 IMS comparisons. Regarding new-onset or recurring MDD, 432 out of 1409 (30.66%) were diagnosed post-SCI. Significant risk factors included: female, employment, length of index hospitalization, discharge from index hospitalization with healthcare services, rehabilitation services post-SCI, MDD>30 days pre-SCI, catheter claims, and 2 of 5 IMS comparisons. Median time to MDD was 74 days. Survival analysis demonstrated a significant difference between 4 of 10 IMS comparisons.
Conclusions: Prevalence of MDD post-SCI is greater than the general population. Stratification by IMS illustrated that individuals with greater inferred reliance on DME are at a greater risk for MDD and have shorter time to MDD diagnosis post-SCI.
Keywords: Cluster analysis; Depression; Durable medical equipment; Rehabilitation; Spinal cord injuries; Survival analysis.
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