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Published on: October 2, 2014
Demographic, Economic, and Clinical Correlates of Depression Treatment Response in an Underserved Primary Care
Dinesh Mittal1,2, Lakshminarayana Chekuri2,3, Liya Lu2
1Health Services Research and Development, Central Arkansas Veterans Healthcare System, North Little Rock; and South Central Mental Illness Research Education and Clinical Center, Central Arkansas Veterans Healthcare System, North Little Rock
Objective:
To examine demographic, economic, and clinical correlates of depression treatment outcomes in a rural low-income population served by federally qualified health centers (FQHCs).
Method:
The current study utilized data collected during a pragmatic comparative effectiveness trial (N = 364) that was conducted at 9 FQHC clinics between November 2007 and June 2009. Participants were randomly assigned to either telemedicine-based collaborative care or practice-based collaborative care. Depression severity was measured at baseline and at 12-month follow-up using the Hopkins Symptom Checklist (SCL-20) and used to categorize outcomes as nonresponse, partial response, full response, and remission. The associations between demographic, economic, and clinical variables and outcomes were estimated using bivariate analyses and multinomial logistic regression.
Results:
287 participants (78.8%) completed the 12-month follow-up assessment. Among these, 127 participants (44.25%) did not respond to treatment, 53 (18.47%) experienced partial response, 47 (16.38%) experienced full response, and 60 (20.91%) experienced remission. Of the 7 demographic characteristics examined, only gender had a significant (P < .05) effect on outcomes. Of the 2 economic variables examined, income was not associated with outcomes, while individuals without health insurance reported higher response rates than those with public health insurance (P < .05). Among the 13 clinical variables examined, baseline depression severity, physical and mental health status, number of prior depression episodes, and comorbid generalized anxiety had a significant (P < .05) effect on outcomes.
Conclusions:
Low treatment response rates and treatment response heterogeneity continue to be significant challenges to clinicians treating depression in low-income underserved populations facing multiple barriers to care. Baseline depression severity and chronicity, health status, and comorbid anxiety appear to have a consistent effect on treatment outcomes in depression.
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