Method: Patients (N = 455) receiving services at five rural health clinics self-reported symptoms of depression as part of an ongoing evaluation to study the effectiveness of integrated health. Depression was assessed using the nine item Patient Health Questionnaire. ANOVA was used to assess differences overtime and trajectories were identified with cluster analyses. Health related factors associated with these trajectories were assessed using logistic regression.
Results: Significant overall decreases in depressive symptoms overtime were found; individual trajectories were identified and include moderate declines, steep declines, and stable high symptoms. Financial problems, race, emergency room visits, missed appointments, chronic pain, substance use, and life stressors correctly classified trajectory membership.
Conclusion and Implications: Trajectories indicate that patients have differing treatment needs and cluster analysis as an evaluation technique may be useful in identifying what treatment works and for whom. The present study addresses a major concern for healthcare providers and emphasizes the importance of identifying health related vulnerabilities that contribute to mental health outcomes. Sub-group analyses are a useful tool for developing more targeted treatment and improved evaluation techniques in integrated healthcare can improve health equity of patients by understanding for whom the interventions work.