Prediction of Primary Care Depression Outcomes at Six Months: Validation of DOC-6 ©.

BACKGROUND The goal of this study was to develop and validate an assessment tool for adult primary care patients diagnosed with depression to determine predictive probability of clinical outcomes at 6 months. METHODS We retrospectively reviewed 3096 adult patients enrolled in collaborative care management (CCM) for depression. Patients enrolled on or before December 31, 2013, served as the training set (n = 2525), whereas those enrolled after that date served as the preliminary validation set (n = 571). RESULTS Six variables (2 demographic and 4 clinical) were statistically significant in determining clinical outcomes. Using the validation data set, the remission classifier produced the receiver operating characteristics (ROC) curve with a c-statistic or area under the curve (AUC) of 0.62 with predicted probabilities than ranged from 14.5% to 79.1%, with a median of 50.6%. The persistent depressive symptoms (PDS) classifier produced an ROC curve with a c-statistic or AUC of 0.67 and predicted probabilities that ranged from 5.5% to 73.1%, with a median of 23.5%. CONCLUSIONS We were able to identify readily available variables and then validated these in the prediction of depression remission and PDS at 6 months. The DOC-6 tool may be used to predict which patients may be at risk for worse outcomes.