Outcomes monitoring and the testing of new psychiatric treatments: Work therapy in the treatment of chronic post-traumatic stress disorder

Objective. To evaluate the effectiveness of a work therapy intervention, th e Department of Veterans Affairs (VA) Compensated Work Therapy program (CWT ), in the treatment of patients suffering from chronic war-related post-tra umatic stress disorder (PTSD); and to demonstrate methods for using outcome s monitoring data to screen previously untested treatments. Data Sources/Study Setting. Baseline and four-month follow-up questionnaire s administered to 3,076 veterans treated in 52 specialized VA inpatient pro grams for treatment of PTSD at facilities that also had CWT programs. Altog ether 78 (2.5 percent) of these patients participated in CWT during the fou r months after discharge. Study Design. The study used a pre-post nonequivalent control group design. Data Collection/Extractian Methods. Questionnaires documented PTSD symptoms , violent behavior, alcohol and drug use, employment status, and medical st atus at the time of program entry and four-months after discharge from the hospital to the community. Administrative databases were used to identify p articipants in the CWT program. Propensity scores were used to match CWT pa rticipants and other patients, and hierarchical linear modeling was used to evaluate differences in outcomes between treatment groups on seven outcome s. Principal Findings. The propensity scaling method created groups that were not significantly different on any measure. No greater improvement was obse rved among CWT participants than among other patients on any of seven outco me measures. Conclusions. Substantively this study suggests that work therapy, as curren tly practiced in VA, is not an effective intervention, at least in the shor t term, for chronic, war-related PTSD. Methodologically it illustrates the use of outcomes monitoring data to screen previously untested treatments an d the use of propensity scoring and hierarchical linear modeling to adjust for selection biases in observational studies.