Clinicians who treat substance use disorders may have a new tool to help them guide the treatment and recovery process, according to a new case study by the Institute of Clinical and Translational Sciences (ICTS) on the Community Academic Partnership on Addiction (CAPA) Collaboration.
Associate Professor David Patterson Silver Wolf, who leads the collaboration, stated that there has historically been a lack of data to guide clinicians serving these populations Measurement of treatment and recovery performance relies heavily on anecdotal, unreliable information, he believes.
Patterson Silver Wolf used his 15 years of experience providing addiction treatment services, along with his experience investigating how to implement evidence-based practices throughout treatment organizations, to co-create a clinical dashboard called Takoda in which therapists can track and visualize recovery metrics. He collaborated with Ken Zheng, a 2014 graduate of Washington University’s McKelvey School of Engineering. The dashboard, which includes mobile apps, was implemented under the leadership of Patterson Silver Wolf in partnership with addiction treatment providers in the St. Louis region. After clinicians were trained to use the dashboard, they saw an 11% increase in addiction treatment completion rates over six months.
Brown School Professor Douglas Luke led a multi-disciplinary team in partnership with ICTS to highlight the project’s impact in a Translational Science Benefits Model (TSBM) case study. The TSBM is a framework that public health scientists can use to demonstrate the clinical, community, economic and policy impacts of their work in the real world.
“We chose to highlight this research because it has already demonstrated impact in the Clinical, Economic, and Community realms. This important project is using data-based approaches to improve recovery outcomes, while also reducing healthcare and crime-related costs of addiction,” said Luke.
Patterson Silver Wolf is excited to move forward. “The next logical steps would be to randomly assign therapists to use treatment as usual services or technology dashboard tools measuring patient’s treatment retention and completion outcomes,” he said.