The Analytics of Rehabilitation
Data scientists lead the charge for more successful substance abuse treatment
Tuesday, March 13, 2018
With the increase of deaths related to substance, opioid and alcohol abuse, the need for outcomes’ analysis in relation to rehabilitation centers has arisen. Virginia Miori, Ph.D., Kathleen Campbell Garwood, Ph.D., and Catherine Cardamone ’18 teamed up with the Futures of Palm Beach rehabilitation center in their study “Forecasting Treatment Outcomes for the Futures Drug and Alcohol Rehabilitation Center,” published in Emerald Insight’s Advances in Business and Management Forecasting, Vol. 12.
Miori, associate professor of decision and system sciences, led the project, which has included two studies so far. “While our first study established the benchmark for data analysis, we were able to fully analyze results with the second,” she explains. “The healthcare industry lags behind others in the area of analytics, and I saw an opportunity with Futures.”
She engaged Campbell Garwood, assistant professor of decision and system sciences, in the collaboration because of her work in data mining. “I like to keep my data analysis based around subjects that can help others,” says Campbell. “This was an ideal position for my interests.” Cardamone, of Media, Pennsylvania, majored in business intelligence at Saint Joseph’s University and completed her undergraduate degree early to enroll in the University’s M.S. in business intelligence program.
The team used surveys taken by the rehabilitation center’s clients and alumni, which included questions regarding any ongoing drug abuse, life experience and their time at Futures. These interviews were conducted in intervals upon their termination from the rehabilitation program throughout 2016. The demographics for this test were based on gender, age, marital status, primary drug of choice, insurance coverage and type of discharge from the facility.
The data scientists found that one primary indicator of a client’s success was their length of stay at Futures. When a patient stays for 28-30 days, their likelihood for success rises exponentially compared to someone who leaves early. While it may seem obvious that duration of stay would affect a client’s success, Miori explains that some may have to leave before they are ready.
“Length of stay often depends on insurance coverage,” Miori says. “Insurance companies only allow a limited number of days at a center, and every week the center has to make inquiries as to whether patients can still be covered. So while some leave on their own, others don’t have another option.”
Their results indicate a need for more studies based on what is successful at rehabilitation centers and the characteristics that make for an accommodating staff.
“I commend Futures for their studies, because they have tried to find data behind what works to raise their reputation and to inform insurance companies of their success,” says Miori. “I would recommend other treatment centers take a look at what works and what doesn’t when it comes to the rehabilitation process.”
Miori will further connect data analytics to the healthcare field in Deeper Than Data: The Analytics of Rehab Success, the fifth episode of “Good to Know,” the Saint Joseph’s University Experts Podcast, available Wednesday, March 14.
Associate Professor of Decision and System Sciences Virginia Miori, Ph.D., is an expert in data analytics. Kathleen Campbell Garwood, Ph.D., assistant professor of decision and system sciences, is an expert in data mining. They can be reached for comment at firstname.lastname@example.org or email@example.com respectively, or by contacting the Office of Marketing and Communications at 610-660-1222.