The untapped power of predictive analytics
When Katie Oliva, Principal Healthcare Consultant at Amitech Solutions, was a Clinical Nurse Specialist in South Bend, Indiana, she’d brace herself during the football season. “Notre Dame home game weekends—the ICU would always be full,” recalls Katie. “People would drink, there would be accidents, or maybe a brawl, and we’d have an influx of patients coming into the hospital.”
What Katie was identifying over 20 years ago in her time at Memorial Hospital was actually predictive analytics—using past data to predict future outcomes.
Predictive analytics is an incredibly powerful tool. It can help identify patients at risk of developing certain diseases or who are more susceptible to hospital readmissions. It can also help allocate resources strategically and efficiently, like staffing and scheduling.
Most hospitals already have this secret weapon but have not tapped into its potential. “We have done millions of schedules and census management, daily bed meetings. We have all that data, but we just haven’t done anything with it,” says Katie.
“Take surgery, for example,” she explains. “It is relatively predictable. We know there is an uptick at the end of the year when people have hit their deductibles and are trying to get elective surgeries.” Another example Katie provides is the ebb and flow of the emergency room. Depending on the ER, typically in the afternoons, admissions begin to rise; around 1:00 am things peak, and then go back down until the next afternoon. Why not schedule accordingly? “Our staff and employees are hard to come by,” says Katie. “We don’t want them to be working when we have a very low census. We can use this data to have the right staff for the right amount of patients.”
Coupled with artificial intelligence, which has the capability to identify specific trends or patterns among individual patients and groups, there is an opportunity to precisely improve not only administrative and staffing issues but also patient outcomes.
Katie recalls a program where COPD patients were identified as high-risk for hospital readmission. The hospital was able to design outreach programs and assign case managers—and readmissions dropped. This outcome was beneficial not just for the patients and hospital systems, but also for healthcare payers. “We’re at the point, industry-wide, where we need to utilize our resources better than we have historically,” says Katie. “Predictive analytics helps us manage care more effectively, make informed decisions, and control costs.”
To learn more about the power of predictive analytics and intelligent automation, connect with Katie.
