In the hospital setting, suboptimal bed utilization can cascade into a multitude of unpleasant or even unsafe experiences for patients — not to mention wasted resources and revenue loss for hospitals.
Our client, a for-profit hospital system, was having trouble determining the right number of staff to schedule for servicing (or “turning around”) beds in any given ward of the hospital. As a result, the client had been experiencing many of these “cascading issues” firsthand.
In wards with too few staff scheduled, staff members could become very stressed while rushing around to prepare rooms. This prompted some to worry about patient safety.
“When beds aren’t ready and staff feels tension and pressure to complete their tasks in a hurry, patient safety can be compromised,” the client explained.
“It’s a very stressful way to work,” she said. “During high-capacity hours, it’s like Grand Central Station. We have to work quickly to clean the rooms, make sure each room has the right equipment, and then get our patients into beds.”
Meanwhile, other wards of the hospital might have too many service staff scheduled for turning around a much smaller number of beds.
Our client knew there were times when beds would be empty, but they couldn’t predict when those times would be or anticipate bed usage and turnaround times with accuracy.
When hospital administrators learned data analytics could provide a solution, they were interested in pursuing it.
Unfortunately, the data needed to conduct a proper predictive analysis existed within several disparate systems throughout the hospital. The hospital’s own IT department had no easy way of collecting or using their data. Stretched to capacity with the daily operational tasks, the hospital’s IT experts didn’t have the bandwidth to build a new solution.
That’s when the hospital decided to hire a data and analytics partner to help them streamline and use their data to unlock insights into optimizing staffing and anticipating hospital bed utilization.
