Data Curbs Healthcare Overtime to Cut Costs 

Healthcare labor arguably fills up the industry’s largest division of funding, with some reports estimating that labor alone accounts for roughly 60 percent of operating budgets. But while labor does fill a fundamental role, hospital executives are searching for ways to reduce this spending.

While some organizations have laid off workers or undergone hiring freezes, these measures come with the risk of compromising patient care as staff become spread too thin. With the Affordable Care Act underway, the number of patients entering healthcare centers is only set to rise, which has led some to turn to data.

Specifically, Ellis Medicine, a healthcare system in Schenectady, N.Y., has found the balance between keeping a robust staff and minimizing labor costs.

“The configuration of hospitals is changing,” explains Joseph Giansante, Ellis’ vice president of human resources in an interview with Healthcare Informatics. “That changing environment has now demanded hospitals to be much more effective and efficient in managing their labor costs.”

Instead of laying off workers and freezing new hires, Ellis has partnered with API Healthcare, a Hartford Wis.,-based IT provider for the healthcare industry to find a solution through data. In the six months since then, the organization has managed to cut $721,000 in overtime without understaffing a single unit.

While human resources was once defined by sitting down with employees and making sure their happy in their working environment, Sara Zappi, director of human resources at Ellis says that data has led to a fundamental change in the way she does her job. “Once you have the metrics, you can make decisions based on data and not based on feelings. You are a better organization if you have data to support your business.”

Zappi says that by using metric-driven workforce planning she can measure when regular versus overtime hours are being used so that Ellis can plan ahead for what they need. “We know that there are certain weeks when we will have a specific volume based on historical data, so we can move forward and staff appropriately,” Zappi says. “That ability has been amazing to us.”

Through their near transparent, real-time scheduling system, Ellis is able to identify when and where too many employees are on staff and redeploy them to create a more efficient hospital floor as well as to cut back on labor costs.