Effective workforce management in healthcare delivery organizations is an ongoing challenge driven by factors such as the need for highly skilled professionals and workers and the 24/7 operational schedule. According to Fitch Ratings, personnel costs represent between 50 to 60 percent of hospital operating revenue, and as most healthcare organizations operate on tight margins, efficient workforce management is critical. Increasingly, healthcare organizations are applying data analytics technology to workforce management in order to make data-driven, on-demand staffing decisions.
New Brunswick, N.J.-based Robert Wood Johnson University Hospital, flagship hospital of Robert Wood Johnson Health System, has implemented time and attendance, employee scheduling, workforce analytics, and mobile applications solutions with the aim of improving productivity and employee engagement, according to Christine Silvia, productivity manager, Robert Wood Johnson University Hospital (RWJUH). And, by better matching labor levels to fluctuating patient volumes and controlling costs, RWJUH has, to date, realized cost savings of $10 million.
The hospital worked with health IT vendor Kronos to deploy a workforce analytics application, and according to Silvia, the mobile analytics application gives managers instant access and insight into actionable information. The full technology suite deployed at RWJUH enables managers and hospital leaders to monitor data and compare it to benchmarks, budget volume, and patient demand, helping the hospital minimize unnecessary overtime, over staffing and inflated costs.
Hospital managers also gained more visibility into employee data, which specifically helps with making evidence-based staffing decisions as managers attempt to manage costs without sacrificing employee engagement and quality of patient care.
“I think it has improved patient care because now we are staffed correctly,” Silvia says, noting that an ongoing healthcare staffing challenge is the volatility of workload and volumes and flexing staff up and down to meet the patient volume. “By using this tool, managers can more efficiently staff to the volume in the moment. This has given us a much better way to make on-demand, data-driven decisions.”
