skip to Main Content
Time

Improving staffing management through analytics

Kathy Bennett

Content writer for PAN Communications

In our recent webinar writeup, “Leveraging Your EHR Investment with Analytics,” Steve Hess, Chief Information Officer of The University of Colorado Health (UC Health), shared how the healthcare system leveraged its investment in an enterprise-wide EHR with the use of machine learning and AI.  Using constraint-based optimization methods and simulation algorithms available through  of LeanTaaS solutions iQueue for Inpatient Beds, iQueue for OR and iQueue for Infusion Centers, they were able to optimize capacity, significantly reducing overtime and decreasing patient wait time

But a further benefit of this technology is exceptionally important during the COVID pandemic – the ability to optimize staffing management across a system to accommodate unpredictable surges in demand.

In a hospital system like UCHealth, there are different organizations, including large academic centers, small community hospitals, outpatient practices, and independent clinics. As UCHealth introduced Epic system-wide, the EHR was shared seamlessly across them all. When it comes to surge capacity and staffing management, each organization operates independently for the most part. But by layering analytics on top of their EHR, UC Health has been able to optimize a central staffing pool by looking at supply and demand across the entire system.

Hess explained that through the use of LeanTaaS solutions, UCHealth was better able to predict demand for services. This is especially critical during COVID, when must be prepared for a surge at any time. By predicting demand, UCHealth leaders were able to stand up surge capacity well in advance. Predicting staffing for surge capacity requires a sophisticated modeling scheme. How do you rescale, on the fly, all clinical staff, both licensed and non-licensed, given that demands are ever changing?

Hess explained, “Going into COVID, we looked at all of our clinicians from a competency, skill, and license perspective and sorted them into labor pools. This allowed us to pull from ICU to inpatient or ambulatory, to inpatient from informatics to inpatient and everything in between. So we tried to meet that demand-supply matching through our central labor pool.”

“But what’s really important to understand is that we actually leveraged the electronic health record and the intelligence to get to the point where we were predicting what the surge looks like and then staying one step ahead of it from a staffing perspective, and also medical equipment perspective. You need to make sure you understand what the physical areas are, what your medical equipment is, what your staffing is, and then matching it best you can. COVID challenged us all to think creatively about matching multiple staffing pools across a common supply.”

With an enterprise-wide EHR combined with LeanTaaS solutions, UCHealth was able predict demand, and match that need with the staffing necessary to provide patient care across their entire footprint. This allows them to be better prepared with staffing management no matter what demand surge COVID brings next.

 

Back To Top