An innovative hospital staffing solution

Avantas forecasts hospital staffing needs with a 97% accuracy rate

By taking years of data and industry expertise and pairing it with the analytic power of SAS® Forecast Server, Avantas helps client hospitals spend more time on patient care and less time developing staffing plans for their units. One Avantas client estimates it saved more than $23 million over five years using the Avantas solution powered by SAS.

The Omaha, NE, company is recognized for proven, best-practice work strategies for the health care industry and provides staffing forecasts to more than 75 facilities across the country. Avantas' offerings help hospitals spend less time on administrative staffing tasks and more time on improving the quality of patient care at the nursing-unit level. More effective staffing helps hospitals save money and improve morale by reducing dependence on contract nurses and last-minute schedule changes. With forecasts accurate to 97 percent 30 days out, hospitals are better able to assign bonus dollars to work shifts that are the hardest to fill, and use shift premiums and overtime more effectively.

SAS has the ability to incorporate hundreds of different models, allowing us to create a custom forecasting methodology. That is very important because every unit in a hospital behaves so differently.

Jackie Larson
Senior Vice President

Avantas had developed a proprietary algorithm for forecasting staffing needs, but prior to using SAS, the process was too manual and time-consuming. With each forecast taking three to four weeks to complete, the company couldn't expand without hiring additional staff.

Avantas chose SAS because it can handle thousands of models and automate the process. "SAS has the ability to incorporate hundreds of different models, allowing us to create a custom forecasting methodology. That is very important because every unit in a hospital behaves so differently," explains Jackie Larson, Senior Vice President at Avantas.

Hospital systems, such as the 31-facility Mercy Health System based in Missouri, help choose which factors are used in creating unit staffing recommendations. "I have that data and I can dig into it, but the amount of time it took to do that for one single unit you could not replicate unless you had a whole army of people," says Bruce Weinberg, Executive Director of Nursing Resource Management for Mercy Health System. Weinberg says Mercy is hitting that 97 percent accuracy rating.

Here's how Avantas' SAS solution works:

  • Avantas quickly and easily pulls in outside data from such sources as the Google Flu Index as part of model creation. It also factors in local events – such as home football games at a large university near a particular hospital.
  • Avantas staffers then create a unit forecast in about eight hours, rather than the 80 hours it took before SAS.
  • Hospital users have the information at their fingertips via a real-time, decision-support dashboard tool.
  • The SAS forecasts are fed into Avantas' Smart Square scheduling software. Available shifts are displayed so that only staff with the specific skill set can see them, resulting in optimal patient care.

Avantas' SAS solution has driven impressive results:

  • Nurse managers, who once spent 60 percent of their time on staffing issues, now spend less than half that and can focus more time on patient care.
  • Forecasting that anticipates needs proactively enables open shifts to be posted 30 days out; 70 percent of the spots are now filled more than two weeks before the shift.
  • Unit-staffing models are at least 20 percent more accurate than schedules built based on budgeted demand.
  • Shift bonus dollars are targeted more accurately. Hospital clients now know the highest-need shifts far in advance and can offer the right amount of supplemental pay to fill them promptly.
  • Nursing managers can decrease expenses by staffing more efficiently, which saves on overtime, contract-nursing costs and turnover. Units are also staffed appropriately, leading to a higher quality of care.

The forecasting ability Avantas provides customers by using SAS is a huge selling point to hospitals. "It's one of our sizzle points. We have multiple years of business intelligence experience and data that feed these models," Larson says. "The flexibility that SAS provides gives us the ability to make adjustments to the models. Immediately receiving updated forecasts is crucial for the 24/7, ever-changing health care environment."

Next steps

Avantas is now customizing its models to provide staff forecasting for surgery departments, emergency rooms, labs and large outpatient clinics. As part of the process, the company works collaboratively with hospital staff to capture the right data to build the models. SAS not only offered Avantas a product that could use its data, it provided domain experts through SAS Professional Services to get the most out of the solution. "Our models aren't run on just general data. It's very specific to the health care industry, and SAS experts supported us every step of the way," Larson says.

Ultimately, the forecasts go a long way to making the harried life of a health care manager a little easier. "It really gives them the peace of mind that they can see critical needs weeks in advance to proactively recruit the right staff, avoiding the last-minute chaos in staffing," Larson says. "There's a correlation between a satisfied staff and retention; there's a correlation between turnover and poor quality. With quality outcomes a critical component of the Affordable Care Act, these are increasingly important areas for hospitals to address."


Improve forecasting capabilities to accurately and quickly predict hospital staffing needs by unit.


SAS® Forecast Server


Forecasts are 97 percent accurate 30 days out – allowing customers (hospitals) to save on overtime, recruit the right staff mix for each shift and increase patient satisfaction. Nurse managers, who once spent 60 percent of their time on staffing issues, spend less than half that with the solution. Avantas employees can create a unit forecast in about eight hours versus the 80 hours it took before SAS.

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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