Avantas revolutionizes healthcare forecasting

Avantas helps hospitals accurately forecast staffing needs so that they can spend more time on patients and less time staffing their units. Its service helps hospitals reduce dependence on contract nurses and limit last-minute schedule changes. Not only can clients save money and improve morale, they can target bonus dollars to the hardest shifts to fill.

Prior it took three to four weeks to generate forecasts. "We'd pull data from SPSS, paste it into Excel – over and over again. It was manual and time-consuming. We could only update a forecast when something changed,'' explains Julie Kiefer, Manager of Analytics at Avantas. "We wanted to automate our forecasts to provide our clients with a proactive solution." The company also wanted to expand, but couldn't without either hiring additional staff or making forecasting more efficient. 

Avantas liked the ability of SAS to handle hundreds of models and automate the process. "Other solutions required more hands-on work. SAS can incorporate hundreds of different models, allowing us to create a custom forecasting methodology, which is very important because every hospital department behaves differently,'' Kiefer says. Among Avantas' successes using SAS Forecast Server: 

  • Hospitals have information at their fingertips via a real-time decision support dashboard.
  • Nurse managers who spent 60 percent of their time on staffing now spend less than half that.
  • Shift bonus dollars are accurately targeted. Hospital clients know high-need shifts far in advance and can offer the right supplement pay to fill them promptly.
  • Nurse managers can decrease expenses by staffing more efficiently saving on overtime, contract nursing costs and nursing turnover.
  • Units are staffed appropriately leading to a higher quality of care.
  • Avantas has grown business five-fold without adding staff in the forecasting area.
  • Avantas staffers can create a unit forecast in about eight hours vs. 80 hours before using SAS.
  • Unit staffing model accuracy has increased 13 percent at 30 days out. Accuracy improves dramatically closer to shift dates. 

SAS not only enabled Avantas to harness its information, it provided domain experts to get the most out of the solution. "Our models are very specific to the healthcare industry and SAS experts supported us every step of the way,'' said Michelle Krapfl, Vice President of Operations, Avantas. 

Most importantly, the forecasts make the harried life of a nurse manager a little easier. "It gives them peace of mind to see critical needs weeks in advance and recruit the right staff, avoiding last minute staffing chaos,'' Krapfl says. "Nurses want to focus on patient care, not scheduling."

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