Predictive analytics is a hot topic in healthcare these days.
IBM, for instance, created some buzz when it introduced its Watson-based Content and Predictive Analytics for Healthcare to help reduce hospital readmissions.
On the opposite end of the spectrum, Verizon Fraud Management for Healthcare uses predictive-modeling algorithms to identify potentially fraudulent claims in real-time and send them to case managers.
(Read an article about that from eWeek here.)
At Avantas we use predictive analytics in yet another way. Since 2004 we have been using the Avantas Predictive Model to forecast future volume levels. In 2011, we began expanding to other departments across the enterprise, such as women’s services.
The goal of the technology is to help better align staff resources throughout the scheduling and staffing process.
One of the things that differentiate the Avantas Predictive Model from other types of healthcare forecasting is that while it uses retrospective data (historical census) as one of its inputs, it is hardly a retrospective process. In addition to a unit’s historical census, dozens of indices are used to refine and enhance the prediction.
Mathematical models are run and compared for each unit with the most accurate being selected to predict the census volumes. The predictions automatically reflect needs within our labor management software, Smart Square®. It posts anticipated needs (open shifts) that staff members can pick up weeks before the actual shift. Hospital administrators can elect to implement flexible, proactive incentive programs to reward staff for picking up these high-need shifts in advance.
Avantas Predictive Analytics in the News
Staff Scheduling Tools Can Improve the Bottom Line Healthcare Finance News
Hospital Gets a Better Handle on Staffing Needs Healthcare Informatics
A Single Version of the Truth Takes a Whole Toolbox Health Leaders Media
Using predictive analytics to forecast volume helps managers align staff resources well in advance and eases the strains that are often encountered during the staffing and deployment process.
Additionally, the Avantas Predictive Model:
- Helps staff stay aligned to their FTEs (less FTE leakage/overtime)
- Results in less need for contingency and agency resources
- Results in fewer cancellations of core staff
These factors lead to improved clinical, financial and operational outcomes, reduced staffing costs, and increased staff satisfaction.
Feel free to email me at firstname.lastname@example.org if you have questions or want to share your thoughts.