Predictive Analytics for Capacity Planning: All Forecasts are Not Created Equal
The use of predictive analytics to manage healthcare provider capacity is one of the newest applications of this powerful tool. Faced with unprecedented pressure to produce better outcomes at a lower cost, healthcare organizations must figure out how to achieve sustainable cost reductions exceeding 20% across their system, while improving quality, safety and outcomes. With labor costs typically comprising up to 60% of total expenses, one of the best ways to reduce operating costs is to align staffing and capacity to predicted patient demand.
Whether a healthcare system is experiencing variable, declining, steady or increasing volumes, rightsizing staffing to demand is critical to operational performance.
Because patient demand forecasting is so new, few organizations have sufficient exposure to full-spectrum systems to rank various offerings in terms of the value they deliver. If you’ve never had anything to work with but annual budget staffing ratios, even a static forecast that predicts census over the next few weeks or months may seem like a big improvement. Granted, it’s better than no forecast at all.
However, if your goal is to sustainably reduce operating expenses by transforming how you allocate staff and resources, you need to understand the full spectrum of forecasting power that it will take – and discern the difference between vendor claims and reality.
This guide will show you what to look for. (Click here to download the full PDF)
Be the first to comment on this!
Personal Subscriber? Sign In
Note: Please enter a display name. Your email address will not be publically displayed