How Predictive Analytics are Solving Staffing and Scheduling Challenges in an Increasingly Complex Healthcare Delivery Environment
July 14, 2017
Predictive analytics uses sophisticated computational techniques such as data mining, algorithms, and computer modeling to analyze past data and make predictions about future patient demand. Such forecasting technology has been in use for many years in other industries, such as manufacturing, transportation, and financial services, where it helps organizations save time and money through better resource management.
The same approach is being applied in healthcare scheduling and staffing, where major organizations around the country are seeing extremely high rates of predictive accuracy. Such strategic information can produce significant labor savings, considering that workforce staffing represents the single largest expense for healthcare organizations, accounting for more than half of operating budgets, according to Fitch Ratings.