THE NEED: STAFFING OPTIMIZATION

Providence, like many healthcare networks, struggles to efficiently, and cost effectively staff the hospital floors.  A shortage of employees, cost cutting, and unpredictable priorities leads to a stressful environment, low morale for the employees and ultimately inadequate care for the patients. This project AV was intended to create a MVP staffing optimization platform utilizing both public and propriety data to model better staffing schedules to build better and more efficient experiences for both the administration and the staff.

 

THE RESULT: DATA-DRIVEN SOLUTIONS
The MVP we created utilized the data models that the data science team created via machine learning to proactively predict and balance the floor. The insights and reports generated helped the real users, nurse managers and administrative employees understand future schedules and volume. Additionally it also helped senior management and administration to fully understand the state of real time staffing within a hospital as well as comparatively across the healthcare network.  The data visualizations created were critical in getting a read on the real time experience and help the users better predict and mitigate staff shortages. All this in an effort to raise morale, create a better employee, cost savings and patient satisfaction.