Scheduling and shift recruitment are critical to driving revenue and staff retention, but most solutions require too much manual intervention and often create even more work and less capacity.

New technologies leveraging AI and machine learning are moving quickly to revolutionize these processes across the healthcare landscape. Nida Al-Ramahi, Executive Director of Operations at Mercy, is currently leading the vision to decrease manual workflows, reactionary scheduling, and incentive program utilization across Mercy’s 40+ hospitals.

In this webinar we will review the technology and strategies that have enabled Mercy to build a comprehensive clinical workforce management approach that drives better financial, clinical, and organizational value across its entire nursing, ancillary, and support services staff — ultimately cutting their travel agency spend in half and driving savings of $30.7 million in premium labor.

Outlining:

• The creation of workforce layers in a tech environment to manage the entire scheduling workload and output strategic operational insights of real-time staffing metrics to ensure every unit is safely staffed.
• Adopting new technology leveraging predictive analytics to power shift insights and automate staffing of the clinical workforce.
• Using AI to set hourly shift rates based on market demand and past performance to control labor costs while meeting healthcare staffing demands.
• Process in building toward a vision of a unified clinical nursing workforce across inpatient, outpatient, post-acute settings.

Delivering world class care extends beyond the intricacies of operating healthcare institutions, but new operational technologies that save nurse managers hundreds of hours spent in spreadsheets and decreasing operational burden, are emerging as the biggest drivers of true transformation.