3 Tips to Apply Predictive Analytics in the Surgical Setting
December 15, 2019 Tweet
We know patient anxiety can be reduced through direct time with a nurse, but we also know a nurse’s time can be limited if the surgical schedule does not accommodate the time required for thorough patient care.
Predictive analytics using artificial intelligence (AI) changes this by accurately predicting the amount of time a nurse needs with a patient as part of the surgical schedule to ensure care is deliberate and not rushed, according to Mary Pat Gilligan, DNP, RN, CNOR, NEA-BC.
Gilligan is associate vice president of perioperative services for HCA Healthcare and executive director of perioperative services at Mission Health in Ashville, NC. She oversees a new interventional AI platform tower that brings together previously separate surgical and procedural modalities for surgical, interventional, and cardiac procedures and offers the complete continuum of care using AI and real-time data.
The goal with applying AI in this setting is to improve communication, increase patient throughput, optimize staffing based on available beds and projected demand, and avoid or mitigate surgical and procedural delays.
Following the launch of this new AI platform earlier this year, Gilligan shares three tips for other perioperative nurse leaders:
Tip #1: Help your team understand the benefits of AI.
“Nurses miss their touch time with patients. AI does some of the critical data analysis to understand the unique variables that help us to individualize care,” Gilligan says. “Our AI platform also allows the nurse to communicate in real-time with all disciplines involved in the patient’s care.”
Tip #2: Know what your resources are and how to use them.
Work with a technology partner that has a healthy understanding of your work environment, including your patient population and the resources afforded to you, such as staffing and surgeon availability, Gilligan advises.
Tip #3: Build a multidisciplinary implementation team.
Applying AI in the perioperative setting creates a tool that takes into account all of the nuances within an interdisciplinary surgical team, including the anesthesia provider, nurse, surgeon, and surg tech, Gilligan shares. “The right team representing these roles is needed to plan and implement how AI can be leveraged to bring every team member’s knowledge together to optimize care delivery.”
Gilligan will be sharing her experiences with this AI launch at her education session titled, A.I. and Real-time Data Optimizes Periop Flow as part of the Leadership Summit March 28–April 1 in Anaheim, CA.