New research from HIMSS Media shows how healthcare organizations are turning to AI to keep up with the growing complexities of healthcare. Key finding: 75% of industry leaders reported that AI/ML will be a greater focus next year, but only 40% rated their current predictive or prescriptive analytics as extremely or very effective.
Why the disparity? Healthcare organizations recognize AI’s potential for both clinical and operational use cases, but barriers to success are multiple and diverse.
Read, “The Convergence of Data Analytics and Artificial Intelligence (AI) in Healthcare,” to discover:
- The top barriers to effectively applying data to predict trends and/or prescribe actions
- Three principles to overcome the complexity associated with AI initiatives
- Where to immediately focus your AI efforts for measurable results
The age of AI has arrived in healthcare. Read the report to find out how you can start implementing this new technology.
“The thing that really excites us is when we see customers begin with basic analytics, move into the realm of AI with predictive and prescriptive analytics, and as a result drive measurable value that impacts the lives of real people. Nothing builds confidence like success.”
— Andy Dé, "The Convergence of Data Analytics and Artificial Intelligence (AI) in Healthcare,” HIMSS Media