From Experiment to Scaled Deployment: How Health Systems Can Leverage Tech and AI in Hospital Operations

Speakers

A man wearing glasses, a dark suit, a light shirt, and a patterned tie, smiling against a black background, ready to leverage technology and AI for innovative solutions.
Neal Patel, MD, MPH
Chief Information Officer, Vanderbilt University Medical Center
A person with curly gray hair and glasses, wearing a blue top and a silver necklace, smiles in front of a plain light background, embodying confidence to leverage technology and AI for future opportunities.
Bethany Daily, MHA
Executive Director, Perioperative Services and Healthcare Systems Engineering, Massachusetts General Hospital
A woman with shoulder-length blonde hair, wearing a black top and a gold necklace, smiles against a plain white background—reflecting confidence in leveraging technology and AI.
Ashley Walsh, MHA
Chief Revenue Officer, LeanTaaS

Summary

This webinar navigates the journey of health systems in adopting and scaling technology and AI in hospital operations, featuring leaders from Vanderbilt University Medical Center, Massachusetts General Hospital, and Loma Linda University Health. Discussions revolve around the critical role of leaders in decision-making around technology adoption, operational challenges like capacity constraints and staffing shortages, and AI’s current and potential impacts. Insights into the build vs. buy dilemma, considerations for evaluating technology vendors, and the shift towards digital transformation for clinical efficiency are shared. This discussion offers a glimpse into the future of healthcare operations, emphasizing actionable strategies for successful implementation and AI adoption.

Learning Objectives:

  • Time-to-value is the key in the build vs buy technology decision process.
  • AI should help digital transformation, not just digitization. The goal is to invest in tools that save meaningful time for clinicians.
  • When evaluating technology vendors, you need to understand the full life cycle of your data – where it is coming from, how it can be accessed and shared, and whether the technology can be easily accessed by the intended end user.

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