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An AI Early Adopter Shares Lessons Learned with Healthcare IT News

Radiology

Clinicians at Yale New Haven Health – one of Aidoc’s first U.S. installation sites – have been at the forefront of healthcare AI adoption and research, making significant contributions to industry awareness and available evidence. 

One trailblazer, Melissa A. Davis, MD, Associate Professor of Radiology and Biomedical Imaging and Vice Chair for Imaging Informatics, Radiology and Biomedical Imaging, provided Healthcare IT News with an overview of how clinical AI evolved from a few use cases to various radiology workflows at Connecticut’s largest health system.

As Dr. Davis shared with the reporter: “These technologies are largely still new, so their impacts are not completely known. We wanted to be at the leading edge of that conversation.”

For health systems exploring enterprise-wide AI solutions, Dr. Davis outlined a few of the critical success factors witnessed at Yale New Haven Health when implementing Aidoc:

  • Assess your clinical needs and challenges. Identify the areas where AI can support objectives, such as workflow efficiency or improved communication.
  • Get buy-in from all relevant stakeholders. End users should be involved in selection as well as IT staff and administrators. 
  • Carefully evaluate AI vendors. In addition to data on how a solution performs, ask for case studies and references. 
  • Have a change management plan. Ongoing training and education is essential for adoption. 

Read the full interview with Dr. Davis and browse the Aidoc clinical study library for select research, including studies from Yale New Haven Health. 

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