Emerging Artificial intelligence (AI) technologies can help organizations create more value for their patients and communities by converting time-consuming, labor-intensive and often inefficient tasks and functions into actionable information to produce better outcomes. Forward-looking hospital and health system leaders see AI as perhaps the most effective path to a more productive, efficient and higher-performing health care organization. But realizing AI’s full potential will require work on many fronts. It will take a collective effort by senior executives, health IT, operations, finance, clinicians and employees and new expertise to successfully integrate AI into the daily management of a hospital or health system.
This AHA Center for Health Innovation, Market Insights report offers hospital and health system leaders an overview of the health care AI landscape, including the common use cases for AI in four broad areas: administrative, financial, operational and clinical. It’s clear from these examples that AI can create more intelligent processes and generate insights to deliver more effective, efficient and affordable health care.
The report also lists a sampling of vendors that sell, test and develop AI solutions and categorizes the market maturity of the highlighted solutions in these areas: generally are available now (green), being beta-tested at hospitals or health systems (yellow) or are still in development (red).
This AHA Center for Health Innovation, Market Insights report walks hospital and health system leaders through the why and how of successfully integrating AI-powered technologies into their care delivery operations to improve health outcomes and lower costs at each stage of the care cycle.
This AHA Center for Health Innovation, Market Insights report provides useful frameworks and tools for hospital and health system leaders to critically think about how AI may impact their workforce strategy and to successfully integrate AI technologies into their workforce and workflows.
AI Care Delivery Discussion Guide
AI’s potential to improve outcomes and lower costs in care delivery is too important to ignore. This discussion guide identifies issues and key strategic questions leaders should consider to successfully integrate AI-powered technologies into their care delivery operations.
AI Vendor Partner Selection Tips
To slice through the hype, executives need to know what questions to ask a potential vendor, whether it’s to assist with a homegrown AI project or outsource 100% of all AI projects. These questions will help vet a potential AI vendor and set up a partnership for success.
AI Workforce Discussion Guide
The increasing prevalence of AI in health care will have significant impacts on the workforce. This discussion guide will help leadership teams understand the implications of AI on workforce strategy and help ensure successful and effective integration into the workforce.
AI Scenario Planning For Health Care
The proliferation of AI in health care is well underway. One way to prepare today for a future with AI is to scenario plan. This document will guide you and your leadership team through what-if scenarios to help you visualize, ask questions and plan for an AI-enabled future.
AI's Potential to Personalize Medicine and Bring Back the Human Touch
Photo credit: Michael Balderas
On this AHA Center for Health Innovation podcast, Eric Topol, M.D., Founder and Director of the Scripps Research Translational Institute, talks about his new book “Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again” and shares his insights on how artificial intelligence has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment. By freeing physicians from the tasks that interfere with human connection, AI can create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard.
Imaging Data Science In Action
AI in clinical practice is rapidly developing and increasingly used by health care professionals to manage and analyze data. In this webinar, Amy Kotsenas, M.D., associate professor of radiology, Mayo Clinic; Arun Krishnaraj, M.D., associate professor of radiology and medical imaging, University of Virginia Health System; and Bibb Allen, M.D., CMO, ACR Data Science Institute, share how AI technology is used in their facilities. Tune in to hear about the successful use of AI in clinical quality improvement and learn what hospitals and health systems can gain from the "emerging use case" of AI in medical imaging.
What New Roles Will AI Create in Health Care?
Knows how AI works and can design AI models to perform tasks required at a hospital or health system.
Builds the AI models to perform the tasks required at a hospital or health system.
Sets the data governance policies around how data are collected and makes sure that staff protect the privacy and security of patients’ personal health information at a hospital or health system.
Curates, cleans, scrubs and structures data from a variety of internal and external sources into the system that feeds AI models with the data they need to perform the tasks required at a hospital or health system.
Builds the system that fuels the AI models with the data they need to perform the tasks required at a hospital or health system.
Leads the effort to explore potential opportunities, develop a cogent AI strategy and harness the necessary funding, professionals, technology and organizational resources to implement them.