Whether it’s sepsis detection, medical imaging analysis, readmission prediction, diagnostic coding or something else, two out of three physicians say that their organizations are already using health care augmented intelligence (AI)—commonly called artificial intelligence.
With the rapidly growing adoption of these AI tools in medicine, it is important that health care organizations set up a governance system to manage and guide how that technology will be used to help physicians, patients and others in the organization.
A big part of that is assessing what health care AI the organization already has in place and creating a framework for what will take priority when implementing new AI tools.
“These tools are exciting. They’re shiny. They’re new. It’s easy to get caught up in them. Now is the time to do this hard work to set ourselves up for success. It’s what is going to allow these tools to actually reach the potential that we hope that they will reach,” said Margaret Lozovatsky, MD, who is chief medical information officer and vice president of digital health innovations at the AMA.
Taking stock of what health care AI the organization uses provides an opportunity to catalog successes, identify future opportunities and ensure the organization is complying with all the applicable laws. A toolkit from the AMA provides guidance on how to go about surveying departments to see what AI is in use, identifies some common organizational priorities that AI solutions can help address and offers tools on how the organization can approach prioritizing which projects to tackle.
“The speed of technology’s innovation is always going to be different than our ability to utilize the technology and having this governance will allow us to keep up with that speed more easily,” Dr. Lozovatsky explained in an AMA interview.
The AMA STEPS Forward® toolkit, “Governance for Augmented Intelligence,” was developed in collaboration with Manatt Health, and is a comprehensive eight-step guide for health care systems to establish a governance framework to implement, manage and scale AI solutions.
The AMA defines AI as augmented intelligence to emphasize that AI’s role is to help health care professionals, not replace them. The foundational pillars of responsible AI adoption are:
- Establishing executive accountability and structure.
- Forming a working group to detail priorities, processes and policies.
- Assessing current policies.
- Developing AI policies.
- Defining project intake, vendor evaluation and assessment processes.
- Updating standard planning and implementation processes.
- Establishing an oversight and monitoring process.
- Supporting AI organizational readiness.
From AI implementation to EHR adoption and usability, the AMA is fighting to make technology work for physicians, ensuring that it is an asset to doctors—not a burden.
Prioritizing what AI to implement
When aligning the work with the practice’s strategic initiatives, Dr. Lozovatsky encouraged clinicians to look at what problem they are trying to solve, determine what they are trying to accomplish and to listen to others in the working group around them so that a multi-disciplinary group solves the problem together and learns from each other.
The toolkit outlines common organizational priorities that AI can help to address, including:
- Shifting to value-based care. Leverage AI-powered predictive analytics on patient data, health outcomes and more.
- Improving financial sustainability. Apply AI to automate billing, claims processing and more.
- Supporting workforce retention. Offer AI ambient clinical documentation to reduce administrative burden and cognitive load.
- Advancing health equity. Use AI tools to support real-time translation services.
- Focusing on patient-centered care. Launch AI-driven virtual health assistants to help patients find timely answers to key questions, such as billing and scheduling.
- Advancing population health management. Incorporate AI-powered remote patient monitoring tools.
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The toolkit also outlines two possible ways the AI governance working group members can go about assessing which AI projects should be prioritized:
- The Health Care Value Equation, a formula that allows an organization to compare quality of care to the cost of providing it.
- The 2x2 Decision-Making Matrix, a framework that can be used to help prioritize AI tools based on two factors—factors related to clinical impact and factors related to ease of implementation.
Find out how participants in the AMA Health System Member Program are using AI to make meaningful change.
In addition to fighting on the legislative front to help ensure that technology is an asset to physicians and not a burden, the AMA has developed advocacy principles (PDF) that address the development, deployment and use of health care AI, with particular emphasis on:
- Health care AI oversight.
- When and what to disclose to advance AI transparency.
- Generative AI policies and governance.
- Physician liability for use of AI-enabled technologies.
- AI data privacy and cybersecurity.
- Payer use of AI and automated decision-making systems.
Learn more with the AMA about the emerging landscape of health care AI. Also, explore how to apply AI to transform health care with the “AMA ChangeMedEd® Artificial Intelligence in Health Care Series.”
