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Health care AI is no longer theoretical. It’s totally practical.

. 5 MIN READ
By
Timothy M. Smith , Contributing News Writer

AMA News Wire

Health care AI is no longer theoretical. It’s totally practical.

Sep 19, 2024

It’s happening. Augmented intelligence (AI), often called artificial intelligence, is already at the point in its clinical application that it is transforming care.

Indeed, the list of its accomplishments is by now a long one. AI is easing the documentation burden, providing seamless access to test results, helping with monitoring and treatment, improving diagnostic and prognostic capability, empowering patients’ decision-making, providing personalized reminders and instructions, streamlining patient scheduling and generally freeing up physicians to focus more on patients.

Making technology work for physicians

The AMA is working to make sure technology is an asset to physicians—not a burden.

Physicians appreciate its potential too. An AMA survey of more than 1,000 doctors found that nearly two-thirds can see AI’s potential benefits.

An AMA Ed Hub™ CME series introduces learners to foundational principles in AI and machine learning, a subdomain of AI that enables computers to learn patterns and relationships from data without being explicitly programmed by people. Developed by the AMA ChangeMedEd initiative and the University of Michigan DATA-MD team and geared toward medical students, it is also suitable for residents, fellows, practicing physicians and other health professionals.

The fourth module in the series, “Practical Applications of AI in the Health System,” explores the potential impact of AI on clinical practice, research and education. It also identifies the various health care AI stakeholders and outlines key considerations when implementing AI algorithms into clinical practice.

From AI implementation to EHR adoption and usability, the AMA is making technology work for physicians, ensuring that it is an asset to doctors—not a burden.

“Clinician roles in health care are evolving due to the integration of Al with a shift from bidirectional,” meaning between patients and the health care team, “to a more complex tridirectional interaction that actively involves Al, empowers patients and requires clinicians to adapt to this evolving landscape,” the module notes.

Using machine-learning models, physician practices can now analyze vast amounts of patient data and make quicker and more accurate diagnoses and prognoses, which can help them detect diseases at earlier stages. This, in turn, can lead to better treatment options and patient outcomes. They can also get evidence-based insights and personalized treatment recommendations.

“This augmented intelligence empowers health care professionals and patients to make data-driven, evidence-based, patient-centered decisions, leading to more precise and tailored patient care plans,” the module says. “Additionally, stakeholders can use Al to automate routine tasks and administrative processes, freeing up clinicians' time and allowing them to focus on complex patient interactions and critical medical decisions.”

Learn more with the AMA about the emerging landscape of augmented intelligence in health care (PDF). 

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The module also explores how AI can aid in clinical trial design and patient identification, public health and drug discovery.

“The health care system has many inefficiencies and deficiencies leading to challenges in clinical research,” the module says. “Fortunately, researchers have found a valuable ally in Al through its data-driven insights and advanced algorithms, propelling health care toward more targeted and efficient approaches.”

Clinical trials take a lot of time, and they cost a lot too, the module notes.

“Al has the potential to help researchers address this challenge,” it says. “In clinical trial design and patient identification, researchers utilize Al algorithms to analyze vast amounts of patient data, helping them design more efficient and personalized clinical trials. By using Al to identify eligible patients based on specific criteria, researchers streamline the recruitment of participants, saving time and resources while ensuring trials are better suited to individual patient needs. This approach improves the chances of successful outcomes and facilitates the development of targeted therapies.”

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“Health care professionals must undergo ongoing training to use Al-based tools in clinical practice effectively,” the module says. “This training should span all stages of education, from undergraduate and graduate studies to ongoing professional development.”

In fact, any educational program should integrate training in Al to prepare learners to engage with Al responsibly and navigate its challenges in clinical settings. Moreover, interprofessional and multidisciplinary training is necessary to help physicians use Al tools collaboratively.

The module identifies five core areas of competence for physicians:

  • Foundational knowledge, including development, evaluation and regulatory issues. The physician should ask: What is this tool?
  • Critical appraisal, which looks at evidence, benefits, limitations and appropriate uses of Al tools. The key question is: Why should I use this tool?
  • Incorporating Al outputs into clinical decision-making to enhance effectiveness, value and fairness: When and where should I use this tool?
  • Technical use to maintain patient-clinician relationships: How should I use this tool?
  • Addressing unintended consequences by recognizing and mitigating potential adverse effects of Al tools: What are the side effects of this tool, and how should I manage them?

Getting up to speed on AI is not, however, a one-time endeavor.

“Health care professionals need training throughout their careers to effectively engage AI,” the module says.

Periodic knowledge checks test the user’s understanding of how concepts are applied.

The CME module “Practical Applications of AI in the Health System” is enduring material and designated by the AMA for a maximum of 0.75 AMA PRA Category 1 Credit™.

It is part of the AMA EdHub, an online platform with high-quality CME and education that supports the professional development needs of physicians and other health professionals. With topics relevant to you, it also offers an easy, streamlined way to find, take, track and report educational activities.

Learn more about AMA CME accreditation.

Making technology work for physicians

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