Grand Rounds January 30, 2026: A Pragmatic Randomized Controlled Trial of Ambient Artificial Intelligence to Improve Health Practitioner Well-Being (Majid Afshar, MD, MS; Mary Ryan Baumann, PhD)

Speakers

Majid Afshar, MD, MS
Associate Professor
Director, Learning Health Systems
Departments of Medicine and Biostatistics & Medical Informatics
University of Wisconsin-Madison

Mary Ryan Baumann, PhD
Assistant Professor
Departments of Population Health Sciences and Biostatistics & Medical Informatics
University of Wisconsin-Madison

Keywords

Artificial Intelligence; Burnout; Provider Well-Being; Learning Health System

Key Points

  • Documentation in the Electronic Health Record (EHR) is a driver of clinician burnout; it can reduce their capacity to connect with patients during an appointment and spill over into daily life, i.e. “work outside of work.” The research team sought to assess whether the use of an ambient Artificial Intelligence (AI) scribe could improve clinician well-being by automating the documentation process.
  • The stepped-wedge, individually randomized trial took place over 24 weeks at UW Health. 66 providers across various specialties were randomized to receive access to ambient AI at Week 1, Week 7, or Week 13. The primary endpoint was physician well-being, measured by the Professional Fulfillment subscale and a burnout composite.
  • The research team found a 20% reduction in burnout and a trend towards improvement in professional fulfillment. These effects were sustained over the course of the trial. Use of the technology also decreased “work outside of work” by an average of 30 minutes and “time in notes” by 21 minutes.

Discussion Themes

Qualitative interviews found that patients of the clinicians in the trial appreciated the reduced computer interaction and felt that communication was clearer and more open.

The research team worked with the EHR company to develop a rubric for evaluating the AI-generated notes for accuracy, i.e. the presence of AI hallucinations or falsifications.

Following the trial’s success, UW Health scaled the project from 66 to over 600 licenses. An operational dashboard was developed for real-time monitoring of utilization and documentation metrics to ensure sustained performance and coding compliance.

Grand Rounds January 9, 2026: Pragmatic Care Embedded Randomization: Insights From the KP-VACCINATE Megatrial (Ankeet S. Bhatt, MD, MBA, ScM)

Speaker

Ankeet S. Bhatt, MD, MBA, ScM
Cardiologist, Kaiser Permanente San Francisco Medical Center
Research Scientist, Kaiser Permanente Northern California Division of Research
Assistant Professor, Kaiser Permanente Bernard J. Tyson School of Medicine
Adjunct Professor, Stanford University School of Medicine

Keywords

Vaccination; Learning Health System; Implementation Science; Nudges; Influenza; Cardiovascular

Key Points

  • Every year, influenza leads to over 500,000 deaths and 3-5 million severe cases globally. It increases the risk of cardiovascular (CV) events like myocardial infarction and heart failure. Though health guidelines strongly recommend annual influenza vaccination, rates remain suboptimal globally and persistent inequities exist. There’s an urgent need for novel, effective, and scalable strategies to improve influenza vaccination rates.
  • The KP-VACCINATE trial is one of the largest ever conducted, randomizing over 3.6 million patients in under 30 days. It included several pragmatic elements, such as coordination with existing vaccine promotion efforts; randomization performed by operational health system teams; and endpoint capture fully embedded in the electronic health record.
  • The study team assessed the effect of a cardiovascular-focused nudge communication on influenza vaccination rates and found that there was no effect. Despite the negative results, the trial establishes that pragmatic and rapid randomization of communication strategies is operationally feasible at scale with routine healthcare workflows in the US.

Discussion Themes

The study team targeted a larger-than-usual population in order to 1) demonstrate the feasibility of randomization within a large-scale health system, and 2) be well-powered for subgroup analyses that could help tailor future interventions.

Dr. Bhatt viewed the negative result as an illustration of the importance of design and context for interventions based in behavioral science, rather than an indication that nudges are ineffective.

Future directions may include involvement of the broader care team, with primary care providers and specialty providers playing a potentially critical role in nudging patients towards vaccine uptake.

Grand Rounds October 31, 2025: The LHS Shared Commitments — All Treats, No Tricks (Peter Margolis, MD, PhD; Sean C. Dowdy, MD, FACS, FACOG; Sarah Greene, MPH)

Speakers

Peter Margolis, MD, PhD
Adjunct Professor of Pediatrics
Stanford University School of Medicine
Emeritus Professor of Pediatrics
University of Cincinnati School of Medicine
Former Co-Director of the James M. Anderson Center for Health Systems Excellence
Cincinnati Children’s Hospital Medical Center

Sean C. Dowdy, MD, FACS, FACOG
Chief Value Officer
Robert D. and Patricia E. Kern Associate Dean for Practice Transformation
Professor, Division of Gynecologic Oncology
Mayo Clinic

Sarah Greene, MPH
Consultant and Senior Advisor
The National Academy of Medicine

Keywords

Learning Health System; Healthcare; Knowledge

Key Points

  • In service to the goal of establishing a Learning Health System (LHS), the National Academy of Medicine developed and shared a foundational set of shared commitments. These principles, published in 2024, sought to define a common cause for all healthcare workers.
  • To build on the concept of the shared commitments, consider the LHS from a systems perspective: not as a sum of its parts, but as the product of their interaction. Discussions around the feasibility of LHSs often center around individual parts, e.g. data and informatics, incentives, and culture; but an LHS succeeds when these pieces are built and interact as part of a whole.
  • So, what does a coherent system look like? A learning organization is an organization skilled at creating, acquiring, and transferring knowledge between parts and at modifying its behavior to reflect new knowledge and insights.
  • Turning an LHS from an idea to a lived reality involves intertwining infrastructure with an adaptive cycle, propelled by a defined population or system; methods for system change and learning; and measurement and evaluation.
  • The LHS is not intended as a single program or one-size-fits-all structure; it’s a system that learns at multiple levels of scale, from the individual level to the population level. Dr. Margolis shared an example of a patient-physician collaboration that resulted in an electronic health record (EHR)-integrated dosing algorithm utilized across the healthcare system.
  • The Kern Center at Mayo Clinic demonstrates how the shared commitments come to life within an organization over time. Founded 15 years ago, Kern brings together diverse experts who create and evaluate data-driven solutions that transform healthcare for patients, clinicians, and communities. It seeks to generate both clinical and practical knowledge, emphasizing practice impact over research.
  • Roughly 4 years ago, the Kern Center was experiencing an existential crisis; a suboptimal focus was negatively impacting on their reputation within the institution. They pivoted to deep practice engagement and a focus on defining and pursuing clinical practice priorities, and have become an essential piece of practice transformation. Resources like the Project Dashboard and HealthLocator are facilitating communication and the diffusion of practice impact.
  • Every organization faces a design challenge. Organizing in traditional ways means imposing resource constraints based on assumptions about who can contribute and how. When organizations prioritize the capacity for information to flow freely, however, their learning capacity expands; they can overcome constraints by leaning on the amount, quality, and diversity of expertise available to a network. To illustrate this, Dr. Margolis shared a few examples of LH network successes.
  • The approach to the LHS has changed and adapted since its inception. Ms. Greene shared 10 reasons they think it will endure, to serve as a high-level roadmap to bring organizational leaders to the table and to help distinguish it from other approaches for translating knowledge into action.

Discussion Themes

In its first decade, Kern was established as a research arm; while it was intended to be transformative, it wasn’t well-integrated with clinical practice. A hybrid model, rooted in research and practice, didn’t work either. Transitioning to a focus on practice only has allowed them to start doing transformative work.

The speakers discussed a couple of facets of patient engagement with LHSs. First, during startup, a community of patients, clinicians, researchers, and other stakeholders often work together to identify measures of success. Second, patients who enter LHSs are consented. However, there is always more work to be done in terms of engaging patients in a mutual exchange of information.

The pursuit of standardization can come into conflict with a system’s ability to innovate. Over time, Dr. Dowdy noted, he’s started giving more weight to the unique circumstances of each hospital and their pursuant need for freedom to innovate. They’ve started emphasizing standardized expectations, measured via the Mayo Clinic Value index, as opposed to standardized methods.

Grand Rounds September 5, 2025: The Non-Learning Health System (Robert Califf, MD)

Speaker

Robert Califf, MD
Instructor in Medicine
Duke University Medical Center
Former Commissioner of Food and Drugs

Keywords

Healthcare; Learning Health System; Evidence-Based Practices; Health Outcomes

Q&A

The following reflects key takeaways from a fireside chat with Dr. Robert Califf, in which he shared his perspective on the “non-learning” health system. For a comprehensive account of Dr. Califf’s insights, watch the recording.

What do you mean by the “non-learning” health system?

25 years ago, certain visionaries looked at the advancement of computing, electronic health records, and other digital data and noted that data could and should be used to improve healthcare delivery and, in turn, health outcomes.

But increasingly, the healthcare system in the United States is “learning” based on institutional financial outcomes as opposed to patient outcomes. That’s not to say it’s a zero-sum game—but efforts are being directed towards expensive technologies that offer marginal benefit (but deliver good economic returns) as opposed to primary care, prevention, and interventions that address basic risk factors.

How can we reshape those incentives?

If the goal is to optimize the longevity, well-being, and functionality of the American population, incentives within the healthcare system should be aligned with health outcomes.

Why has it been so difficult to integrate evidence-based practices into healthcare settings? And how can we begin to change that?

If we align health care systems’ incentives with health outcomes, they will figure out how to operationalize these practices. But if we assume the incentives will not be realigned in the near future, we will need to eke out areas of alignment with decision-makers, incremental improvements that are not so disruptive that they get squashed. And finally, we need to develop disruptive external systems to challenge health systems.

What tasks should this community focus on?

Keep working on pragmatic trials; show that interventions have practical applications. Keep developing the skills to communicate about your work to the public. And be prepared to put our system back together when it breaks.

Discussion Themes

Other discussion themes included the critical role of randomized trials and the potential role of AI in answering scientific questions; what the research community can learn from other industries; and anticipated changes to the healthcare system and research landscape.

May 15, 2020: Podcast for Dr. Robert Califf’s May 1 Grand Rounds Presentation Now Available

 
This discussion provides a deeper look into Dr. Califf’s keynote presentation, which kicked off the Grand Rounds Special Series: Advances at the Intersection of Digital Health, Electronic Health Records, and Pragmatic Clinical Trials.

In this episode, you will learn more about:

  • The state of the current healthcare delivery system
  • How the COVID-19 pandemic could influence change in the current system
  • Aspects of clinical research that have accelerated over the past several months
  • Access to digital technologies and adoption of electronic health records

Click on the recording below to listen to the podcast.

Want to hear more? View the full Grand Rounds presentation.

For alerts about new episodes, subscribe free on iTunes or SoundCloud.

Read the transcript.

Podcast May 1, 2020: Can the COVID-19 Crisis Lead to Reformation of the Evidence Generation Ecosystem? (Robert Califf, MD, MACC)

In this episode of the NIH Collaboratory Grand Rounds podcast, Dr. Lesley Curtis speaks with Dr. Robert Califf, Head of Strategy and Policy at Verily Life Sciences and Google Health about whether the COVID-19 crisis can lead to reformation of the current healthcare delivery system. This discussion follows Dr. Califf’s keynote presentation of a Grand Rounds Series titled Advances at the Intersection of Digital Health, Electronic Health Records, and Pragmatic Clinical Trials.

Click on the recording below to listen to the podcast.

Want to hear more? View the full Grand Rounds presentation.

For alerts about new episodes, subscribe free on Apple Podcasts or SoundCloud.

Read the transcript.

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May 31, 2019: Adapting Clinical Trial Design to Meet the Needs of Learning Health Systems (Harriette Van Spall, MD, MPH)

Speaker

Harriette G.C. Van Spall, MD, MPH, FRCPC
Associate Professor of Medicine
Department of Medicine, Division of Cardiology
Department of Health Research Methods, Evidence, and Impact
McMaster University
Population Health Research Institute

Topic

Adapting Clinical Trial Design to Meet the Needs of Learning Health Systems

Keywords

Learning health system; Pragmatic clinical trial; Patient-Centered Care Transitions in Heart Failure (PACT-HF); Heart failure; Stepped-wedge cluster trial

Key Points

  • Characteristics of a learning health system include:
    • Possessing a culture of knowledge and quality improvement
    • Encouraging research innovation by embedding research into clinical practice and generating knowledge at the point of care
    • Harnessing data from electronic health records and claims/administrative databases
    • Fostering trust between research and clinical teams
    • Engaging patients, clinicians, and key stakeholders
  • The Patient-Centered Care Transitions in Heart Failure (PACT-HF) trial evaluated the effectiveness of a group of transitional care services in patients hospitalized for HF within a publicly funded healthcare system.
  • Challenges of a learning health system include integrating care, intervention, and communications across silos; streamlining workflow; preventing “contamination” of usual care; and the limited interoperability of EHRs and slow updates to claims/administrative datasets.

Discussion Themes

Efficacy in explanatory randomized clinical trials (RCTs) does not equate to effectiveness in real-world settings.

Decisions about implementation of an intervention are not made “live”; you must wait until the study has ended, all the data are available for analysis, and analysis is complete before you can inform decision-maker partners about the risks and benefits of the intervention.

Read more about the PACT-HF study and results in JAMA Network (Van Spall et al. 2019)

Tags

#pctGR, @Collaboratory1