The Impact of AI Scribes on Clinicians’ Electronic Health Record Time: Initial Results from the Multisite Ambient Clinical Documentation Collaborative
Time on the electronic health record (EHR) is associated with burnout among physicians. While human scribes have been shown to reduce EHR time, there are cost and person-power limitations to scaling their use. Given these limitations, healthcare organizations across the United States are now testing the ability of artificial intelligence-powered scribes to ease documentation burden while enhancing the clinician experience. The Ambient Clinical Documentation Collaborative is a consortium of healthcare organizations across the United States that have adopted AI scribes and use Epic Systems as their EHR. Sites include the Geisinger Health System, Emory Healthcare, Mass General Brigham, New York University, the University of California at San Francisco, the University of California at Davis, the University of California at San Diego, the University of Rochester, and Yale New Haven Health System/Yale Medicine. In this study of Collaborative participants, we describe the range of settings and ways in which AI scribes are being implemented, their impact on physicians’ EHR time, and the factors associated with significant time benefits of AI scribe technology. Our preliminary results suggest variability in the implementation of AI scribe technology across the large healthcare systems represented. AI scribes are most commonly being used in the outpatient setting, and early analyses suggest the benefits of AI scribe technology for reducing clinicians’ EHR time expenditure and improving documentation efficiency, with some variability across vendors. These results can guide clinical and information technology leaders in their AI scribe implementation approaches.
Learning Objectives
- Identify the impact of AI scribes on physicians’ EHR time.
Speaker
- Lisa Rotenstein, MD, MBA, MSc (UCSF)
Comparative Case Study on Implementing Generative AI in Medical Practices to Ease Documentative Overburden: A Sociotechnical Systems Perspective
This is a comparative case study of a live implementation of Generative AI solution in 5 medical practices. We shed new light on the impact of Generative AI on various aspects such as social structures, roles, organizational processes, and technical systems of medical practices. It is well known now that increasing documentation burden on physicians has led to medical errors, patient safety concerns, and physician burnout. This study investigates the adoption and implementation of a Generative AI based clinical documentation technology in medical practices over a span of 5 months. Our data consisted of interviews, participant observations, process documentation and mapping, tracking social interactions, and analyzing textual user feedback data. The results reveal a process framework that can be generalized across medical practices, categorizing changes into social, technical, organizational, and goals & outcomes. The implementation of Generative AI has led to both tangible and intangible benefits, including the creation of a new role of Scribe to provide human oversight of AI-generated clinical documentation. Resistance and apprehensions from practice staff have impacted implementation speed and decision-making. The study emphasizes the importance of considering social and organizational process changes in the adoption of new technologies and identifies role re-reforming and triadic co-creation as key concepts. The study also includes an entrepreneur’s and emerging technology product implementation team’s experiences of the co-creation with the medical practices. Overall, this research provides a processual framework to capture the nuances of the adoption and co-evolution of an emergent and uncertain technology.
Speaker
- Sri Ramesh Eevani, Doctorate in Business Administration (Healthfirst)
Learning Objectives
- At the conclusion of this presentation the learner will be able to gain insights on qualitative case study approach of Generative AI implementation at medical practices.
Clinician Personas for Ambient Artificial-Intelligence Scribing Documentation
Ambient documentation, also known as AI-based scribes, is being used by healthcare systems to address documentation burden. Understanding clinician phenotypes for ambient documentation would allow implementation teams to determine clinicians who would benefit from the technology. We will present personas for adoption of ambient documentation derived from interview and survey data of our ambient documentation users.
Learning Objectives
- Interpret qualitative feedback from clinicians regarding the use of AI scribing technology in clinical practice
Speaker
- Julie Wang, BS (Harvard Medical School)
Rejuvenating Clinician Wellbeing with Ambient Documentation
Mass General Brigham and Emory Healthcare both piloted ambient documentation, AI-assisted scribing, at their respective institutions. Preliminary results show statistically significant improvements in clinician burnout/wellbeing scores after 6 weeks of exposure to ambient documentation. Ambient documentation is a promising tool to rejuvenate clinician wellbeing at a time of high burnout in healthcare.
Learning Objectives
- Identify ambient documentation as a tool to address clinician burnout and understand lessons learned from large ambient documentation pilots.
Speaker
- Jacqueline You, MD (Mass General Brigham)
About CME/CNE Credit
The following information pertains to individual sessions included in the AMIA 2025 Clinical Informatics Conference On Demand product. A total of 16.75 CME/CNE credits may be earned if all sessions are completed.
Continuing Education Credit
Physicians
The American Medical Informatics Association is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.
The American Medical Informatics Association designates this online enduring material for 16.75 AMA PRA Category 1™ credits. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Claim credit no later than within two years of the release date or within one year of your purchase date, whichever is sooner.
ANNC Accreditation Statement
The American Medical Informatics Association is accredited as a provider of nursing continuing professional development by the American Nurses Credentialing Center's Commission on Accreditation.
- Nurse Planner (Content): Robin Austin, PhD, DNP, DC, RN, NI-BC, FAMIA, FAAN
- Approved Contact Hours: 16.75 participant maximum CME/CNE
ACHIPsTM
AMIA Health Informatics Certified ProfessionalsTM (ACHIPsTM) can earn 1 professional development unit (PDU) per contact hour.
ACHIPsTM may use CME/CNE certificates or the ACHIPsTM Recertification Log to report 2025 CIC sessions attended for ACHIPsTM Recertification.
Claim credit no later than within two years of the release date or within one year of your purchase date, whichever is sooner.