AI for Primary Care: Electronic Scribes and More

The "AI for Primary Care: Electronic Scribes and More" workshop invites healthcare professionals, AI researchers, and technology developers to explore the pioneering intersection of artificial intelligence (AI) and clinical scribing. With a rich legacy spanning from Florence Nightingale's emphasis on incorporating diagnoses and treatment plans into clinical notes in the 19th century to Dr. Lawrence Weed's introduction of the SOAP format in 1968, clinical documentation stands at the cusp of a new era. These historical milestones underscore the long-standing commitment to improving patient care through meticulous record-keeping and informed decision-making.

Today, as we stand on the brink of another transformative phase, propelled by AI technologies, this workshop aims to continue that tradition of innovation and excellence. By integrating AI, we aim to enrich patient care and streamline healthcare provider workflows through enhanced clinical documentation.

This workshop is dedicated to showcasing innovative AI applications that automate and enhance the scribing process. Participants will delve into how AI-driven tools can accurately capture patient narratives, interpret clinical signs, assist in diagnostic processes, and recommend treatment plans. The goal is to explore how AI can augment the accuracy, efficiency, and comprehensiveness of clinical notes, thereby improving patient care and healthcare provider workflows.

Key themes include the application of natural language processing (NLP) to interpret subjective symptoms and objective clinical signs, machine learning algorithms for assisting with assessments and differential diagnoses, and AI-driven decision support systems for planning treatments and investigations. The workshop will highlight cutting-edge research, case studies, and pilot projects that demonstrate the potential of AI to revolutionize primary care documentation, making it more reflective, predictive, and personalized.

By facilitating discussions on the challenges and opportunities of integrating AI into clinical scribing, this workshop aims to foster collaboration among clinicians, AI technologists, and policy makers. Attendees will gain insights into the latest advancements and the future trajectory of AI in enhancing the quality and efficiency of healthcare documentation and delivery.

SCOPE

We welcome submissions on a variety of AI methodologies, including but not limited to deep learning, neural networks, and generative models, with a special interest in how these technologies can be tailored to fit the unique demands of primary care settings. This workshop is not just a forum for presenting research but a crucible for generating innovative ideas and forming partnerships that will lead the charge toward a new horizon in healthcare.

TOPICS

AI technologies in Scribing: A deep dive into how different AI technologies, including NLP, deep learning, and neural networks, are transforming the scribing process in primary care	Personalization of primary care through AI
Improving patient-reported narratives with AI: Techniques and tools for leveraging AI to capture patient narratives more accurately and comprehensively	Challenges and opportunities in AI-enhanced scribing
Objective clinical sign interpretation through AI: Showcasing AI's capability to interpret objective clinical signs, improving diagnostics and treatment accuracy. Some modalities can use image or video recognition to transcribe signs	Case studies, pilot projects, and software or clinical flow demonstrations
AI-assisted diagnostic processes	Future directions for AI in healthcare documentation
AI in treatment planning and recommendations

PROGRAM FORMAT

Time	Format	Topic	Speakers
1:30 - 1:35 pm	Podium Presentation	Welcome Address	TBN
1:35 - 2:15 pm	Podium Presentation	Keynote: AI for Primary Care	Caroline R. Richardson
2:15 - 2:45 pm	Rising Star Research Presentation	Evaluating an LLM for Translating Patient Instructions	Daniel Kats
2:45 - 3:05 pm	Research Presentation	Document-level Clinical Information Extraction with Bayesian Networks and Neural Text Classifiers	Paloma Rabaey
3:05 - 3:25 pm	Research Presentation	Machine Learning Analysis of Vocal Characteristics Able to Detect Moderate to Severe Depression	Prentice Tom
3:25 - 3:45 pm	Coffee Break
3:45 - 4:05 pm	Research Presentation	Lessons Learned Post-Implementation of an Artificial Intelligence-Powered Retinal Screening Camera at an Academic Family Medicine Clinic	Ariel Leifer
4:05 - 4:25 pm	Research Presentation	Preliminary Findings and Insights from the UI Health Generative AI in-basket Pilot	Awais Farooq
4:25 - 4:45 pm	Research Presentation	From Patient Homes to the Clinic and Communities: Using AI to Improve Outcomes for Patients in Primary Care	Anthony Sunjaya
4:45 - 5:15 pm	Podium Talk	Closing Keynote	Yves Lussier and JT Menchaca