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- S59: Chart Notes on the Dusty Trail: Documentation Is the Work (Oral Presentations)
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11/10/2026 |
8:00 AM – 9:15 AM |
Cortez B
S59: Chart Notes on the Dusty Trail: Documentation Is the Work (Oral Presentations)
Presentation Type: Oral Presentations
Session Credits: 1.25
Exploring the Relationship Between the Objective and Subjective Natures of Excessive Documentation Burden: Comparing Nurse-Reported Perceptions of Time-Consuming Documentation to EHR Log File Measures
Presentation Type: Paper - Student
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2026 Symposium 25x5 Presentation
Presentation Time: 08:00 AM - 08:12 AM
Abstract Keywords: Documentation Burden, Qualitative Methods, Quantitative Methods
Programmatic Theme: Clinical Informatics
Excessive documentation burden (ExDocBurden) among clinicians is measured using subjective (e.g., surveys), and objective (e.g., electronic health record (EHR) log files) measures, with a common focus on time-spent documenting. To our knowledge, direct comparisons of subjective and objective time-spent measures have not been performed. We compared survey-based nurse-reported rankings of time-spent for several documentation types to durations of documentation quantified from nurses’ matched EHR log files. We found high alignment between survey and log file-derived rankings of time-spent in flowsheets, labs, and notes, and statistically significant discrepancies between rankings of time-spent in care plans, medication administration records, orders, and secure messaging. These results suggest that objective time-spent measures may have varying alignment with nurses’ perceptions of time-spent relative to other EHR documentation activities. Future work should seek to replicate and further investigate these relationships, and to understand the limitations of EHR log file-derived time-spent measures to guide burden reduction interventions.
Speaker(s):
Courtney Diamond, MA, MPhil
Columbia University
Author(s):
Courtney Diamond, MA, MPhil - Columbia University; Po-Yin Yen, PhD, RN - Washington University in St. Louis; Amy Finnegan, PhD, MPA - Columbia University; Jennifer Thate, PhD, RN - Siena University; Rosie Mugoya, PhD - Washington University of St. Louis; Hao Fan, MBBS - Washington University School of Medicine in St Louis; Sarah Rossetti, RN, PhD, FAAN, FACMI, FAMIA, FIAHSI - Columbia University Irving Medical Center;
Courtney Diamond, MA, MPhil - Columbia University
EHR Time Decreases Are Not Consistently Associated with Burnout Changes Among AI Scribe Users: A Multi-Site Study
Presentation Type: Podium Abstract
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2026 Symposium 25x5 Presentation
Presentation Time: 08:12 AM - 08:24 AM
Abstract Keywords: Documentation Burden, Usability, Real-World Evidence Generation, Artificial Intelligence
Programmatic Theme: Clinical Informatics
AI scribes are spreading rapidly, but how they improve clinician experience remains uncertain. In a multi-site study of physicians at two academic health systems, burnout scores improved significantly after adoption at both institutions. EHR efficiency outcomes, however, were small and inconsistent across sites. Changes in burnout were largely uncorrelated with EHR-time changes suggesting benefits extend beyond measurable time savings.
Speaker(s):
Erik Holbrook, MD
Mass General Brigham
Author(s):
Erik Holbrook, MD - Mass General Brigham; Christopher Toretsky, MPH - University of California, San Francisco; Michelle Frits, BA - Brigham and Women's Hospital; Christine Iannaccone, MPH - Brigham and Women's Hospital; Julia Adler-Milstein, PhD, FACMI - UCSF School of Medicine; Rebecca Mishuris, MD, MS, MPH - Mass General Brigham; Lisa Rotenstein, MD, MBA, MSc - UCSF;
Erik Holbrook, MD - Mass General Brigham
Care Through Charting: The Documentation Tension in AI-Enabled Learning Health Systems
Presentation Type: Podium Abstract
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2026 Symposium 25x5 Presentation
Presentation Time: 08:24 AM - 08:36 AM
Abstract Keywords: Documentation Burden, Human-computer Interaction, Surveys and Needs Analysis, Qualitative Methods, Workflow, Workforce Development
Programmatic Theme: Clinical Informatics
Clinical documentation in electronic health records (EHRs) functions within the sociotechnical infrastructure that shapes clinical work. Interviews with 24 healthcare professionals identified three themes: Commitment to Helping, Communication for Helping, and Management Constraints of Helping, revealing a tension that healthcare professionals experience in clinical documentation between care through charting and charting as interference. Findings highlight the need for AI-enabled documentation systems that preserve healthcare professionals’ values, professional identity, and patient-centered care.
Speaker(s):
Michael Cauley, PhD
Vanderbilt University Medical Center Department of Biomedical Informatics
Author(s):
Michael Cauley, PhD - Vanderbilt University Medical Center Department of Biomedical Informatics; Richard Boland, Jr., PhD - Department of Design & Innovation, Weatherhead School of Management; Corinne Coen, PhD - Organizational Behavior, Weatherhead School of Management; Rachael Miller, PharmD - Veterans Health Administration; Mollie Hobensack, PhD, RN, NI-BC - Vanderbilt University Medical Center; Benjamin Collins, MD - Vanderbilt University Medical Center; Jessica Ancker, MPH, PhD, FACMI - Vanderbilt University Medical Center; S. Trent Rosenbloom, MD, MPH, FACMI, FAMIA, FAAP - Vanderbilt University Medical Center Department of Biomedical Informatics;
Michael Cauley, PhD - Vanderbilt University Medical Center Department of Biomedical Informatics
Examine Clinicians’ Modification of Hedging Language in Ambient AI Documentation: A Comparative Study of AI Drafts and Final Notes
Presentation Type: Paper - Student
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2026 Symposium 25x5 Presentation
Presentation Time: 08:36 AM - 08:48 AM
Abstract Keywords: Artificial Intelligence, Quantitative Methods, Clinical Decision Support, Health Equity
Programmatic Theme: Clinical Informatics
Ambient AI documentation systems generate clinical note drafts that clinicians frequently revise before signing off into electronic health records, yet how these edits alter hedging language remains unclear. We conducted paired analysis of clinician-edited portions of ambient AI drafts and final notes to examine (1) whether these edits change the prevalence of hedging language, (2) whether these edits exhibit a systematic shift toward greater certainty or uncertainty, and (3) whether these changes in hedging prevalence and directionality differ by ambient AI vendors and clinical specialties. Among 62,811 paired note sections, hedging terms were more often introduced into previously non-hedged text than removed from previously hedged text, and post-edit text contained more hedging mentions than pre-edit text. Directionality analyses showed a significant overall tendency toward greater uncertainty in hedging-related replacement edits. Vendor and specialty analyses revealed substantial heterogeneity in hedging prevalence, pre-to-post changes in hedging mentions, and directionality.
Speaker(s):
Yiliang Zhou, PhD
University of California, Irvine
Author(s):
Yawen Guo, MISM - University of California - Irvine; Di Hu, Master of Science in Information Systems - University of California - Irvine; Emilie Chow, MD - University of California, Irvine; Steven Tam, MD - UC Irvine; Danielle Perret, MD - The University of California Irvine; Deepti Pandita, MD, FACP, FAMIA - University of California Irvine; Kai Zheng, PhD - University of California, Irvine; Sairam Sutari, MSHI - University of California, Irvine;
Yiliang Zhou, PhD - University of California, Irvine
Leveraging LLMs to Bridge Nursing Care Plan Documentation Gaps in the EHR
Presentation Type: Podium Abstract
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2026 Symposium 25x5 Presentation
Presentation Time: 08:48 AM - 09:00 AM
Abstract Keywords: Large Language Models (LLMs), Documentation Burden, Workflow, Artificial Intelligence
Programmatic Theme: Clinical Research Informatics
Nurses frequently re-enter patient data into care plans that is already recorded in EHR assessment flowsheets, creating redundant work. We investigate the feasibility of using LLMs to identify patient care activities included in care plans that are also captured in EHR assessment flowsheets. Our findings revealed a strong alignment, suggesting care plans could be automatically generated from existing EHR data. This would reduce repetitive documentation and allow nurses to focus more on direct patient care.
Speaker(s):
Rosie Mugoya, PhD
Washington University of St. Louis
Author(s):
Rosie Mugoya, PhD - Washington University of St. Louis; Hao Fan, MBBS - Washington University School of Medicine in St Louis; Mikie Rachman, RN, MSHI, NI-BC - Washington University in St. Louis; Po-Yin Yen, PhD, RN - Washington University in St. Louis;
Rosie Mugoya, PhD - Washington University of St. Louis
Clinical Notes Reveal Medical, Nursing, and Rehabilitation Terminology Gaps in Falls and Neonatal Intensive Care Unit Care
Presentation Type: Paper - Student
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Presentation Time: 09:00 AM - 09:12 AM
Abstract Keywords: Controlled Terminologies, Ontologies, and Vocabularies, Data Standards, Natural Language Processing, Information Extraction
Programmatic Theme: Clinical Informatics
Multiprofessional clinical notes contain clinically meaningful concepts often incompletely represented in standard terminology resources, limiting interoperability and secondary use. We analyzed 2,977 notes from two cohorts: 1) NICU patients who transitioned out of the hospital and 2) patients who experienced a fall that caused injury that were authored by five professions (RN, MD, PT, OT, SLP) across three institutions. 43,518 unique clinician-annotated concepts were extracted from free-text notes, canonicalized, and compared with concepts captured by cTAKES and present in UMLS and BioPortal. Remaining concepts were carried forward through sequential cleaning, including removal of numeric artifacts, anatomy dominant phrases and documentation-related phrasing effects. 15,736 concepts remained after cleaning. Residual concepts reflected clinically meaningful themes, particularly in mobility, functional safety, gait, motor development, feeding, and neonatal care coordination. These findings suggest important interdisciplinary and rehabilitation-relevant concepts remain underrepresented in standard terminology systems and may require targeted terminology expansion.
Speaker(s):
Prathamesh Bapat, Doctor of philosophy
University of Illinois Chicago
Author(s):
Prathamesh Bapat, PhD Student - University of Illinois Chicago; Emmy R. Maddy, BS - University of Illinois Chicago; Sukhwindar S. Ajimal, DO, MS - University of Illinois Chicago; Grace Anderson, MS CCC-SLP - Loyola University Medical Center; Jaewon Bae, PhD - University of Iowa College of Nursing; Vanessa M. Barbosa, RN - University of Illinois Chicago; Lauren Boyd, MD - Loyola University Chicago Stritch School of Medicine; Gina M Burke, OTR/L BCPR CHT - University of Iowa; David Chestek - University of Illinois at Chicago; Brianna J. Clarahan, DPT - University of Iowa; Elizabeth M. Cullen, PT - University of Iowa; Rachel A. Dawson, ARNP, CPNP-PC - University of Iowa; Aileen Eviota, PT, DPT, NCS - University of Illinois Chicago; Manisha Gore, MS MSLP - University of Iowa; Jessica L. Hansen, PT, DPT - University of Missouri; Kristi Haughey, MSN, RNC-NIC - University of Iowa; Lindsey Knake, MD, MS - The University of Iowa Carver College of Medicine; Haleh Vatani - UIC; Karen Dunn Lopez, PhD, MPH, RN, FAAN - University of Iowa College of Nursing; Catherine Craven, PhD, MA, MLS, FAMIA - Dell Medical School, UT Austin;
Prathamesh Bapat, Doctor of philosophy - University of Illinois Chicago
S59: Chart Notes on the Dusty Trail: Documentation Is the Work (Oral Presentations)
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