Background: Medical scribes have been utilized to reduce electronic health record (EHR) associated documentation burden. Although evidence suggests benefits to scribes, no large-scale studies have quantitatively evaluated scribe impact on physician documentation across clinical settings. This study aimed to evaluate the effect of scribes on physician EHR documentation behaviors and performance.
Methods: This retrospective cohort study used EHR audit log data from a large academic health system to evaluate clinical documentation for all ambulatory encounters between January 2014 and December 2019 to evaluate the effect of scribes on physician documentation behaviors. Scribe services were provided on a first-come, first-served basis on physician request. Based on a physician's scribe use, encounters were grouped into 3 categories: never using a scribe, prescribe (before scribe use), or using a scribe. Outcomes included chart closure time, the proportion of delinquent charts, and charts closed after-hours.
Results: Three hundred ninety-five physicians (23% scribe users) across 29 medical subspecialties, encompassing 1,132,487 encounters, were included in the analysis. At baseline, scribe users had higher chart closure time, delinquent charts, and after-hours documentation than physicians who never used scribes. Among scribe users, the difference in outcome measures postscribe compared with baseline varied, and using a scribe rarely resulted in outcome measures approaching a range similar to the performance levels of nonusing physicians. In addition, there was variability in outcome measures across medical specialties and within similar subspecialties.
Conclusion: Although scribes may improve documentation efficiency among some physicians, not all will improve EHR-related documentation practices. Different strategies may help to optimize documentation behaviors of physician-scribe dyads and maximize outcomes of scribe implementation.
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http://dx.doi.org/10.3122/jabfm.2023.230211R2 | DOI Listing |
Plast Reconstr Surg Glob Open
January 2025
Department of Computer Science, Johns Hopkins University, Baltimore, MD.
Artificial intelligence (AI) scribe applications in the healthcare community are in the early adoption phase and offer unprecedented efficiency for medical documentation. They typically use an application programming interface with a large language model (LLM), for example, generative pretrained transformer 4. They use automatic speech recognition on the physician-patient interaction, generating a full medical note for the encounter, together with a draft follow-up e-mail for the patient and, often, recommendations, all within seconds or minutes.
View Article and Find Full Text PDFFocus (Am Psychiatr Publ)
January 2025
Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania (Buckley, Gopalan); Department of Health Information Management, University of Pittsburgh, Pittsburgh, Pennsylvania (Wang).
Artificial intelligence (AI) scribes for clinical documentation are likely to be among the first AI tools to affect the day-to-day practice of psychiatry, yet many psychiatrists are unfamiliar with them. This article introduces psychiatrists to AI scribes, including their potential benefits and risks. AI scribes may enhance efficiency, reduce physician burnout, and improve patient-physician rapport by automating documentation processes.
View Article and Find Full Text PDFJ Am Med Inform Assoc
February 2025
Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, United States.
Objectives: To quantify utilization and impact on documentation time of a large language model-powered ambient artificial intelligence (AI) scribe.
Materials And Methods: This prospective quality improvement study was conducted at a large academic medical center with 45 physicians from 8 ambulatory disciplines over 3 months. Utilization and documentation times were derived from electronic health record (EHR) use measures.
J Am Med Inform Assoc
February 2025
Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, United States.
Objective: This study evaluates the pilot implementation of ambient AI scribe technology to assess physician perspectives on usability and the impact on physician burden and burnout.
Materials And Methods: This prospective quality improvement study was conducted at Stanford Health Care with 48 physicians over a 3-month period. Outcome measures included burden, burnout, usability, and perceived time savings.
Brain Res
December 2024
Department of Rehabilitation, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Rehabilitation, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China; Rehabilitation Physician Branch of Fujian Medical Doctor Association, Fuzhou 350005, China. Electronic address:
Objective: To investigate the impact of inspiratory muscle training on lung function and swallowing function in patients with dysphagia-induced aspiration following ischemic stroke and to evaluate the effectiveness of inspiratory muscle training on aspiration symptoms.
Methods: Fifty-eight inpatients with dysphagia-induced aspiration following ischemic stroke were selected and randomly divided into a control group (n = 29, conventional swallowing therapy) and a treatment group (n = 29, conventional swallowing therapy plus inspiratory muscle training). Both groups received conventional swallowing function training, including oral sensory training, oral motor training, airway safety protection training, and neuromuscular electrical stimulation therapy for 10-20 min per session, twice daily for 2 weeks.
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