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Investigation of Information Overload in Electronic Health Records: Protocol for Usability Study

Investigation of Information Overload in Electronic Health Records: Protocol for Usability Study

CSUQ: Computer System Usability Questionnaire; ICU: intensive care unit; NASA-TLX: National Aeronautics and Space Administration–Task Load Index; Q and A: question and answer. A team of critical care physicians created 4 patient cases. Each patient was representative of a patient that could be hospitalized in an ICU setting. Of the 4 patients, 2 were considered basic or “standard” ICU patients while 2 were considered to be complex patients.

Saif Khairat, Jennifer Morelli, Marcella H Boynton, Thomas Bice, Jeffrey A Gold, Shannon S Carson

JMIR Res Protoc 2025;14:e66127

Using ChatGPT-4 to Create Structured Medical Notes From Audio Recordings of Physician-Patient Encounters: Comparative Study

Using ChatGPT-4 to Create Structured Medical Notes From Audio Recordings of Physician-Patient Encounters: Comparative Study

Despite this, there is a continued interest in whether Chat GPT-4 could serve as a freely available tool to assist as a documentation intermediary, bridging the gap between health care professionals and the tedious task of recordkeeping. However, it is imperative that prior to the widespread adoption of these tools, their safety and efficacy need to be evaluated in a structured and clinically contextually relevant manner.

Annessa Kernberg, Jeffrey A Gold, Vishnu Mohan

J Med Internet Res 2024;26:e54419

Using a New Model of Electronic Health Record Training to Reduce Physician Burnout: A Plan for Action

Using a New Model of Electronic Health Record Training to Reduce Physician Burnout: A Plan for Action

The emphasis on clinical workflow efficiency (a phenomenon that has seen a sharp increase in attention after the advent of the EHR) coupled with the increasing complexity of the medical record has led to an exponential increase in the amount of patient data recorded in the EHR.

Vishnu Mohan, Cort Garrison, Jeffrey A Gold

JMIR Med Inform 2021;9(9):e29374

Sex Differences in Electronic Health Record Navigation Strategies: Secondary Data Analysis

Sex Differences in Electronic Health Record Navigation Strategies: Secondary Data Analysis

We thus developed a novel variable—the Gaze Index (GI)—to denote the ratio of time spent in long fixation (“staring”) to time spent in saccadic motion (“scanning”). The GI represents the proportion of time each participant spent in fixation versus saccade. For example, a GI of 0.11 would indicate that a participant spent approximately 9 times more of their screen time in saccade-microfixation-saccade-etc (a “reading”/“scanning” pattern) than in full fixation (“staring”).

Daniel R Allen Seifer, Karess Mcgrath, Gretchen Scholl, Vishnu Mohan, Jeffrey A Gold

JMIR Hum Factors 2021;8(2):e25957

The Impact of Electronic Health Record–Based Simulation During Intern Boot Camp: Interventional Study

The Impact of Electronic Health Record–Based Simulation During Intern Boot Camp: Interventional Study

Through the use of eye and screen tracking, we have previously demonstrated that there is a lack of a standard approach to use the EHR concerning screen navigation, with only a very small subset of screens used universally by residents. This is associated with a decrease in the number of embedded safety items recognized within simulated EHR charts and subsequent massive variance in perceived diagnosis and plan [13-15].

Matthew E Allen Miller, Gretchen Scholl, Sky Corby, Vishnu Mohan, Jeffrey A Gold

JMIR Med Educ 2021;7(1):e25828

Use of Simulation Based on an Electronic Health Records Environment to Evaluate the Structure and Accuracy of Notes Generated by Medical Scribes: Proof-of-Concept Study

Use of Simulation Based on an Electronic Health Records Environment to Evaluate the Structure and Accuracy of Notes Generated by Medical Scribes: Proof-of-Concept Study

On the basis of the script of each scenario, agold-standard” note was created for each case to allow for assessment of accuracy of content of individual scribe notes. A list of all medical scribes was collected from the Scribe Program Supervisor of the OHSU medical scribing program. Medical scribes working at the OHSU Center for Women’s Health (CWH) were selected because they represented the largest proportion of all medical scribes working at OHSU.

Robert Allen Pranaat, Vishnu Mohan, Megan O'Reilly, Maxwell Hirsh, Karess McGrath, Gretchen Scholl, Deborah Woodcock, Jeffrey A Gold

JMIR Med Inform 2017;5(3):e30