Thomas A Lasko1, David A Owens2, Daniel Fabbri1,3, Jonathan P Wanderer1,4, Julian Z Genkins5, Laurie L Novak1. 1. Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States. 2. Owen Graduate School of Management, Vanderbilt University, Nashville, Tennessee, United States. 3. Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, United States. 4. Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, Tennessee, United States. 5. Department of Medicine, University of California, San Francisco, San Francisco, California, United States.
Abstract
BACKGROUND: Suboptimal information display in electronic health records (EHRs) is a notorious pain point for users. Designing an effective display is difficult, due in part to the complex and varied nature of clinical practice. OBJECTIVE: This article aims to understand the goals, constraints, frustrations, and mental models of inpatient medical providers when accessing EHR data, to better inform the display of clinical information. METHODS: A multidisciplinary ethnographic study of inpatient medical providers. RESULTS: Our participants' primary goal was usually to assemble a clinical picture around a given question, under the constraints of time pressure and incomplete information. To do so, they tend to use a mental model of multiple layers of abstraction when thinking of patients and disease; they prefer immediate pattern recognition strategies for answering clinical questions, with breadth-first or depth-first search strategies used subsequently if needed; and they are sensitive to data relevance, completeness, and reliability when reading a record. CONCLUSION: These results conflict with the ubiquitous display design practice of separating data by type (test results, medications, notes, etc.), a mismatch that is known to encumber efficient mental processing by increasing both navigation burden and memory demands on users. A popular and obvious solution is to select or filter the data to display exactly what is presumed to be relevant to the clinical question, but this solution is both brittle and mistrusted by users. A less brittle approach that is more aligned with our users' mental model could use abstraction to summarize details instead of filtering to hide data. An abstraction-based approach could allow clinicians to more easily assemble a clinical picture, to use immediate pattern recognition strategies, and to adjust the level of displayed detail to their particular needs. It could also help the user notice unanticipated patterns and to fluidly shift attention as understanding evolves. Georg Thieme Verlag KG Stuttgart · New York.
BACKGROUND: Suboptimal information display in electronic health records (EHRs) is a notorious pain point for users. Designing an effective display is difficult, due in part to the complex and varied nature of clinical practice. OBJECTIVE: This article aims to understand the goals, constraints, frustrations, and mental models of inpatient medical providers when accessing EHR data, to better inform the display of clinical information. METHODS: A multidisciplinary ethnographic study of inpatient medical providers. RESULTS: Our participants' primary goal was usually to assemble a clinical picture around a given question, under the constraints of time pressure and incomplete information. To do so, they tend to use a mental model of multiple layers of abstraction when thinking of patients and disease; they prefer immediate pattern recognition strategies for answering clinical questions, with breadth-first or depth-first search strategies used subsequently if needed; and they are sensitive to data relevance, completeness, and reliability when reading a record. CONCLUSION: These results conflict with the ubiquitous display design practice of separating data by type (test results, medications, notes, etc.), a mismatch that is known to encumber efficient mental processing by increasing both navigation burden and memory demands on users. A popular and obvious solution is to select or filter the data to display exactly what is presumed to be relevant to the clinical question, but this solution is both brittle and mistrusted by users. A less brittle approach that is more aligned with our users' mental model could use abstraction to summarize details instead of filtering to hide data. An abstraction-based approach could allow clinicians to more easily assemble a clinical picture, to use immediate pattern recognition strategies, and to adjust the level of displayed detail to their particular needs. It could also help the user notice unanticipated patterns and to fluidly shift attention as understanding evolves. Georg Thieme Verlag KG Stuttgart · New York.
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