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Jeffery AD, Reale C, Faiman J, Borkowski V, Beebe R, Matheny ME, Anders S. Inpatient nurses' preferences and decisions with risk information visualization. J Am Med Inform Assoc 2023; 31:61-69. [PMID: 37903375 PMCID: PMC10746300 DOI: 10.1093/jamia/ocad209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 09/10/2023] [Accepted: 10/09/2023] [Indexed: 11/01/2023] Open
Abstract
OBJECTIVE We examined the influence of 4 different risk information formats on inpatient nurses' preferences and decisions with an acute clinical deterioration decision-support system. MATERIALS AND METHODS We conducted a comparative usability evaluation in which participants provided responses to multiple user interface options in a simulated setting. We collected qualitative data using think aloud methods. We collected quantitative data by asking participants which action they would perform after each time point in 3 different patient scenarios. RESULTS More participants (n = 6) preferred the probability format over relative risk ratios (n = 2), absolute differences (n = 2), and number of persons out of 100 (n = 0). Participants liked average lines, having a trend graph to supplement the risk estimate, and consistent colors between trend graphs and possible actions. Participants did not like too much text information or the presence of confidence intervals. From a decision-making perspective, use of the probability format was associated with greater concordance in actions taken by participants compared to the other 3 risk information formats. DISCUSSION By focusing on nurses' preferences and decisions with several risk information display formats and collecting both qualitative and quantitative data, we have provided meaningful insights for the design of clinical decision-support systems containing complex quantitative information. CONCLUSION This study adds to our knowledge of presenting risk information to nurses within clinical decision-support systems. We encourage those developing risk-based systems for inpatient nurses to consider expressing risk in a probability format and include a graph (with average line) to display the patient's recent trends.
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Affiliation(s)
- Alvin D Jeffery
- School of Nursing, Vanderbilt University, Nashville, TN 37240, United States
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States
- Tennessee Valley Healthcare System, United States Department of Veterans Affairs, Nashville, TN 37212, United States
| | - Carrie Reale
- Center for Research and Innovation in Systems Safety, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Janelle Faiman
- Center for Research and Innovation in Systems Safety, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Vera Borkowski
- School of Nursing, Vanderbilt University, Nashville, TN 37240, United States
| | - Russ Beebe
- Center for Research and Innovation in Systems Safety, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Michael E Matheny
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States
- Tennessee Valley Healthcare System, United States Department of Veterans Affairs, Nashville, TN 37212, United States
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Shilo Anders
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States
- Center for Research and Innovation in Systems Safety, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN 37232, United States
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