Publications by authors named "Yik-Ki Jacob Wan"

2 Publications

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User interface approaches implemented with automated patient deterioration surveillance tools: protocol for a scoping review.

BMJ Open 2022 Jan 13;12(1):e055525. Epub 2022 Jan 13.

College of Pharmacy, Idaho State University, Pocatello, Idaho, USA

Introduction: Early identification of patients who may suffer from unexpected adverse events (eg, sepsis, sudden cardiac arrest) gives bedside staff valuable lead time to care for these patients appropriately. Consequently, many machine learning algorithms have been developed to predict adverse events. However, little research focuses on how these systems are implemented and how system design impacts clinicians' decisions or patient outcomes. This protocol outlines the steps to review the designs of these tools.

Methods And Analysis: We will use scoping review methods to explore how tools that leverage machine learning algorithms in predicting adverse events are designed to integrate into clinical practice. We will explore the types of user interfaces deployed, what information is displayed, and how clinical workflows are supported. Electronic sources include Medline, Embase, CINAHL Complete, Cochrane Library (including CENTRAL), and IEEE Xplore from 1 January 2009 to present. We will only review primary research articles that report findings from the implementation of patient deterioration surveillance tools for hospital clinicians. The articles must also include a description of the tool's user interface. Since our primary focus is on how the user interacts with automated tools driven by machine learning algorithms, electronic tools that do not extract data from clinical data documentation or recording systems such as an EHR or patient monitor, or otherwise require manual entry, will be excluded. Similarly, tools that do not synthesise information from more than one data variable will also be excluded. This review will be limited to English-language articles. Two reviewers will review the articles and extract the data. Findings from both researchers will be compared with minimise bias. The results will be quantified, synthesised and presented using appropriate formats.

Ethics And Dissemination: Ethics review is not required for this scoping review. Findings will be disseminated through peer-reviewed publications.
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January 2022

Interactive Visual Displays for Interpreting the Results of Clinical Trials: Formative Evaluation With Case Vignettes.

J Med Internet Res 2018 06 25;20(6):e10507. Epub 2018 Jun 25.

Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States.

Background: At the point of care, evidence from randomized controlled trials (RCTs) is underutilized in helping clinicians meet their information needs.

Objective: To design interactive visual displays to help clinicians interpret and compare the results of relevant RCTs for the management of a specific patient, and to conduct a formative evaluation with physicians comparing interactive visual versus narrative displays.

Methods: We followed a user-centered and iterative design process succeeded by development of information display prototypes as a Web-based application. We then used a within-subjects design with 20 participants (8 attendings and 12 residents) to evaluate the usability and problem-solving impact of the information displays. We compared subjects' perceptions of the interactive visual displays versus narrative abstracts.

Results: The resulting interactive visual displays present RCT results side-by-side according to the Population, Intervention, Comparison, and Outcome (PICO) framework. Study participants completed 19 usability tasks in 3 to 11 seconds with a success rate of 78% to 100%. Participants favored the interactive visual displays over narrative abstracts according to perceived efficiency, effectiveness, effort, user experience and preference (all P values <.001).

Conclusions: When interpreting and applying RCT findings to case vignettes, physicians preferred interactive graphical and PICO-framework-based information displays that enable direct comparison of the results from multiple RCTs compared to the traditional narrative and study-centered format. Future studies should investigate the use of interactive visual displays to support clinical decision making in care settings and their effect on clinician and patient outcomes.
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June 2018