Background Interactive data visualization and dashboards can be an effective way to explore meaningful patterns in large clinical data sets and to inform quality improvement initiatives. However, these interactive dashboards may have usability issues that undermine their effectiveness. These usability issues can be attributed to mismatched mental models between the designers and the users. Unfortunately, very few evaluation studies in visual analytics have specifically examined such mismatches between these two groups. Objectives We aimed to evaluate the usability of an interactive surgical dashboard and to seek opportunities for improvement. We also aimed to provide empirical evidence to demonstrate the mismatched mental models between the designers and the users of the dashboard. Methods An interactive dashboard was developed in a large congenital heart center. This dashboard provides real-time, interactive access to clinical outcomes data for the surgical program. A mixed-method, two-phase study was conducted to collect user feedback. A group of designers (N = 3) and a purposeful sample of users (N = 12) were recruited. The qualitative data were analyzed thematically. The dashboards were compared using the System Usability Scale (SUS) and qualitative data. Results The participating users gave an average SUS score of 82.9 on the new dashboard and 63.5 on the existing dashboard (p = 0.006). The participants achieved high task accuracy when using the new dashboard. The qualitative analysis revealed three opportunities for improvement. The data analysis and triangulation provided empirical evidence to the mismatched mental models. Conclusion We conducted a mixed-method usability study on an interactive surgical dashboard and identified areas of improvements. Our study design can be an effective and efficient way to evaluate visual analytics systems in health care. We encourage researchers and practitioners to conduct user-centered evaluation and implement education plans to mitigate potential usability challenges and increase user satisfaction and adoption.
Objective This study aimed to understand how a metaverse-based (virtual) workspace can be used to support the communication and collaboration in an academic health informatics lab. Materials and Methods A survey of lab members (n = 14) was analyzed according to a concurrent triangulation mixed methods design. The qualitative survey data were organized according to the Capability, Opportunity, Motivation, Behavior (COM-B) model and combined to generate personas that represent the overall types of lab members. Additionally, scheduled work hours were analyzed quantitatively to complement the findings of the survey feedback. Results Four personas, representative of different types of virtual workers, were developed using the survey responses. These personas reflected the wide variety of opinions about virtual work among the participants and helped to categorize the most common feedback. The Work Hours Schedule Sheet analysis showed the low number of possible collaboration opportunities that were utilized compared to the number available. Discussion We found that informal communication and co-location were not supported by the virtual workplace as we had originally planned. To solve this issue, we offer 3 design recommendations for those looking to implement their own virtual informatics lab. First, labs should establish common goals and norms for virtual workplace interactions. Second, labs should carefully plan the virtual space layout to maximize communication opportunities. Finally, labs should work with their platform of choice to address technical limitations for their lab members to improve user experience. Future work includes a formal, theory-guided experiment with consideration on ethical and behavioral impact.
Introduction Inpatient care coordinators (ICCs) in the United States play a critical role in case management and care transition. ICCs spend a large amount of time in chart review and documentation through electronic health record (EHR) systems. However, significant knowledge gaps exist regarding their workflow barriers and their use of health information technology (Health IT). Using only quantitative or quantitative methods does not provide a comprehensive picture about ICC’s workflow due to its complex and dynamic nature. This work aimed to address this gap by conducting a mixed-methods study to understand the workflow of ICCs and identifying challenges in care deliver and documentation activities. Methods The study adopted a concurrent triangulation design including qualitative interviews with 12 ICC staff members in the United States followed by extraction of their EHR event logs for one month. The qualitative interview data were analyzed thematically, and the log data were analyzed statistically. The results were triangulated and interpreted. Results Three major workflow barriers faced by ICCs were identified: long travel time, heavy documentation load, and suboptimal communication. The event logs provided empirical evidence to support the workflow barriers identified in the interviews, especially in travel time and documentation load. Discussion ICC workflow has several inefficiencies. The study generated four design considerations to develop a Health IT solution: Mobility, EHR integration, Team-based Communication, and User Adoption to improve workflow efficiency and care coordination. Using a mixed-methods approach is effective and efficient in collecting and analyzing clinical workflow.
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