CarePortal: Designing a Clinician-Centered Dashboard for Wearable Data Analytics (Preprint)

UNSTRUCTURED Recent growth of electronic health (e-health) is unprecedented, especially after the COVID-19 pandemic. Within e-health, wearable technology is increasingly adopted since it can offer the remote monitoring of chronic and acute conditions in daily life environments. Wearable technology may be used to monitor and track key indicators of physical and psychological stress in daily life settings, providing helpful information for clinicians. One of the key challenges is to present the extensive wearable data to clinicians in an easily interpretable way for making informed decisions. The purpose of the presented research was to design a webapp dashboard, named CarePortal, for analytic visualizations of wearable data that are meaningful to clinicians. The study was divided into two main research objectives (ROs): (RO1) Understand the needs of clinicians regarding wearable data interpretation and visualization. (RO2) Develop a system architecture of a web app to visualize wearable data and related analytics. We used a wearable dataset collected from 116 adolescent participants who experienced trauma. For two weeks, participants wore a Microsoft Band that logged physiological sensor data such as Heart Rate (HR). A total of 834 days of heart rate data was collected. To design the CarePortal Dashboard, we employed a participatory design approach, interacting directly with clinicians (stakeholders) with backgrounds in clinical psychology and neuropsychology. A total of eight clinicians were recruited from Rhode Island Hospital and University of Massachusetts Memorial Health. The study involved five stages of participatory workshops and began with understanding the needs of clinicians. A User Experience Questionnaire (UEQ) survey was used at the end of the study to quantitatively evaluate the user experience. Physiological metrics such as daily and hourly maximum, minimum, average and standard deviation of HR and HR variability (HRV), along with HR-based activity levels were identified. The study investigated various data visualization graphing methods for wearable data including radar chart, stacked bar plot, scatter plot combined with line plot, simple bar plot, and box plot. We created a CarePortal dashboard after understanding clinicians needs. Results from our Workshops indicate that overall clinicians preferred aggregate information such as daily heart rate instead of continuous heart rate and want to see trends in the wearable sensor data over a period (e.g., days). In the UEQ survey, a score of 1.4 was received which indicated that CarePortal was exciting to use (Q5), a similar score was received indicating CarePortal was leading edge (Q8). On an average, clinicians reported that CarePortal was supportive and can be useful to make informed decisions.