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Accepted for/Published in: JMIR Formative Research

Date Submitted: Feb 28, 2023
Open Peer Review Period: Feb 28, 2023 - Apr 25, 2023
Date Accepted: Sep 8, 2023
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Designing a Clinician-Centered Wearable Data Dashboard (CarePortal): Participatory Design Study

Sadhu S, Solanki D, Bric LAD, Nugent NR, Mankodiya K

Designing a Clinician-Centered Wearable Data Dashboard (CarePortal): Participatory Design Study

JMIR Form Res 2023;7:e46866

DOI: 10.2196/46866

PMID: 38051573

PMCID: 10731575

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

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

  • Shehjar Sadhu; 
  • Dhaval Solanki; 
  • Leslie Ann D Bric; 
  • Nicole R. Nugent; 
  • Kunal Mankodiya

ABSTRACT

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.


 Citation

Please cite as:

Sadhu S, Solanki D, Bric LAD, Nugent NR, Mankodiya K

Designing a Clinician-Centered Wearable Data Dashboard (CarePortal): Participatory Design Study

JMIR Form Res 2023;7:e46866

DOI: 10.2196/46866

PMID: 38051573

PMCID: 10731575

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