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Seriously ill pediatric patient, parent, and clinician perspectives on visualizing symptom data.

Publication ,  Journal Article
Vaughn, J; Kamkhoad, D; Shaw, RJ; Docherty, SL; Subramaniam, AP; Shah, N
Published in: J Am Med Inform Assoc
July 14, 2021

OBJECTIVE: This study examined the perspectives on the use of data visualizations and identified key features seriously ill children, their parents, and clinicians prefer to see when visualizing symptom data obtained from mobile health technologies (an Apple Watch and smartphone symptom app). MATERIALS AND METHODS: Children with serious illness and their parents were enrolled into a symptom monitoring study then a subset was interviewed for this study. A study team member created symptom data visualizations using the pediatric participant's mobile technology data. Semi-structured interviews were conducted with a convenience sample of participants (n = 14 children; n = 14 parents). In addition, a convenience sample of clinicians (n = 30) completed surveys. Pediatric and parent participants shared their preferences and perspectives on the symptom visualizations. RESULTS: We identified 3 themes from the pediatric and parent participant interviews: increased symptom awareness, communication, and interpretability of the symptom visualizations. Clinicians preferred pie charts and simple bar charts for their ease of interpretation and ability to be used as communication tools. Most clinicians would prefer to see symptom visualizations in the electronic health record. DISCUSSION: Mobile health tools offer a unique opportunity to obtain patient-generated health data. Effective, concise symptom visualizations can be used to synthesize key clinical information to inform clinical decisions and promote patient-clinician communication to enhance symptom management. CONCLUSIONS: Effectively visualizing complex mobile health data can enhance understanding of symptom dynamics and promote patient-clinician communication, leading to tailored personalized symptom management strategies.

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Published In

J Am Med Inform Assoc

DOI

EISSN

1527-974X

Publication Date

July 14, 2021

Volume

28

Issue

7

Start / End Page

1518 / 1525

Location

England

Related Subject Headings

  • Telemedicine
  • Surveys and Questionnaires
  • Parents
  • Medical Informatics
  • Humans
  • Electronic Health Records
  • Communication
  • Child
  • 46 Information and computing sciences
  • 42 Health sciences
 

Citation

APA
Chicago
ICMJE
MLA
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Vaughn, J., Kamkhoad, D., Shaw, R. J., Docherty, S. L., Subramaniam, A. P., & Shah, N. (2021). Seriously ill pediatric patient, parent, and clinician perspectives on visualizing symptom data. J Am Med Inform Assoc, 28(7), 1518–1525. https://doi.org/10.1093/jamia/ocab037
Vaughn, Jacqueline, Donruedee Kamkhoad, Ryan J. Shaw, Sharron L. Docherty, Arvind P. Subramaniam, and Nirmish Shah. “Seriously ill pediatric patient, parent, and clinician perspectives on visualizing symptom data.J Am Med Inform Assoc 28, no. 7 (July 14, 2021): 1518–25. https://doi.org/10.1093/jamia/ocab037.
Vaughn J, Kamkhoad D, Shaw RJ, Docherty SL, Subramaniam AP, Shah N. Seriously ill pediatric patient, parent, and clinician perspectives on visualizing symptom data. J Am Med Inform Assoc. 2021 Jul 14;28(7):1518–25.
Vaughn, Jacqueline, et al. “Seriously ill pediatric patient, parent, and clinician perspectives on visualizing symptom data.J Am Med Inform Assoc, vol. 28, no. 7, July 2021, pp. 1518–25. Pubmed, doi:10.1093/jamia/ocab037.
Vaughn J, Kamkhoad D, Shaw RJ, Docherty SL, Subramaniam AP, Shah N. Seriously ill pediatric patient, parent, and clinician perspectives on visualizing symptom data. J Am Med Inform Assoc. 2021 Jul 14;28(7):1518–1525.
Journal cover image

Published In

J Am Med Inform Assoc

DOI

EISSN

1527-974X

Publication Date

July 14, 2021

Volume

28

Issue

7

Start / End Page

1518 / 1525

Location

England

Related Subject Headings

  • Telemedicine
  • Surveys and Questionnaires
  • Parents
  • Medical Informatics
  • Humans
  • Electronic Health Records
  • Communication
  • Child
  • 46 Information and computing sciences
  • 42 Health sciences