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Common Barriers to the Use of Patient-Generated Data Across Clinical Settings

Authors:

Richard Giordano,

Nigel ShadboltAuthors Info & Claims

CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

Paper No.: 484, Pages 1 - 13

https://doi.org/10.1145/3173574.3174058

Published: 21 April 2018 Publication History

Abstract

Patient-generated data, such as data from wearable fitness trackers and smartphone apps, are viewed as a valuable information source towards personalised healthcare. However, studies in specific clinical settings have revealed diverse barriers to their effective use. In this paper, we address the following question: are there barriers prevalent across distinct workflows in clinical settings to using patient-generated data? We conducted a two-part investigation: a literature review of studies identifying such barriers; and interviews with clinical specialists across multiple roles, including emergency care, cardiology, mental health, and general practice. We identify common barriers in a six-stage workflow model of aligning patient and clinician objectives, judging data quality, evaluating data utility, rearranging data into a clinical format, interpreting data, and deciding on a plan or action. This workflow establishes common ground for HCI practitioners and researchers to explore solutions to improving the use of patient-generated data in clinical practices.

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Index Terms

Common Barriers to the Use of Patient-Generated Data Across Clinical Settings
1. Applied computing
  1. Life and medical sciences
2. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

April 2018

8489 pages

ISBN:9781450356206

DOI:10.1145/3173574

General Chairs:
Regan Mandryk
University of Saskatchewan, Canada
,
Mark Hancock
University of Waterloo, Canada
,
Program Chairs:
Mark Perry
Brunel University London, UK
,
Anna Cox
University College London, UK

Copyright © 2018 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Published: 21 April 2018

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CHI '18 Paper Acceptance Rate 666 of 2,590 submissions, 26%;

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https://doi.org/10.4018/979-8-3693-9631-5.ch005
Staehelin DDolata MStöckli LSchwabe G(2024)How Patient-generated Data Enhances Patient-Provider Communication in Chronic Care: A Field Study in Design Science Research (Preprint)JMIR Medical Informatics10.2196/57406Online publication date: 16-Feb-2024
https://doi.org/10.2196/57406
Guardado SKarampela MIsomursu MGrundstrom C(2024)Use of Patient-Generated Health Data From Consumer-Grade Devices by Health Care Professionals in the Clinic: Systematic ReviewJournal of Medical Internet Research10.2196/4932026(e49320)Online publication date: 31-May-2024
https://doi.org/10.2196/49320
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