An Exploratory Study on the Utility of Patient-Generated Health Data as a Tool for Health Care Professionals in Multiple Sclerosis Care

Author:

Guardado Sharon1,Mylonopoulou Vasiliki2,Rivera-Romero Octavio345,Patt Nadine6,Bansi Jens6,Giunti Guido1789

Affiliation:

1. Empirical Software Engineering (M3S) Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland

2. Division of Human-Computer Interaction, Department Of Applied Information Technology, University of Gothenburg, Gothenburg, Sweden

3. Department of Electronic Technology, Universidad de Sevilla, Seville, Spain

4. Instituto de Investigación en Informática, Universidad de Sevilla, Seville, Spain

5. SABIEN Group, ITACA Institute, Universitat Politécnica de Valéncia, Valencia, Spain

6. Department of Neurology, Kliniken Valens, Rehabilitationszentrum Valens, Valens, Switzerland

7. Health Sciences and Technology Unit, Faculty of Medicine, University of Oulu, Finland

8. Applied Ergonomics and Design, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, The Netherlands

9. Clinical Medicine Neurology, School of Medicine, Trinity College Dublin, Dublin, Ireland

Abstract

Abstract Background Patient-generated health data (PGHD) are data collected through technologies such as mobile devices and health apps. The integration of PGHD into health care workflows can support the care of chronic conditions such as multiple sclerosis (MS). Patients are often willing to share data with health care professionals (HCPs) in their care team; however, the benefits of PGHD can be limited if HCPs do not find it useful, leading patients to discontinue data tracking and sharing eventually. Therefore, understanding the usefulness of mobile health (mHealth) solutions, which provide PGHD and serve as enablers of the HCPs' involvement in participatory care, could motivate them to continue using these technologies. Objective The objective of this study is to explore the perceived utility of different types of PGHD from mHealth solutions which could serve as tools for HCPs to support participatory care in MS. Method A mixed-methods approach was used, combining qualitative research and participatory design. This study includes three sequential phases: data collection, assessment of PGHD utility, and design of data visualizations. In the first phase, 16 HCPs were interviewed. The second and third phases were carried out through participatory workshops, where PGHD types were conceptualized in terms of utility. Results The study found that HCPs are optimistic about PGHD in MS care. The most useful types of PGHD for HCPs in MS care are patients' habits, lifestyles, and fatigue-inducing activities. Although these subjective data seem more useful for HCPs, it is more challenging to visualize them in a useful and actionable way. Conclusion HCPs are optimistic about mHealth and PGHD as tools to further understand their patients' needs and support care in MS. HCPs from different disciplines have different perceptions of what types of PGHD are useful; however, subjective types of PGHD seem potentially more useful for MS care.

Publisher

Georg Thieme Verlag KG

Subject

Health Information Management,Advanced and Specialized Nursing,Health Informatics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3