Using Patient-Generated Data to Support Cardiac Rehabilitation and the Transition to Self-Care
Shreya Tadas, Jane Dickson, David Coyle
Abstract
Patient-generated data from commercially available self-tracking devices has the potential to enhance support for people transitioning from hospitalization to self-care. However, studies have revealed significant barriers to the routine use of such data in clinical settings. This paper explores the use of patient-generated data in the context of cardiac rehabilitation. We describe a two-stage investigation: (1) a co-design study with clinicians to design a data system that combines objective and subjective patient data; and (2) an 18-week field-study where this system was deployed as part of a hospital-based rehabilitation program. Our findings suggest the system is feasible, supported clinicians’ workflow, and helped patients to bridge the gap between supervised and self-managed care. Subjective data contextualized objective data and a structured approach data collection helped generate actionable information. The paper also provides insight on patients' attitudes towards peer data sharing and demonstrates the importance of timing when introducing self-tracking technology.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Cited by top-tier papers7
- CardioAI: A Multimodal AI-based System to Support Symptom Monitoring and Risk Prediction of Cancer Treatment-Induced CardiotoxicitySiyi Wu, Weidan Cao, Shihan Fu, Bingsheng Yao et al.CHI 2025 · 17 citations
- Caring about Care: A Meta-Narrative Review of HCI Research on CareZixuan Wang, Yuanrong Guo, Eilidh Bowman, Yuxiang Zhai et al.CHI 2026 · 6 citations
- "It's Sink or Swim": Exploring Patients' Challenges and Tool Needs for Self-Management of Postoperative Acute PainSouleima Zghab, Gabrielle Pagé, Mélanie Lussier, Sylvain Bédard et al.CHI 2024 · 3 citations
- Exploring Collaboration Breakdowns Between Provider Teams and Patients in Post-Surgery CareBingsheng Yao, Menglin Zhao, Zhan Zhang, Pengqi Wang et al.CHI 2026 · 1 citation
- Design for Dis/Ability: A Crip Inquiry into Personal Energy TrackingIrene Kaklopoulou, Sarah Homewood, Pedro SanchesCHI 2026 · 1 citation
Related papers
- Patients Waiting for Cues: Information Asymmetries and Challenges in Sharing Patient-Generated Data in the ClinicChi Young Oh, Yuhan Luo, Beth St. Jean, Eun Kyoung ChoeCSCW 2022 · 20 citations
- "I think it saved me. I think it saved my heart": The Complex Journey From Self-Tracking With Wearables To DiagnosisRachel Keys, Paul Marshall, Graham Stuart, Aisling Ann O'KaneCHI 2024 · 17 citations
- MIND: Empowering Mental Health Clinicians with Multimodal Data Insights through a Narrative DashboardRuishi Zou, Shiyu Xu, Margaret E. Morris, Jihan Ryu et al.CHI 2026 · 2 citations
- 'Are They Doing Better In The Clinic Or At Home?': Understanding Clinicians' Needs When Visualizing Wearable Sensor Data Used In Remote Gait Assessments For People With Multiple SclerosisAyanna Seals, Giuseppina Pilloni, Jin Kim, Raul Sanchez et al.CHI 2022 · 15 citations
- Design and Evaluation of a Power Wheelchair-based Self-tracking System to Prevent Pressure UlcersTamanna Motahar, Brandon Rivera-Melo, Ross Imburgia, YeonJae Kim et al.UbiComp 2025
