Using Patient-Generated Data to Support Cardiac Rehabilitation and the Transition to Self-Care

Title of the Paper

Using Patient-Generated Data to Support Cardiac Rehabilitation and the Transition to Self-Care

Bibliographic Information

• Subject Area: Human-Computer Interaction (HCI), Mobile Health Technology (mHealth), Patient-Generated Data
• Keywords: mHealth, Cardiac Rehabilitation, Self-Management, Wearable Devices, Peer Data Sharing, Mobile Health Technology, Integration of Subjective and Objective Data, Co-Design, Field Study

Research Background and Problem

• Identified Problems:
  • Cardiac rehabilitation is critical for reducing long-term mortality and recurrence risks in cardiovascular disease patients, but the transition to self-management is challenging.
  • Technology-supported rehabilitation programs hold great potential but face barriers in clinical practice, such as the burden on patients and clinicians, lack of trust and familiarity with technology, and difficulty integrating into existing workflows.
  • Existing system designs rarely adopt user-centered and iterative approaches.
• Significance of the Research:
  • With the proliferation of wearable devices, patient-generated data (including activity levels, heart rate, etc.) can help clinicians gain a more comprehensive understanding of patients' conditions and support the transition from clinical rehabilitation to self-management.
  • This approach has the potential to enhance patients' self-efficacy, improve rehabilitation outcomes, and reduce healthcare burdens.
• Motivation and Related Work:
  • Previous studies have highlighted the need to address patients' emotional, safety, and knowledge acquisition needs during cardiac rehabilitation and suggested the use of digital tools to connect clinical guidance with everyday life scenarios.
  • Practical challenges include the high complexity of data analysis, poor clinical operability, and patients' concerns about technology and data sharing.

Solution

• Proposed Method or Solution:
  • Designed and tested a cardiac rehabilitation data system driven by patient-generated data, combining objective data (e.g., heart rate) and subjective data (e.g., questionnaire feedback) to support both clinicians and patients in improving the effectiveness of rehabilitation monitoring and the transition to self-management.
  • Co-designed the system with clinical teams to ensure alignment with real-world needs. The system prototype was validated using Wizard-of-Oz techniques.
• Innovations:
  • Integrated patients' subjective experience data (collected via structured questionnaires) with objective monitoring data (collected via Fitbit) to provide "situated objectivity" support.
  • Developed a clinical user interface for integrated data, embedding real-time feedback optimization for physicians in the design.
• Implementation Steps:
  1. Collaborated with clinicians for co-design, analyzing their needs and workflows.
  2. System design included: patients using Fitbit and completing weekly questionnaires; data aggregated and manually processed by researchers before being provided to clinicians.
  3. Conducted an 18-week field study within a Phase 3 cardiac rehabilitation program at a hospital to evaluate the system's impact on patients and clinicians.
  4. Conducted semi-structured interviews with patients to understand their attitudes toward data usage and sharing.

Research Outcomes

• Specific Outcomes:
  • The data provided personalized insights into patients' health activities, enabling clinicians to better manage rehabilitation progress.
  • Periodic collection of subjective data allowed clinicians to understand soft information such as patients' emotions, motivations, and health knowledge.
  • Fitbit and questionnaires established continuity between in-class and out-of-class activities for patients, boosting their confidence in independently achieving recommended goals.
• Advantages:
  • Compared to existing systems, this approach combines subjective and objective data, making it more adaptable to diverse patient needs and supporting more refined clinical decision-making.
  • The integration of both data types makes the information more contextualized, facilitating easier understanding and application by clinicians.
• Experimental and Evaluation Results:
  • The combination of daily Fitbit monitoring data and psychological state questionnaires significantly improved the quality of interaction among patients and enhanced clinicians' preparation efficiency.
  • Patients were generally open to data sharing but showed reservations about viewing other patients' data, especially when lacking context or compatibility.
  • Early introduction (during the initial phase of rehabilitation) was more effective in enhancing patients' technological adaptability and self-management confidence.
• Limitations and Future Directions:
  • The study was limited to a single hospital setting, with participants predominantly from middle-income Western backgrounds; future research should extend to more diverse populations.
  • The short study duration prevented the assessment of long-term self-management outcomes.
  • Future work should explore patient-generated recovery narratives and visual data presentation techniques, including the integration of multimedia and delayed sharing strategies.