Towards Data-Enabled Physical Activity Planning: An Exploratory Study of HCP Perspectives On The Integration Of Patient-Generated Health Data

2025-11-02

AI Summary

Integrating patient-generated health data (PGHD) into clinical workflows for physical activity planning in cardiovascular rehabilitation remains challenging, particularly for supporting shared decision-making (SDM) between healthcare professionals (HCPs) and patients. Method: Through contextual inquiry, self-tracking, in-depth interviews, and card-sorting workshops—analyzed qualitatively—we systematically mapped clinical workflows and patient journeys, identifying HCPs’ critical information needs in risk assessment, vital sign monitoring, and exercise adherence management. Contribution/Results: We propose a tripartite PGHD integration framework—“adaptive data interpretation, standardization, and organizational support”—and uncover core barriers: time constraints, suboptimal data quality, lack of trust in PGHD, and ambiguous role responsibilities. Our findings provide empirically grounded design principles and actionable implementation pathways for developing trustworthy, usable, and clinically embeddable digital health technologies tailored to cardiac rehabilitation.

Technology Category

• Planning, Routing, and Scheduling: Activity and Plan Recognition
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Knowledge Representation and Reasoning: Diagnosis and Abductive Reasoning

Application Category

• User Modeling, Personalization and Recommendation: Psychology-informed user models and recommender systems
• Responsible Web: Consent frameworks and practices on the web
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

Physical activity planning is an essential part of cardiovascular rehabilitation. Through a two-part formative design exploration, we investigated integrating patient-generated health data (PGHD) into clinical workflows supporting shared decision-making (SDM) in physical activity planning. In part one, during a two-week situated study, to reduce risk of working with cardiovascular disease patients, we recruited healthy participants who self-tracked health and physical activity data and attended a physical activity planning session with a healthcare professional (HCP). Subsequently both HCPs and participants were interviewed. In part two, findings from part one were presented to HCPs in a card-sorting workshop to corroborate findings and identify information needs of HCPs alongside patient journeys and clinical workflows. Our outcomes highlight HCP information needs around patient risk factors, vital signs, and adherence to physical activity. Enablers for PGHD integration include adaptive data sense-making, standardization and organizational support for integration. Barriers include lack of time, data quality, trust and liability concerns. Our research highlights implications for designing digital health technologies that support PGHD in physical activity planning during cardiac rehabilitation.

Problem

• Integrating patient-generated health data into clinical workflows
• Supporting shared decision-making in physical activity planning
• Identifying barriers and enablers for PGHD integration

Innovation

• Integrating patient-generated health data into clinical workflows
• Using card-sorting workshops to identify healthcare professional needs
• Developing adaptive data sense-making for physical activity planning