Providing Context to the "Unknown": Patient and Provider Reflections on Connecting Personal Tracking, Patient-Reported Insights, and EHR Data within a Post-COVID Clinic

COVID Long Haul (CLH) is an emerging chronic illness for which the healthcare system continues to seek a common understanding of symptoms, diagnosis, and treatment. CLH experiences can differ drastically, necessitating personalized care plans. Because patients interact with different clinicians during their CLH journey, it becomes important to ensure interoperability and understand clinical relevance of different data that can support clinicians in making appropriate recommendations. We conducted qualitative research where we interviewed 13 patients, conducted a focus group with 8 clinicians, and analyzed care plan follow-up records. We report patient and clinician expectations from and interactions with clinic data. We uncover logistical challenges, personal contexts, and health barriers impacting patient compliance. As researchers embedded in the clinical system, we identify the potential of using multiple patient data streams to support personalized treatment and clinical decisions. We discuss technology design opportunities and provide actionable recommendations for improving clinical workflows and cross-provider collaboration.

CCS Concepts: • Human-centered computing → Empirical studies in HCI; • Applied computing → Health informatics.