Charting the COVID Long Haul Experience -- A Longitudinal Exploration of Symptoms, Activity, and Clinical Adherence
Jessica Pater, Shaan Chopra, Juliette Zaccour, Jeanne Carroll, Fayika Farhat Nova, Tammy Toscos, Shion Guha, Fen Lei Chang
TL;DR
This study addresses COVID Long Haul (CLH) by employing a three-month, multi-stream longitudinal design that triangulates EHR data, wearable sensor metrics, weekly symptom surveys, and exit interviews from 14 patients in a Post-COVID Clinic. By integrating objective data with subjective reports and clinician notes, the authors illuminate the heterogeneous and evolving nature of CLH, uncover adherence barriers, and reveal how patients experience and respond to health data and care plans. The work provides contextualized descriptions of patient experiences, evaluates the pros and cons of data triangulation across streams, and offers design heuristics for technologies that support CLH patients and their clinicians. The findings highlight the need for agile, user-centered design in health technologies and clinical workflows to accommodate uncertain trajectories, financial and social constraints, and the desire for a meaningful sense of a
Abstract
COVID Long Haul (CLH) is an emerging chronic illness with varied patient experiences. Our understanding of CLH is often limited to data from electronic health records (EHRs), such as diagnoses or problem lists, which do not capture the volatility and severity of symptoms or their impact. To better understand the unique presentation of CLH, we conducted a 3-month long cohort study with 14 CLH patients, collecting objective (EHR, daily Fitbit logs) and subjective (weekly surveys, interviews) data. Our findings reveal a complex presentation of symptoms, associated uncertainty, and the ensuing impact CLH has on patients' personal and professional lives. We identify patient needs, practices, and challenges around adhering to clinical recommendations, engaging with health data, and establishing "new normals" post COVID. We reflect on the potential found at the intersection of these various data streams and the persuasive heuristics possible when designing for this new population and their specific needs.