Clinical Data in Context

TLDR

Clinical data combined with contextual information can help chronic disease patients understand their condition, but current tools lack support for interpreting multiple data streams. The study investigates how Type 1 diabetes patients and caregivers interpret clinical and contextual data through context‑enhanced visualizations, and uses these insights to propose design guidelines for sensemaking tools that support patient agency. The authors conducted semi‑structured interviews with patients and caregivers, presenting them with context‑enhanced visualizations of their data to probe interpretation activities. Participants performed four analytical activities—identifying context‑based trends, triangulating factors, proposing actions, and hypothesizing alternate factors—yet struggled with trend detection and counterintuitive insights, illustrating that sensemaking both guides action and uncovers information needs for contextual data exploration.

Abstract

Clinical data augmented with contextual data can help patients with chronic conditions make sense of their disease. However, existing tools do not support interpretation of multiple data streams. To better understand how individuals make sense of clinical and contextual data, we interviewed patients with Type 1 diabetes and their caregivers using context-enhanced visualizations of patients' data as probes to facilitate interpretation activities. We observed that our participants performed four analytical activities when interpreting their data -- finding context-based trends and explaining them, triangulating multiple factors, suggesting context-specific actions, and hypothesizing about alternate contextual factors affecting outcomes. We also observed two challenges encountered during analysis -- the inability to identify clear trends challenged action planning and counterintuitive insights compromised trust in data. Situating our findings within the existing sensemaking frameworks, we demonstrate that sensemaking can not only inform action but can guide the discovery of information needs for exploration. We further argue that sensemaking is a valuable approach for exploring contextual data. Informed by our findings and our reflection on existing sensemaking frameworks, we provide design guidelines for sensemaking tools to improve awareness of contextual factors affecting patients and to support patients' agency in making sense of health data.