Digital Health Co-Design
Affinity Diagramming
Affinity Diagramming
Affinity diagramming is a collaborative, visual method used to organise and synthesise large amounts of qualitative data by grouping related ideas, quotes, or observations into clusters, from which overarching themes emerge. It helps teams move from scattered raw data to clear, shared insights, supporting problem definition and design decision-making.
Application Example
In this study, researchers aimed to design a web-based prototype tool to support the remote management of chemotherapy-related toxicities in cancer patients. They collected qualitative data through ethnographic field observations, interviews, and focus groups with patients, caregivers, and healthcare professionals. Using the affinity diagramming method by Holtzblatt and Beyer, two human factors specialists first coded all data sources to extract key words, phrases, and quotes. These coded data were then discussed in team ideation sessions with both human factors experts and clinicians, where related codes were clustered into natural groupings and developed into overarching themes (for example, the quote “Patients are overwhelmed. My guess is that 95% of the information is instantly forgotten” was coded as “Overwhelmed” and grouped under the theme “Anxiety and feeling overwhelmed”).
While this approach helped the multidisciplinary team synthesise diverse perspectives into clear, actionable insights, a key limitation is that affinity diagramming produces only high-level thematic summaries and may lack rich contextual detail; to mitigate this, the same researchers who conducted the fieldwork also joined the analysis and prototype design, drawing on their first-hand contextual understanding, and triangulation and data saturation were sought to enhance the credibility of the findings. (Prince et al., 2019)