Making quality improvement data more accessible and understandable: Analyst, designer, and storyteller

Making data more accessible and understandable in quality improvement requires a diversity of approaches beyond formal teaching in technical skills of measurement. Improvement practitioners might co-opt the wider skillset of analyst, designer, and storyteller in tailoring the team strategy needed to make best use of the data used to inform decision-making at the point of care. Data literacy levels, negative prior experiences, or limited access to technology might influence the ability of teams to engage in measurement. Co-designing the experience ensures that the data are meaningful, that it is framed in inclusive language, and that the process is manageable. Being mindful about intrinsic motivators when designing measurement strategies can improve the collective approach to data analysis and the sustainability of the project. Thoughtful data visualization takes account of the inherent perceptual challenges of comprehending data and complex images. Establishing a routine of simplification-removing redundant elements and distractions-and amplifying aspects that aid understanding can bring clarity to the important concepts within a chart. Story-telling techniques can help wider audiences engage with data by carefully shaping analytical and emotional content around a central narrative-always mindful of the limitations of working memory, and the emotional momentum needed to inspire change.