Aims:

Patient journey studies utilize qualitative interviews to describe patients’ entire clinical and quality of life clinical and experience from diagnosis through recovery. The majority of patient journey studies visualize the experiences of individual patients or small groups of patients using heterogenous methods. By aggregating patient experiences, researchers can identify the ways that interventions and information influence outcomes. This presentation aims to introduce a visualization approach to improve the interpretability of patient journey study data and better facilitate comparison across studies.

Methods:

We examined examples of patient journey studies to identify key deficits in current approaches to visualizing patient journey data, particularly the aggregated narratives of more than one patient. These deficits guided the development of a visualization approach that facilitates the integration of patients’ condition and clinical interactions. The approach was then used to develop an open-source, visualization tool. The approach is interpretable as static images, but can also utilize animation to reinforce conclusions. Using a case study, we demonstrate the application of this tool and highlight additional insights facilitated by the tool.

Results:

The application of this tool enables researchers to more efficiently evaluate patient journey data to elicit more meaningful conclusions, such as gaps in information sharing, insight about intervention timing, and opportunities to enhance patient activation, among many others.

Conclusions:

Patient journey studies can provide unique and useful insights into patients’ entire disease experience. Our framework and data visualization tool can help researchers better integrate fragmented data, differentiate trends among aggregated qualitative data, and identify meaningful insights to improve patient outcomes.