Exploring Alternative Methods of Visualizing Patient Data

Patient data visualization can help health care providers gain an overview of their patient’s condition, and assist in decision-making on next steps on management and care. This thesis explores acceptance of, and reactions to five visualizations that can be used to summarize patient data, including a Text Summary, text and frequency-based Word Cloud, a Bar Graph, a Line Graph, and a newly developed Text Graph that combines text with time-based distribution. Results from a qualitative study with medical school students and health care providers show that users can interpret patient health information from all visualizations, and can imagine using these visualizations in their medical practice. Overall, the Text Summary is the most positively received visualization, and the Text Summary and Text Graph are the most useful in extracting patient health information. This thesis provides evidence to support the idea that qualitative patient-generated information can be displayed in ways other than clinical notes.M.A.S