Visual Exploration and Cohort Identification of Acute Patient Histories Aggregated from Heterogeneous Sources

How can we use information visualization to support retrospective, exploratory analysis of collections of histories for patients admitted to acute care? This paper describes a novel design for visual cohort identification and exploration. We have developed a tool that integrates multiple, heterogeneous clinical data sources and allows alignment, querying and abstraction in a common workbench. This paper presents results from two projects and a review of related work in the field of information visualization including both presentation and interactive navigation of the information. We have developed an interactive prototype and present the visualization aspect of this prototype and a brief demonstration of its use in a research project with a large cohort of patients. The prototype represents and reasons with patient events in different OWL-formalizations according to the perspective and use: One for integration and alignment of patient records and observations; Another for visual presentation of individual or cohort trajectories. Health researchers have successfully analyzed large cohorts (over 100,000 individuals) using the tool. We have also used the tool to produce interactive personal health time-lines (for more than 10,000 individuals) on the web. Utility, usability and effect have been tested extensively and the results so far are promising. We envision that clinicians who want to learn more about groups of patients and their treatment processes will find the tool valuable. In addition, we believe that the visualization can be useful to researchers looking at data to be statistically evaluated, in order to discover new hypotheses or get ideas for the best analysis strategies. Our main conclusion is that the tool is usable, but it can be challenging to use for large data sets.Postprint version. © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

Design and Evaluation of a Temporal, Graph-Based Language for Querying Collections of Patient Histories

Giving clinicians and researchers the ability to easily retrieve and explore relevant fragments of patient histories would greatly facilitate quality assurance, patient followup and research on patient treatment processes. Established database query languages are inconvenient for such exploration, and may also be too complex for users with limited backgrounds in informatics. We believe that understandability can be increased in return for a sacrifice of some of the power of expression found in general query languages. In order to design a specialized query language, we have collected and synthesized a tentative list of requirements. Based on these requirements, we have designed and implemented Practice Explorer, a prototype for visual query of collections of patient histories, and evaluated the understandability of its query language by testing with medical students. The results indicate that parts of the language are intuitive enough for users to understand without demonstrations, examples, feedback or assistance. They also provide some lessons for future work in this area