Cohort Comparison of Event Sequences with Balanced Integration of Visual Analytics and Statistics

Abstract

Finding the differences and similarities between two datasets is a common analytics task. With temporal event sequence data, this task is complex because of the many ways single events and event sequences can differ between the two datasets (or cohorts) of records: the structure of the event sequences (e.g., event order, co-occurring events, or event frequencies), the attributes of events and records (e.g., patient gender), or metrics about the timestamps themselves (e.g., event duration). In exploratory analyses, running statistical tests to cover all cases is time-consuming and determining which results are significant becomes cumbersome. Current analytics tools for comparing groups of event sequences emphasize a purely statistical or purely visual approach for comparison. This paper presents a taxonomy of metrics for comparing cohorts of temporal event sequences, showing that the problem-space is bounded. We also present a visual analytics tool, CoCo (for "Cohort Comparison"), which implements balanced integration of automated statistics with an intelligent user interface to guide users to significant, distinguishing features between the cohorts. Lastly, we describe two early case studies: the first with a research team studying medical team performance in the emergency department and the second with pharmacy researchers.

Chronodes

“…An alternate approach to understanding the trends of aggregated mHealth data streams is to consider groups of patients as cohorts, or individuals that share certain properties [4, 23]. In an effort to comparatively assess sequences of events between cohorts, projects such as CoCo (Cohort Comparison) [23] show the chronology of events associated with two user-defined cohorts.…”

“…In an effort to comparatively assess sequences of events between cohorts, projects such as CoCo (Cohort Comparison) [23] show the chronology of events associated with two user-defined cohorts. Whereas this effectively reveals the different properties and event sequences between specified cohorts, CoCo focuses on specifying and comparing the attributes of two distinctly defined cohorts (e.g., male and female), and does not enable the user to interactively and dynamically redefine cohort groups by arranging sequences of events.…”

Mining and exploring care pathways from electronic medical records with visual analytics

“…Outflow [19] designed a way to aggregate events into a graph, as well as integrating statistics. CoCo [37] is a tool for comparing event sequences at a cohort level.…”

ITEA—interactive trajectories and events analysis: exploring sequences of spatio-temporal events in movement data

“…Event sequence data appear in a very diverse range of domains, such as medical care, movement analysis, marketing, sociology, bioinformatics, or genomics, for instance [11,12,16]. An example of an application dealing with such event sequences is LifeFlow [19] visualization tool, where events are grouped by certain characteristics and the average of a measure (e.g., elapsed time) is calculated.…”