Talk to the Veterans Crisis Line now
U.S. flag
An official website of the United States government

VA Health Systems Research

Go to the VA ORD website
Go to the QUERI website

HSR&D Citation Abstract

Search | Search by Center | Search by Source | Keywords in Title

A flexible framework for visualizing and exploring patient misdiagnosis over time.

Widanagamaachchi W, Peterson K, Chapman A, Classen D, Jones M. A flexible framework for visualizing and exploring patient misdiagnosis over time. Journal of Biomedical Informatics. 2022 Oct 1; 134:104178.

Dimensions for VA is a web-based tool available to VA staff that enables detailed searches of published research and research projects.

If you have VA-Intranet access, click here for more information

VA staff not currently on the VA network can access Dimensions by registering for an account using their VA email address.
   Search Dimensions for VA for this citation
* Don't have VA-internal network access or a VA email address? Try searching the free-to-the-public version of Dimensions


Diagnosis is a complex and ambiguous process and yet, it is the critical hinge point for all subsequent clinical reasoning and decision-making. Tracking the quality of the patient diagnostic process has the potential to provide valuable insights in improving the diagnostic accuracy and to reduce downstream errors but needs to be informative, timely, and efficient at scale. However, due to the rate at which healthcare data are captured on a daily basis, manually reviewing the diagnostic history of each patient would be a severely taxing process without efficient data reduction and representation. Application of data visualization and visual analytics to healthcare data is one promising approach for addressing these challenges. This paper presents a novel flexible visualization and analysis framework for exploring the patient diagnostic process over time (i.e., patient diagnosis paths). Our framework allows users to select a specific set of patients, events and/or conditions, filter data based on different attributes, and view further details on the selected patient cohort while providing an interactive view of the resulting patient diagnosis paths. A practical demonstration of our system is presented with a case study exploring infection-based patient diagnosis paths.

Questions about the HSR website? Email the Web Team

Any health information on this website is strictly for informational purposes and is not intended as medical advice. It should not be used to diagnose or treat any condition.