Decision-Support Tool for Diagnosing Pulmonary Embolism

Digital Clinical Decision-Support Tool for Diagnosing Pulmonary Embolism

About the Project

The goal of this project is to design, create, and evaluate the impact of a clinical decision-support tool in a hospital setting with the aim of reducing (potentially) unneeded tests, or to help providers choose the best path to pulmonary embolism (PE) diagnosis. PE is the sudden blockage of a major blood vessel in the lung. It is surprisingly common and has a high fatality rate if not diagnosed. This user-centred design project started as a Computer Science PhD project on Visualizing Uncertainty in 2006, with observations and interviews with real providers in the hospital. This helped the PhD student understand workflow and develop a prototype. This prototype was evaluated in a pre-clinical setting and found to be better at supporting PE diagnosis than classroom lectures because of its 24/7 availability. W21C has now taken that prototype, redeveloped it into a Web app, and is studying its impacts on PE diagnosis in Calgary hospitals. This research was supported through an Alberta Innovates CRIO team grant.

Impact

Research results for this study hope to…

  • Improve patient outcomes and diagnostic accuracy for PE
  • Reduce mortality and morbidity associated with PE
  • Improve rural/remote care for parents where doctors may have limited access to diagnostic imaging
  • Save time, money, and health impacts caused by unnecessary diagnostic imaging (e.g., CT scans)

Services Provided

  • Grant Writing Support
  • Ethics Development and Management
  • Human-Centred Design
  • Expert Reviews
  • Usability Testing
  • Clinical Trial Design and Coordination
  • Medical and Scientific Oversight
  • Data Management
  • Knowledge Translation

Additional Content

Published article
Babione JN, Ocampo W, Haubrich S, Yang C, Zuk T, Kaufman J,Carpendale S, Ghali W, Altabbaa G, Human-centred design processes for clinical decision support: a pulmonary embolism case study, International Journal of Medical Informatics(2020), doi: https://doi.org/10.1016/j.ijmedinf.2020.104196