Allan Fong1, Daniel J Hoffman2, A Zachary Hettinger2,3, Rollin J Fairbanks2,3,4, Ann M Bisantz4. 1. MedStar Institute for Innovation - National Center for Human Factors in Healthcare, 3007 Tilden St. NW, Suite 7M, Washington, DC, 20008, USA allan.fong@medicalhfe.org. 2. MedStar Institute for Innovation - National Center for Human Factors in Healthcare, 3007 Tilden St. NW, Suite 7M, Washington, DC, 20008, USA. 3. Georgetown University School of Medicine, 3800 Reservoir Rd NW, Washington, DC 20007. 4. The State University of New York, University at Buffalo, Amherst, NY 14216, USA.
Abstract
IMPORTANCE AND OBJECTIVES: As health information technologies become more prevalent in physician workflow, it is increasingly important to understand how physicians are using and interacting with these systems. This includes understanding how physicians search for information presented through health information technology systems. Eye tracking technologies provide a useful technique to understand how physicians visually search for information. However, analyzing eye tracking data can be challenging and is often done by measuring summative metrics, such as total time looking at a specific area and first-order transitions. METHODS: In this paper, we propose an algorithmic approach to identify different visual search patterns. We demonstrate this approach by identifying common visual search patterns from physicians using a simulated prototype emergency department patient tracking system. RESULTS AND CONCLUSIONS: We evaluate and compare the visual search pattern results to first-order transition results. We discuss the benefits and limitations of this approach and insights from this initial evaluation.
IMPORTANCE AND OBJECTIVES: As health information technologies become more prevalent in physician workflow, it is increasingly important to understand how physicians are using and interacting with these systems. This includes understanding how physicians search for information presented through health information technology systems. Eye tracking technologies provide a useful technique to understand how physicians visually search for information. However, analyzing eye tracking data can be challenging and is often done by measuring summative metrics, such as total time looking at a specific area and first-order transitions. METHODS: In this paper, we propose an algorithmic approach to identify different visual search patterns. We demonstrate this approach by identifying common visual search patterns from physicians using a simulated prototype emergency department patient tracking system. RESULTS AND CONCLUSIONS: We evaluate and compare the visual search pattern results to first-order transition results. We discuss the benefits and limitations of this approach and insights from this initial evaluation.
Authors: Jonathan Currie; Raymond R Bond; Paul McCullagh; Pauline Black; Dewar D Finlay; Stephen Gallagher; Peter Kearney; Aaron Peace; Danail Stoyanov; Colin D Bicknell; Stephen Leslie; Anthony G Gallagher Journal: Int J Comput Assist Radiol Surg Date: 2019-02-07 Impact factor: 2.924