Related Experiment Video
Updated: Dec 4, 2025

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
Published on: August 8, 2019
Application of Human Factors Methods to Understand Missed Follow-up of Abnormal Test Results
Deevakar Rogith1, Tyler Satterly2,3, Hardeep Singh2,3
1The University of Texas Health Science Center at Houston School of Biomedical Informatics, Houston, Texas, United States.
Objective:
This study demonstrates application of human factors methods for understanding causes for lack of timely follow-up of abnormal test results ("missed results") in outpatient settings.
Methods:
We identified 30 cases of missed test results by querying electronic health record data, developed a critical decision method (CDM)-based interview guide to understand decision-making processes, and interviewed physicians who ordered these tests. We analyzed transcribed responses using a contextual inquiry (CI)-based methodology to identify contextual factors contributing to missed results. We then developed a CI-based flow model and conducted a fault tree analysis (FTA) to identify hierarchical relationships between factors that delayed action.
Results:
The flow model highlighted barriers in information flow and decision making, and the hierarchical model identified relationships between contributing factors for delayed action. Key findings including underdeveloped methods to track follow-up, as well as mismatches, in communication channels, timeframes, and expectations between patients and physicians.
Conclusion:
This case report illustrates how human factors-based approaches can enable analysis of contributing factors that lead to missed results, thus informing development of preventive strategies to address them.
More Related Videos
05:35Author Spotlight: Developing a Point-of-Care Hemoglobin Estimation Method for Anemia Management
Published on: January 19, 2024
11:21Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Related Concept Videos
Methods of Documentation VI: Case Management Model
For example, a patient with a chronic...
Assumptions of Survival Analysis
Errors occurring during blood pressure monitoring
Several factors...
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...
Regression Toward the Mean
Detection of Gross Error: The Q Test