Characterizing and Visualizing Display and Task Fragmentation in the Electronic Health Record: Mixed Methods Design (Preprint)

Autor: Yalini Senathirajah, David R Kaufman, Kenrick D Cato, Elizabeth M Borycki, Jaime Allen Fawcett, Andre W Kushniruk
Rok vydání: 2020
DOI: 10.2196/preprints.18484
Popis: BACKGROUND The complexity of health care data and workflow presents challenges to the study of usability in electronic health records (EHRs). Display fragmentation refers to the distribution of relevant data across different screens or otherwise far apart, requiring complex navigation for the user’s workflow. Task and information fragmentation also contribute to cognitive burden. OBJECTIVE This study aims to define and analyze some of the main sources of fragmentation in EHR user interfaces (UIs); discuss relevant theoretical, historical, and practical considerations; and use granular microanalytic methods and visualization techniques to help us understand the nature of fragmentation and opportunities for EHR optimization or redesign. METHODS Sunburst visualizations capture the EHR navigation structure, showing levels and sublevels of the navigation tree, allowing calculation of a new measure, the Display Fragmentation Index. Time belt visualizations present the sequences of subtasks and allow calculation of proportion per instance, a measure that quantifies task fragmentation. These measures can be used separately or in conjunction to compare EHRs as well as tasks and subtasks in workflows and identify opportunities for reductions in steps and fragmentation. We present an example use of the methods for comparison of 2 different EHR interfaces (commercial and composable) in which subjects apprehend the same patient case. RESULTS Screen transitions were substantially reduced for the composable interface (from 43 to 14), whereas clicks (including scrolling) remained similar. CONCLUSIONS These methods can aid in our understanding of UI needs under complex conditions and tasks to optimize EHR workflows and redesign.
Databáze: OpenAIRE