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Title page for ETD etd-03212018-213405


Type of Document Master's Thesis
Author Danciu, Ioana
URN etd-03212018-213405
Title Mixed methods approach for understanding clinical workflow
Degree Master of Science
Department Biomedical Informatics
Advisory Committee
Advisor Name Title
Dr. Kim Unertl Committee Chair
Dr. Daniel Fabbri Committee Member
Dr. Stuart Weinberg Committee Member
Keywords
  • mixed methods
  • clinical workflow
  • qualitative studies
Date of Defense 2018-02-16
Availability unrestricted
Abstract
Our research focused on the study of clinical workflow using an iterative mixed-methods approach that integrated data analytics with qualitative observations of people, processes and use of technologies. This methodology allowed for assertions from data based on an understanding of the environment. We used the Vanderbilt Ingram Cancer Center (VICC) as the setting for our study due to the increased complexity of the workflows. Our results illustrated the utility of our methodology by establishing causal explanations for workflow trends obtained from electronic data sources used by the clinical staff at the VICC: a workflow tool (the Outpatient Whiteboard), an EHR (Starpanel), an outpatient appointment scheduling system (EPIC) and a human resources system (Kronos). We are able to demonstrate that improved capacity and increased staffing result in decreased wait times at the VICC lab. Using qualitative observations, we identified a significant failure in the paging system, which illustrated the importance of pairing the analytics with qualitative studies. Our results also emphasized the importance of managing workflow via the Outpatient Whiteboard as well as an entire ecosystem of electronic data tools that generated information in a format suitable for research.
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