Description
We studied the medication reconciliation (MedRec) taskthrough analysis of computer logs and ethnographic data. Time spent by healthcare providers performing MedRec was compared between two different EHR systems used at four different regional perioperative settings. Only one of the EHRs used at two settings generated computer logs that supported automatic discovery of the MedRec task. At those two settings, 53 providers generated 383 MedRec instances. Findings from the computer logs were validated with ethnographic data, leading to the identification and removal of 47 outliers. Without outliers, one of the settings had slightly smaller mean (SD) time in seconds 67.3 (40.2) compared with the other, 92.1 (25). The difference in time metrics was statistically significant (p<.001). Reusability of an existing task-based analytic method allowed for rapid study of EHR-based workflow and task.
Learning Objective: Describe what EHR computer logs are and its use for the automatic analysis of clinical tasks that require interactions with the EHR
Give examples of how computer logs and ethnographic data can be combined to study EHR-mediated tasks
Discuss challenges and opportunities for the design of reusable and generalizable mixed-method approaches to study EHR-mediated tasks
Authors:
Vaishak Ramesh Vellore, Arizona State University
Adela Grando, Arizona State University
Benjamin Duncan, Arizona State University
David Kaufman (Presenter)
Arizona State University
Stephanie Furniss, Arizona State University
Bradley Doebbeling, Arizona State University
Karl Poterack, Mayo Clinic
Tim Miksch, Mayo Clinic
Richard Helmers, Mayo Clinic
Presentation Materials: