Process Mining and Ethnography Study of Medication Reconciliation Tasks

Vaishak Ramesh Vellore, M. Adela Grando, Benjamin Duncan, David R. Kaufman, Stephanie K. Furniss, Bradley N. Doebbeling, Karl A. Poterack, Timothy Miksch, Richard A. Helmers

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


We studied the medication reconciliation (MedRec) task through 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.

Original languageEnglish (US)
Pages (from-to)1167-1176
Number of pages10
JournalAMIA ... Annual Symposium proceedings. AMIA Symposium
StatePublished - 2019

ASJC Scopus subject areas

  • Medicine(all)


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