Using Process Mining Techniques to Study Workflows in a Pre-operative Setting

Maria Grando, Danielle Groat, Stephanie K. Furniss, Joshua Nowak, Regina Gaines, David Kaufman, Karl A. Poterack, Tim Miksch, Richard A. Helmers

    Research output: Contribution to journalArticlepeer-review

    2 Scopus citations

    Abstract

    Information technologies have transformed healthcare delivery and promise to improve efficiency and quality of care. However, in-depth analysis of EHR-mediated workflows is challenging. Our goal was to apply process mining, in combination with observational techniques, to understand EHR-based workflows. We reviewed nearly 76,000 event logs from 15 providers and supporting staff, and 142 patients in a pre-operative setting and we inspected 3 weeks of interviews and video observations. We found that on average 44 minutes were spent per patient interacting with the EHR, 55% of the time of the patient visit was spent by personnel interacting with the EHR and for over 5% of the time personnel used or reviewed paper-based artifacts. We also discovered the handover-of-care network and compared frequency of interactions between personnel. This study suggests that applying process mining in combination with observational techniques has vast potential for informing Mayo Clinic in the forthcoming EHR conversion.

    Original languageEnglish (US)
    Pages (from-to)790-799
    Number of pages10
    JournalAMIA ... Annual Symposium proceedings. AMIA Symposium
    Volume2017
    StatePublished - 2017

    ASJC Scopus subject areas

    • Medicine(all)

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