TY - JOUR
T1 - Using Process Mining Techniques to Study Workflows in a Pre-operative Setting
AU - Grando, Maria
AU - Groat, Danielle
AU - Furniss, Stephanie K.
AU - Nowak, Joshua
AU - Gaines, Regina
AU - Kaufman, David
AU - Poterack, Karl A.
AU - Miksch, Tim
AU - Helmers, Richard A.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
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M3 - Article
C2 - 29854145
AN - SCOPUS:85058764589
SN - 1559-4076
VL - 2017
SP - 790
EP - 799
JO - AMIA ... Annual Symposium proceedings. AMIA Symposium
JF - AMIA ... Annual Symposium proceedings. AMIA Symposium
ER -