[PDF][PDF] Classifying Clinical Work Settings Using EHR Audit Logs: A Machine Learning Approach.

S Kim, SS Lou, LR Baratta… - American Journal of …, 2023 - researchgate.net
ABSTRACT OBJECTIVES: We used electronic health record (EHR)–based raw audit logs to
classify the work settings of anesthesiology physicians providing care in both surgical …

Autoregressive Language Models For Estimating the Entropy of Epic EHR Audit Logs

BC Warner, T Kannampallil, S Kim - arXiv preprint arXiv:2311.06401, 2023 - arxiv.org
EHR audit logs are a highly granular stream of events that capture clinician activities, and is
a significant area of interest for research in characterizing clinician workflow on the …

[HTML][HTML] A Computational Framework to Evaluate Emergency Department Clinician Task Switching in the Electronic Health Record Using Event Logs

AJ Moy, KD Cato, EY Kim, J Withall… - AMIA Annual …, 2023 - ncbi.nlm.nih.gov
Workflow fragmentation, defined as task switching, may be one proxy to quantify electronic
health record (EHR) documentation burden in the emergency department (ED). Few …

[HTML][HTML] Creating Conversion Factors from EHR Event Log Data: A Comparison of Investigator-Derived and Vendor-Derived Metrics for Primary Care Physicians

HS Magon, D Helkey, T Shanafelt… - AMIA Annual Symposium …, 2023 - ncbi.nlm.nih.gov
Physicians spend a large amount of time with the electronic health record (EHR), which the
majority believe contributes to their burnout. However, there are limitedstandardized …

[图书][B] Leveraging Clinical Data and Knowledge Networks to Derive Insights Into Alzheimer's Disease

A Tang - 2023 - search.proquest.com
Alzheimer's Disease (AD) is a devastating neurodegenerative disorder that is difficult to
study and treat despite decades of progress. This is due to disease heterogeneity, lack of …