University of Kansas School of Medicine
Validating a Measure of Emergency Department Use Leveraging Long-Term Care EHR Data
Real World Data Source
LTC Data Cooperative
Dr. Bucy is a health services researcher and assistant professor in the Department of Population Health at
the University of Kansas School of Medicine. Through an organizational studies lens, her research examines
the role of long-term and post-acute care within the broader healthcare delivery system and seeks to
identify areas for meaningful organizational improvement in the structures and processes that facilitate the
delivery of high-quality, high-value care to older adults during periods of transition. She has previously
leveraged large-scale administrative data and complex survey data to evaluate organizational attributes that
drive long-term and post-acute care placement decisions and predict high-quality stays. Her research aims
to improve the organization and delivery of care for older adults with complex medical and social needs
along the care continuum.
Approximately 16% of older adults will visit an emergency department (ED) within 14 days of nursing home
(NH) admission, and one in three within the first month, potentially delaying recovery and increasing the risk of
medication errors or delays, falls, delirium, and death. Accurate and reliable approaches to identifying ED
transfers in real-time are essential for isolating contextual drivers of discontinuity; however, existing data
fields in the Minimum Data Set (MDS) provide only limited approximations of resident absence. This project
will derive and validate a measure of ED utilization using the Long-Term Care (LTC) Data Cooperative EHR
data. This award will provide Dr. Bucy with the necessary training and experience using EHR data linked to
Medicare data to: (1) Validate a measure of ED utilization against an established Medicare standard, and (2)
Characterize variation in ED use (frequency, duration) by time since hospital discharge, short versus long-stay
NH status, and proximity to clinical events. This project will establish the validity of a systematic approach to
identifying patterns of ED utilization in NHs using real-world EHR data. These findings will inform future
research aimed at developing and testing targeted interventions to strengthen initial discharge practices and
prevent unnecessary cycling of patients back to the ED. This work will provide a foundation and key
preliminary evidence for future research aimed at identifying opportunities for targeted interventions to
improve and strengthen care processes within and across organizations.