Automating risk stratification for geriatric syndromes in the emergency department

Author:

Haimovich Adrian D.1ORCID,Shah Manish N.2ORCID,Southerland Lauren T.3ORCID,Hwang Ula45ORCID,Patterson Brian W.26ORCID

Affiliation:

1. Department of Emergency Medicine Beth Israel Deaconess Medical Center Boston Massachusetts USA

2. BerbeeWalsh Department of Emergency Medicine University of Wisconsin School of Medicine and Public Health Madison Wisconsin USA

3. Department of Emergency Medicine The Ohio State University Wexner Medical Center Columbus Ohio USA

4. Geriatric Research Education and Clinical Center, James J. Peters VAMC Bronx New York USA

5. Department of Emergency Medicine Yale School of Medicine New Haven Connecticut USA

6. Department of Industrial and Systems Engineering, Department of Biostatistics and Medical Informatics University of Wisconsin—Madison Madison Wisconsin USA

Abstract

AbstractBackgroundGeriatric emergency department (GED) guidelines endorse screening older patients for geriatric syndromes in the ED, but there have been significant barriers to widespread implementation. The majority of screening programs require engagement of a clinician, nurse, or social worker, adding to already significant workloads at a time of record‐breaking ED patient volumes, staff shortages, and hospital boarding crises. Automated, electronic health record (EHR)‐embedded risk stratification approaches may be an alternate solution for extending the reach of the GED mission by directing human actions to a smaller subset of higher risk patients.MethodsWe define the concept of automated risk stratification and screening using existing EHR data. We discuss progress made in three potential use cases in the ED: falls, cognitive impairment, and end‐of‐life and palliative care, emphasizing the importance of linking automated screening with systems of healthcare delivery.ResultsResearch progress and operational deployment vary by use case, ranging from deployed solutions in falls screening to algorithmic validation in cognitive impairment and end‐of‐life care.ConclusionsAutomated risk stratification offers a potential solution to one of the most pressing problems in geriatric emergency care: identifying high‐risk populations of older adults most appropriate for specific GED care. Future work is needed to realize the promise of improved care with less provider burden by creating tools suitable for widespread deployment as well as best practices for their implementation and governance.

Funder

Agency for Healthcare Research and Quality

National Institute on Aging

U.S. Department of Veterans Affairs

National Center for Advancing Translational Sciences

John A. Hartford Foundation

Publisher

Wiley

Subject

Geriatrics and Gerontology

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