Evidence map›Paper›PMID 37811698›Full record

ArticleJournal of the American Geriatrics Society2024

Automating risk stratification for geriatric syndromes in the emergency department.

Adrian D Haimovich, Manish N Shah, Lauren T Southerland, Ula Hwang, Brian W Patterson

Abstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Article
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  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
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  14. Article
  15. Team-based, Multidisciplinary Care in the Emergency Department.Emergency medicine clinics of North America · 2025
    Review
  16. Review
  17. Enhancing healthcare access for an older population: The age-friendly emergency department.Journal of the American College of Emergency Physicians open · 2024
    Review
  18. Observational
  19. Article
  20. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Adrian D HaimovichDepartment of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.ORCID 0000-0002-4106-7055
Manish N ShahBerbeeWalsh Department of Emergency Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.ORCID 0000-0001-6331-1074
Lauren T SoutherlandDepartment of Emergency Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA.ORCID 0000-0002-3561-8332
Ula HwangGeriatric Research, Education and Clinical Center, James J. Peters VAMC, Bronx, New York, USA.ORCID 0000-0002-3715-3073
Brian W PattersonBerbeeWalsh Department of Emergency Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.ORCID 0000-0002-4584-3808

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Institutional Career Development CoreKL2TR002542 · NCATS · HARVARD MEDICAL SCHOOL · PI BREDELLA, MIRIAM ANTOINETTE, RUTKOVE, SEWARD B. · 2018 to 2022
$8.7M
Translational Researchin Aging Trainnig ProgramT32AG023480 · NIA · HEBREW REHABILITATION CENTER FOR AGED · PI LIPSITZ, LEWIS · 2004 to 2024
$7.6M
Growing the Geriatric Emergency care Applied Research (GEAR 1.1) network: Expanding and sustaining an emergency care aging study infrastructure.R33AG058926 · NIA · YALE UNIVERSITY · PI Ula Y Hwang, Daniella Meeker · 2020 to 2026
$4.6M
Geriatric Emergency care Applied Research network 2.0 - Advancing Dementia Care (GEAR 2.0 ADC)R61AG069822 · NIA · YALE UNIVERSITY · PI HWANG, ULA Y, SHAH, MANISH N · 2020 to 2021
$3.0M
Preventing Future Falls in Older Adult ED Patients: Evaluating the Implementation and Effectiveness of a Novel Automated Screening and Referral InterventionR18HS027735 · AHRQ · UNIVERSITY OF WISCONSIN-MADISON · PI PATTERSON, BRIAN W · 2021 to 2025
$1.7M
Mentoring and Research in Patient-Oriented Geriatric Emergency CareK24AG054560 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI SHAH, MANISH N · 2017 to 2021
$955k
Research and mentoring program in shared decision making in the care of older adultsK24AG071906 · NIA · BETH ISRAEL DEACONESS MEDICAL CENTER · PI SCHONBERG, MARA A · 2021 to 2025
$946k
Implementation of Multidisciplinary Assessments for Geriatric Patients in an ED Observation Unit (IMAGE)K23AG061284 · NIA · OHIO STATE UNIVERSITY · PI SOUTHERLAND, LAUREN T. · 2019 to 2023
$832k
AHRQ HHS R18 HS027735NCATS NIH HHS KL2 TR002542NCATS NIH HHS UL1 TR001863NIA NIH HHS K23 AG061284NIA NIH HHS K23AG061284NIA NIH HHS K24AG054560NIA NIH HHS K24 AG071906NIA NIH HHS R33 AG058926NIA NIH HHS R61 AG069822NIA NIH HHS T32 AG023480NIA NIH HHS T32AG023480
6 · The paper itself

Abstract

backgroundGeriatric 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.

Indexed as

Emergency Medical ServicesEmergency Service, HospitalAgedDelivery of Health CareHumansRisk AssessmentRisk FactorsSyndromeartificial intelligenceautomationemergency medicinemachine learningscreening

Identifiers

PMID37811698
PMCPMC10866303

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.