Evidence map›Paper›PMID 40067297›Full record

SynthesisJAMA network open2025

Emergency Department Programs to Support Medication Safety in Older Adults: A Systematic Review and Meta-Analysis.

Rachel M Skains, Jane M Hayes, Katherine Selman, Yue Zhang, Phraewa Thatphet, Kazuki Toda, Bryan D Hayes, Carla Tayes, Martin F Casey, Elizabeth Moreton and 4 more

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Article
  6. Evaluation of Potentially Inappropriate Medications Prescribed to Older Adults Upon Emergency Department Discharge.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2026
    Article
  7. Article
  8. Article
  9. Article
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

14 authors.

Rachel M SkainsDepartment of Emergency Medicine, Heersink School of Medicine, The University of Alabama at Birmingham.
Jane M HayesDepartment of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston.
Katherine SelmanDepartment of Emergency Medicine, Cooper University Hospital, Cooper Medical School at Rowan University, Camden, New Jersey.
Yue ZhangDivision of Gerontology, Geriatrics, and Palliative Care, Department of Medicine, The University of Alabama at Birmingham.
Phraewa ThatphetDepartment of Emergency Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
Kazuki TodaDepartment of Emergency Medicine/Internal Medicine, Christiana Care Health System, Newark, Delaware.
Bryan D HayesDepartment of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston.
Carla TayesDepartment of Emergency Medicine, UNC School of Medicine, The University of North Carolina at Chapel Hill.
Martin F CaseyDepartment of Emergency Medicine, UNC School of Medicine, The University of North Carolina at Chapel Hill.
Elizabeth MoretonDepartment of Emergency Medicine, UNC School of Medicine, The University of North Carolina at Chapel Hill.
Richard E KennedyDivision of Gerontology, Geriatrics, and Palliative Care, Department of Medicine, The University of Alabama at Birmingham.
Sangil LeeDepartment of Emergency Medicine, Carver College of Medicine, The University of Iowa, Iowa City.
Shan W LiuDepartment of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston.
Geriatric Emergency Department Guidelines Medication Safety Group

Funding

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
Automating Delirium Identification and Risk Prediction in Electronic Health Records (Supplement)R01AG060993 · NIA · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI KENNEDY, RICHARD E · 2019 to 2022
$1.8M
Comprehensive Assessment of Delirium Risk due to MedicationsR21AG084218 · NIA · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI KENNEDY, RICHARD E, SKAINS, RACHEL MICHELLE · 2024 to 2025
$393k
Risk Factors and Time Course of Incident Delirium Among Older Adults in the Emergency Department (ED)R03AG082923 · NIA · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI SKAINS, RACHEL MICHELLE · 2023 to 2024
$297k
NIA NIH HHS R01 AG060993NIA NIH HHS R03 AG082923NIA NIH HHS R21 AG084218NIA NIH HHS R33 AG058926
6 · The paper itself

Abstract

Importance: Given that older adults are at high risk for adverse drug events (ADEs), many geriatric medication programs have aimed to optimize safe ordering, prescribing, and deprescribing practices. Objective: To identify emergency department (ED)-based geriatric medication programs that are associated with reductions in potentially inappropriate medications (PIMs) and ADEs. Data Sources: A systematic search of Scopus, Embase, PubMed, PsycInfo, ProQuest Central, CINAHL, AgeLine, and Cochrane Library was conducted on February 14, 2024, with no date limits applied. Study Selection: Randomized clinical trials or observational studies focused on ED-based geriatric (aged ≥65 years) medication programs that provide ED clinician support to avoid PIMs and reduce ADEs. Data Extraction and Synthesis: Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for abstracting data and the Cochrane risk-of-bias tool were used to assess data quality and validity. Abstract screening and full-text review were independently conducted by 2 reviewers, with a third reviewer acting as an adjudicator. Main Outcomes and Measures: Process (ordering, prescribing, and deprescribing PIM rates) and clinical (ADE, health care utilization, and falls) outcomes. Results: The search strategy identified 3665 unique studies, 98 were assessed for eligibility in full-text review, and 25 studies, with 44 640 participants, were included: 9 clinical pharmacist reviews (with 28 360 participants), 1 geriatrician teleconsultation (with 50 participants), 8 clinician educational interventions (with 5888 participants), 4 computerized clinical decision support systems (CDSS; with 9462 participants), and 3 fall risk-increasing drug (FRID) reviews (with 880 participants). Clinical pharmacist review was not associated with decreased hospital admission or length of stay, but 2 studies showed a 32% reduction in PIMs from deprescribing (odds ratio [OR], 0.68 [95% CI, 0.50-0.92]; P = .01). One study also found that ED geriatrician teleconsultation was associated with enhanced deprescribing of PIMs. Three clinician educational intervention studies showed a 19% reduction in PIM prescribing (OR, 0.81 [95% CI, 0.68-0.96]; P = .02). Two computerized CDSS studies showed a 40% reduction in PIM ordering (OR, 0.60 [95% CI, 0.48-0.74]; P < .001). FRID reviews were not associated with reduced time to first fall or fall recurrence at 12 months. Conclusions and Relevance: In this systematic review and meta-analysis of ED-based geriatric medication safety programs, a multidisciplinary team, including clinical pharmacists and/or geriatricians, was associated with improved PIM deprescribing. Furthermore, computerized CDSS, alone or in combination with ED clinician education, was associated with enhanced geriatric ordering and prescribing practices. These findings will inform the Geriatric ED Guidelines version 2.0 update.

Indexed as

Drug-Related Side Effects and Adverse ReactionsEmergency Service, HospitalInappropriate PrescribingAgedAged, 80 and overDeprescriptionsFemaleHumansPotentially Inappropriate Medication List

Identifiers

PMID40067297
PMCPMC11897843

What OpenQuestion holds

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Registered trials

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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.