Evidence map›Paper›PMID 36637405›Full record

ArticleJournal of the American Geriatrics Society2023

The Modified and Extended Hospital Elder Life Program: A remote model of care to expand delirium prevention.

Tamara G Fong, Jason A Albaum, Molly L Anderson, Sara G Cohen, Shauni Johnson, Mark A Supiano, Philip E Vlisides, Harley L Wade, Lyn Weinberg, Heidi R Wierman and 3 more

Abstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
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

13 authors.

Tamara G FongDepartment of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
Jason A AlbaumBiochemistry Program, Vassar College, Poughkeepsie, New York, USA.
Molly L AndersonDivision of Geriatrics, Maine Medical Center, Portland, Maine, USA.
Sara G CohenCalifornia Pacific Medical Center, Sutter Health, San Francisco, California, USA.
Shauni JohnsonDivision of Geriatrics, Primary Care Institute, Allegheny Health Network, Pittsburgh, Pennsylvania, USA.
Mark A SupianoGeriatrics Division, University of Utah School of Medicine and University of Utah Center on Aging, Salt Lake City, Utah, USA.ORCID 0000-0002-5438-5087
Philip E VlisidesDepartment of Anesthesiology, Michigan Medicine, Ann Arbor, Michigan, USA.
Harley L WadeDivision of Geriatrics, Maine Medical Center, Portland, Maine, USA.
Lyn WeinbergDivision of Geriatrics, Primary Care Institute, Allegheny Health Network, Pittsburgh, Pennsylvania, USA.
Heidi R WiermanDivision of Geriatrics, Maine Medical Center, Portland, Maine, USA.
Wendy ZacharyCalifornia Pacific Medical Center, Sutter Health, San Francisco, California, USA.
Sharon K InouyeAging Brain Center, Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Harvard Medical School, Boston, Massachusetts, USA.
HELP-ME Writing Group

Funding

NIDUS III: Advanced-Stage Development and Utilization of the NIDUS Research Infrastructure to Advance Interdisciplinary Aging Research inDeliriumR33AG071744 · NIA · JOHNS HOPKINS UNIVERSITY · PI John W. Devlin, Esther Seunghee Oh · 2021 to 2026
$4.7M
NIA NIH HHS R33 AG071744
6 · The paper itself

Abstract

backgroundDelirium is a common complication of hospitalization and is associated with poor outcomes. Multicomponent delirium prevention strategies such as the Hospital Elder Life Program (HELP) have proven effective but rely on face-to-face intervention protocols and volunteer staff, which was not possible due to restrictions during the COVID-19 pandemic. We developed the Modified and Extended Hospital Elder Life Program (HELP-ME), an innovative adaptation of HELP for remote and/or physically distanced applications.

methodsHELP-ME protocols were adapted from well-established multicomponent delirium prevention strategies and were implemented at four expert HELP sites. Each site contributed to the protocol modifications and compilation of a HELP-ME Operations Manual with standardized protocols and training instructions during three expert panel working groups. Implementation was overseen and monitored during seven learning sessions plus four coaching sessions from January 8, 2021, through September 24, 2021. Feasibility of implementing HELP-ME was measured by protocol adherence rates. Focus groups were conducted to evaluate the acceptability, provide feedback, and identify facilitators and barriers to implementation.

resultsA total of 106 patients were enrolled across four sites, and data were collected for 214 patient-days. Overall adherence was 82% (1473 completed protocols/1798 patient-days), achieving our feasibility target of >75% overall adherence. Individual adherence rates ranged from 55% to 96% across sites for the individual protocols. Protocols with high adherence rates included the nursing delirium protocol (96%), nursing medication review (96%), vision (89%), hearing (87%), and orientation (88%), whereas lower adherence occurred with fluid repletion (64%) and range-of-motion exercises (55%). Focus group feedback was generally positive for acceptability, with recommendations that an optimal approach would be hybrid, balancing in-person and remote interventions for potency and long-term sustainability.

conclusionsHELP-ME was fully implemented at four HELP sites, demonstrating feasibility and acceptability. Testing hybrid approaches and evaluating effectiveness is recommended for future work.

Indexed as

COVID-19DeliriumAgedHospitalizationHospitalsHumansPandemicsCOVID-19deliriumdelirium preventionmulticomponent

Identifiers

PMID36637405
PMCPMC10023347

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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.