Evidence map›Paper›PMID 38991652›Full record

ArticleJournal of the American Medical Directors Association2024

Leadership Perspectives on Nursing Home Operations From Crisis to Control: A Mixed Methods Study.

Liza L Behrens, Erin Kitt-Lewis, Marie Boltz, William A Calo, Erik Lehman, Janice Whitaker, Nicole Osevala, Kimberly Van Haitsma, Lauren J Van Scoy, Jennifer L Kraschnewski

Abstract read
In one paragraph

Article in Journal of the American Medical Directors Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Liza L BehrensNese College of Nursing, The Pennsylvania State University, University Park, PA, USA. Electronic address: llb237@psu.edu.
Erin Kitt-LewisNese College of Nursing, The Pennsylvania State University, University Park, PA, USA.
Marie BoltzNese College of Nursing, The Pennsylvania State University, University Park, PA, USA.
William A CaloCollege of Medicine, The Pennsylvania State University, Hershey, PA, USA.
Erik LehmanCollege of Medicine, The Pennsylvania State University, Hershey, PA, USA.
Janice WhitakerNese College of Nursing, The Pennsylvania State University, University Park, PA, USA.
Nicole OsevalaCollege of Medicine, The Pennsylvania State University, Hershey, PA, USA.
Kimberly Van HaitsmaNese College of Nursing, The Pennsylvania State University, University Park, PA, USA.
Lauren J Van ScoyCollege of Medicine, The Pennsylvania State University, Hershey, PA, USA.
Jennifer L KraschnewskiCollege of Medicine, The Pennsylvania State University, Hershey, PA, USA.

Funding

Penn State Clinical and Translational Science InstituteUL1TR002014 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI KRASCHNEWSKI, JENNIFER L. · 2016 to 2025
$33.7M
Penn State Institutional Career Development CoreKL2TR002015 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI VAN SCOY, LAUREN JODI · 2016 to 2025
$7.8M
A novel use of web-based software to efficiently triage pre-surgical patients basR44TR000045 · NCATS · MEDSLEUTH, INC. · PI KALAMAS, ALICIA GRUBER · 2012 to 2012
$546k
NCATS NIH HHS KL2 TR002015NCATS NIH HHS R44 TR000045NCATS NIH HHS UL1 TR002014NIA NIH HHS L30 AG084137
6 · The paper itself

Abstract

objectivesNursing home (NH) leaders remain challenged to deliver quality care, despite the COVID-19 transition to an endemic phase. This study describes NH leadership perspectives on preparing and maintaining quality care during times of diminishing resources as experienced through the COVID-19 pandemic to gain insight on how best to support NHs moving forward.

designThis was a cross-sectional, parallel convergent mixed methods study. SETTING AND

participantsThis study reports quantitative data from N = 5001 NHs across 12 states along with qualitative data from a subsample of NH leaders (N = 15).

methodsPublicly reported survey data were analyzed using descriptive statistics. Individual in-depth interviews with NH leaders conducted at 12-month follow-up were analyzed using inductive thematic coding organized by a guiding framework. Data were integrated using convergent analysis and a joint display.

resultsNH leaders (licensed administrators, clinical directors, and managers) reported resident and staff infection rates, and access to resources (such as personal protective equipment and testing supplies) that aligned with national trends. Leaders described their NHs (n = 14; 43% rural; 71% not for profit) to be in varied states of operational readiness (standard, contingency, crisis) to support quality infection prevention and control (IPC) at the transition to the endemic COVID-19 phase. Leadership reported continued challenges in addressing resident and staff vaccinations, securing testing supplies, obtaining financial resources to maintain acceptable levels of personal protective equipment, continued staffing shortages, and issues in implementing isolation practices in current facilities. CONCLUSION AND IMPLICATIONS: NH leaders continue to struggle delivering quality IPC care post-pandemic and require focused support in several areas. Clinical practice guidelines should include IPC practices to prevent the infection and spread of any COVID-19 variant in this endemic phase. Policies should support continued reporting of IPC-related metrics and adequate funding to account for the long-term financial burden NHs face.

Indexed as

COVID-19LeadershipNursing HomesSARS-CoV-2Cross-Sectional StudiesFemaleHumansInfection ControlMalePandemicsQuality of Health CareUnited StatesCOVID-19 endemicleadersmixed methodsNursing homesquality of care

Identifiers

PMID38991652
PMCPMC11368636

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.