Evidence map›Paper›PMID 41077066›Full record

ArticleJournal of the American Medical Directors Association2025

Patterns and Predictors of Reopening Nursing Homes to Visitors During the COVID-19 Pandemic.

Jiaying Lu, John R Bowblis, Shuang Li, Yong-Fang Kuo, Jennifer Heston-Mullins, James S Goodwin, Huiwen Xu

Abstract read
In one paragraph

Article in Journal of the American Medical Directors Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Jiaying LuNell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA.
John R BowblisDepartment of Economics, Farmer School of Business, Miami University, Oxford, OH, USA; Scripps Gerontology Center, Miami University, Oxford, OH, USA.
Shuang LiSealy Center on Aging, University of Texas Medical Branch, Galveston, TX, USA.
Yong-Fang KuoSealy Center on Aging, University of Texas Medical Branch, Galveston, TX, USA; School of Public and Population Health, University of Texas Medical Branch, Galveston, TX, USA.
Jennifer Heston-MullinsScripps Gerontology Center, Miami University, Oxford, OH, USA.
James S GoodwinSealy Center on Aging, University of Texas Medical Branch, Galveston, TX, USA; Department of Internal Medicine, University of Texas Medical Branch, Galveston, TX, USA.
Huiwen XuNell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA. Electronic address: huiwen.xu@emory.edu.

Funding

UTMB OAIC Research Education Component (REC)P30AG024832 · NIA · UNIVERSITY OF TEXAS MEDICAL BR GALVESTON · PI JAMES S. GOODWIN, MD, MELISSA M. MORROW · 2005 to 2026
$26.7M
The effectiveness and consequences of visitation bans in nursing homesR01AG081282 · NIA · UNIVERSITY OF TEXAS MED BR GALVESTON · PI Huiwen Xu · 2023 to 2026
$1.5M
Alzheimer's Special Care Units in Nursing Homes: Racial and Ethnic Disparities, Resident Outcomes, and State PoliciesR01AG087296 · NIA · EMORY UNIVERSITY · PI Huiwen Xu · 2024 to 2026
$1.2M
NIA NIH HHS P30 AG024832NIA NIH HHS R01 AG081282NIA NIH HHS R01 AG087296
6 · The paper itself

Abstract

objectivesStatewide restrictions on visitors to nursing homes were widely used during the COVID-19 pandemic. This study examines the patterns and predictors of allowing outside visitors after a statewide ban on visitors was lifted.

designA secondary analysis of publicly available data. SETTING AND

participantsA total of 847 Ohio nursing homes that reported visitor policy data.

methodsWe obtained weekly visitor policies (October 29, 2020, to April 15, 2021) from the Ohio Long-Term Care Facility Visitation Dashboard. We merged visitor policies with resident, facility, and COVID-19 factors and conducted 2-level (nursing home, county) Hierarchical Generalized Linear Mixed models with backward variable selection to examine predictors of allowing visitors and reinstating bans.

resultsWithin 3 weeks of lifting the ban in Ohio on December 10, 2020, 51% of the 653 Ohio nursing homes with available data allowed visitors. The proportion of facilities that allowed visitors declined to 36% by November 25, 2020, but began increasing in late February and reached 81% by April 15, 2021. Of the 495 nursing homes that initially opened to visitors, 35% of them later reinstated bans, with half of these later allowing visitors again before March 2021. When nursing homes were first allowed to reopen, facilities with a recent COVID-19 infection among residents or staff were much less likely to allow visitors (relative risk, 0.38; 95% CI, 0.31-0.47). During a statewide increase in community COVID-19 infection rates, nursing homes in counties with higher rates were less likely to allow visitors (relative risk, 0.80; 95% CI, 0.63-0.99). Nursing homes that had more beds (relative risk, 1.61; 95% CI, 1.35-1.92) and higher overall 5-star ratings (relative risk, 1.27; 95% CI, 1.08-1.49) were more likely to reinstate bans. CONCLUSIONS AND IMPLICATIONS: The pattern of reopening nursing homes to visitors was marked by a slow progression and dynamic policy changes over time. The 2 primary predictors associated with reopening were facility and community COVID-19 status.

Indexed as

COVID-19Nursing HomesVisitors to PatientsAgedHumansOhioPandemicsSARS-CoV-2allowing visitorsCOVID-19 pandemicNursing homes

Identifiers

PMID41077066
PMCPMC12669806

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.