Evidence map›Paper›PMID 41733928›Full record

ArticleJournal of the American Geriatrics Society2026

What's in a Number: Do Transfer Rates Reflect Nursing Home Quality?

Debra Saliba, Vincent Mor, Kisa A Hilliard, Amy L Mochel, Margaret Baumann, Rebecca Boxer, Heather D'Adamo, Hiroshi Gotanda, Kim W House, Seema Joshi and 8 more

Abstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2026. 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

18 authors.

Debra SalibaGRECC and HSR Center of Innovation, Greater Los Angeles Veterans Administration Health System, Los Angeles, California, USA.
Vincent MorDepartment of Health Services, Policy & Practice, Brown University School of Public Health, Providence, Rhode Island, USA.
Kisa A HilliardBorun Center, University of California Los Angeles, Los Angeles, California, USA.
Amy L MochelCenter of Innovation, Providence Veterans Administration Medical Center, Providence, Rhode Island, USA.
Margaret BaumannJesse Brown VA Geriatrics & Extended Care, Chicago, Illinois, USA.
Rebecca BoxerDepartment of Medicine, University of California Davis, Sacramento, California, USA.
Heather D'AdamoDepartment of Veterans Affairs Greater Los Angeles Healthcare System, Geriatrics and Extended Care, Los Angeles, California, USA.
Hiroshi GotandaDepartment of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Kim W HouseJoseph Maxwell Cleland VA Medical Center, Atlanta, Georgia, USA.
Seema JoshiDwight D. Eisenhower VA Medical Center, Leavenworth, Kansas, USA.
Linda SohnDepartment of Veterans Affairs Greater Los Angeles Healthcare System, Geriatrics and Extended Care, Los Angeles, California, USA.
Arti TayadeVA Puget Sound Health Care System, University of Washington, Seattle, Washington, USA.
Sarah TubbesingDepartment of Veterans Affairs Greater Los Angeles Healthcare System, Geriatrics and Extended Care, Los Angeles, California, USA.
Dan R BerlowitzDepartment of Public Health, University of Massachusetts Lowell, Lowell, Massachusetts, USA.ORCID 0000-0002-8783-5611
Orna IntratorJames J. Peters VA Medical Center, Bronx, New York, USA.
Roee GutmanDepartment of Biostatistics, Brown University School of Public Health, Providence, Rhode Island, USA.
Ciaran S PhibbsPalo Alto Veterans Administration Medical Center, Palo Alto, California, USA.
Joseph G OuslanderFlorida Atlantic University Schmidt College of Medicine, Boca Raton, Florida, USA.ORCID 0000-0003-3985-5797

Funding

HSRD VA I01 HX000978US Department of Veterans Affairs CRE-12-025
6 · The paper itself

Abstract

backgroundHospitalization rates from nursing homes (NHs) have gained traction as pragmatic quality measures that can be derived from claims data. However, claims-based hospitalization measures do not account for clinical complexity and the extent to which they reflect quality of care or quality of transfer decision making is unknown. We aim to examine agreement between a claims-based measure of potentially avoidable hospitalizations and expert clinician review of transfer decision making and care quality.

methodsWe randomly selected 252 hospital transfers across eight Veterans Administration (VA) NHs, known as Community Living Centers (CLCs). Eleven expert clinicians independently completed Structured Implicit Reviews (SIRs) of medical records to assess: (1) whether the transfer decision was appropriate (i.e., hospital was the lowest safe level-of-care given the resident's acute condition); (2) quality of care for evaluation or treatment of the acute change (adequate management of acute change), (3) quality of care for chronic conditions and preventing decline. We used VA Corporate Data Warehouse (CDW) data to determine a claims-based measure of potentially avoidable hospitalization.

resultsCDW data were available for 242 VA hospitalizations. The claims-based measure categorized 29 (12%) hospitalizations as potentially avoidable; only 2 of which matched the 20 SIR identified as inappropriate decisions to transfer. Furthermore, the claims-based measure flagged only 5 of 33 cases rated as inadequate treatment of acute decline and 6 of 17 rated as poor quality of chronic disease or preventive care.

conclusionsIn a geographically diverse sample of CLC transfers, independent clinical experts' judgments of transfer decision appropriateness, quality of care for acute decline, and quality of chronic care differ from a claims-based potentially avoidable hospitalizations measure. Findings underscore the need for nuanced clinical consideration of hospitalization metrics for assessing quality and for understanding which aspects of care should be addressed to safely reduce NH transfers to hospitals.

Indexed as

HospitalizationNursing HomesPatient TransferQuality of Health CareAgedAged, 80 and overFemaleHumansMaleNursing Home ResidentsUnited StatesUnited States Department of Veterans Affairsappropriatenesshospitalizationsnursing homesqualitytransfersveterans administration

Identifiers

PMID41733928
PMCPMC13135460

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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.