Evidence map›Paper›PMID 42070673›Full record

ArticleJournal of stroke and cerebrovascular diseases : the official journal of National Stroke Association2026

Factors associated with discharge to skilled nursing despite a clinical recommendation for inpatient rehabilitation.

Kiersten M McCartney, Ruiqi Yan, Lin Xu, Rujula Upasani, Stephen Hampton, Robert E Burke, M Kit Delgado, Kimberly J Waddell

Abstract readComparative StudyMulticenter Study
In one paragraph

Article in Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association, 2026. 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

8 authors.

Kiersten M McCartneyDepartment of Physical Medicine and Rehabilitation, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA. Electronic address: kiersten.mccartney@pennmedicine.upenn.edu.
Ruiqi YanLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA; Penn Medicine Nudge Unit, University of Pennsylvania, Philadelphia, Pennsylvania, USA; Division of General Internal Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA. Electronic address: Ruiqi.yan@pennmedicine.upenn.edu.
Lin XuLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA; Penn Medicine Nudge Unit, University of Pennsylvania, Philadelphia, Pennsylvania, USA; Division of General Internal Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA. Electronic address: Lin.xu@pennmedicine.upenn.edu.
Rujula UpasaniCollege of Medicine, Drexel University, Philadelphia, Pennsylvania, USA. Electronic address: rnu@drexel.edu.
Stephen HamptonDepartment of Physical Medicine and Rehabilitation, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA. Electronic address: Stephen.hamptom@pennmedicine.upenn.edu.
Robert E BurkeLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA; Division of General Internal Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA; Division of Hospital Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA. Electronic address: Robert.burke2@pennmedicine.upenn.edu.
M Kit DelgadoLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA; Penn Medicine Nudge Unit, University of Pennsylvania, Philadelphia, Pennsylvania, USA; Department of Emergency Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA. Electronic address: Mucio.delgado@pennmedicine.upenn.edu.
Kimberly J WaddellDepartment of Physical Medicine and Rehabilitation, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA. Electronic address: Kimberly.waddell@pennmedicine.upenn.edu.

Funding

STATISTICAL DATA ENCLAVE COREP30AG012836 · NIA · UNIVERSITY OF PENNSYLVANIA · PI KOHLER, HANS-PETER · 1999 to 2024
$14.0M
BRIAN INJURY TRAINING GRANTT32NS043126 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI Douglas Hamilton Smith · 2003 to 2026
$5.9M
NIA NIH HHS P30 AG012836NINDS NIH HHS T32 NS043126
6 · The paper itself

Abstract

background and purposeTwo-thirds of adults with stroke receive post-acute rehabilitation to enhance recovery. For many, higher-intensity, but more costly, rehabilitation at an inpatient rehabilitation facility (IRF) is associated with improved outcomes compared to a skilled nursing facility (SNF). Little is known on how often patients recommended for IRF discharge actually discharge to SNF. Ensuring patients receive post-acute care that aligns with clinical need is crucial for long-term outcomes. This study examined how often patients recommended for an IRF discharge after stroke hospitalization discharge to a SNF, and examined the factors associated with this discrepant discharge.

methodsRetrospective cohort study of adults hospitalized for stroke in a multi-hospital health system between January 1, 2018 - December 31, 2024. Electronic health record data identified physical and occupational therapy recommendations for an IRF discharge and the post-discharge location (IRF or SNF). A generalized logistic regression examined factors associated with SNF discharge.

resultsAmong 3388 stroke hospitalizations which recommended IRF, 3092 (91%) discharged to IRF and 296 (9%) discharged to SNF. Enrollment in Medicare Advantage (OR=2.80, 95%CI [1.68, 4.68]), traditional Medicare (OR=2.05, 95%CI [1.22, 3.43]), age ≥ 85 years (OR=1.98, 95%CI [1.17, 3.37]), dependent pre-admission mobility (OR=1.81, 95%CI [1.21, 2.70]), and acute hospital length of stay (OR=1.03, 95%CI=[1.02, 1.04] were most strongly associated with a discrepant discharge.

conclusionsAmong those recommended for IRF discharge, a SNF discharge was driven by a combination of both clinical and non-clinical factors. These results underscore the need to consider how both clinical and non-clinical factors influence this process and may impact long-term outcomes.

Indexed as

Patient DischargeSkilled Nursing FacilitiesStrokeStroke RehabilitationAgedAged, 80 and overFemaleFunctional StatusGuideline AdherenceHumansMaleMiddle AgedRecovery of FunctionRetrospective StudiesRisk FactorsTime FactorsDischargeInpatient rehabilitationPost-acuteSkilled nursingStroke

Identifiers

PMID42070673
PMCPMC13208100

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.