Speed up discharge planning at the acute stroke unit: A development and external validation study for the early prediction of discharge home.

Veerbeek, Janne Marieke; Ottiger, Beatrice; Cazzoli, Dario; Vanbellingen, Tim; Nyffeler, Thomas (2022). Speed up discharge planning at the acute stroke unit: A development and external validation study for the early prediction of discharge home. Frontiers in neurology, 13, p. 999595. Frontiers Media S.A. 10.3389/fneur.2022.999595

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Background

To reduce healthcare costs, it has become increasingly important to shorten the length of stay in acute stroke units. The goal of this study was to develop and externally validate a decision tree model applicable < 48 h poststroke for discharge home from an acute stroke unit with a short length of stay, and to assess the inappropriate home discharge rate.

Methods

A prospective study including two samples of stroke patients admitted to an acute stroke unit. The outcome was discharge home (yes/no). A classification and regression tree analysis was performed in Sample 1. The model's performance was tested in Sample 2.

Results

In total, 953 patients were included. The final decision tree included the patients' activities of daily living (ADL) performance <48 h poststroke, including motor function, cognition, and communication, and had an area under the curve (AUC) of 0.84 (95% confidence interval 0.76, 0.91). External validation resulted in an AUC of 0.74 (95% confidence interval 0.72, 0.77). None of the patients discharged home were re-admitted < 2 months after discharge to a hospital or admitted to a rehabilitation center for symptoms that had needed inpatient neurorehabilitation.

Conclusions

The developed decision tree shows acceptable external validity in predicting discharge home in a heterogeneous sample of stroke patients, only based on the patient's actual ADL performance <48 h poststroke. Importantly, discharge was safe, i.e., no re-hospitalization was registered. The tree's application to speed up discharge planning should now be further evaluated.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Gerontechnology and Rehabilitation
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research
07 Faculty of Human Sciences > Institute of Psychology

UniBE Contributor:

Cazzoli, Dario, Vanbellingen, Tim, Nyffeler, Thomas

Subjects:

600 Technology > 610 Medicine & health
500 Science > 570 Life sciences; biology
100 Philosophy > 150 Psychology

ISSN:

1664-2295

Publisher:

Frontiers Media S.A.

Language:

English

Submitter:

Pubmed Import

Date Deposited:

04 Oct 2022 10:25

Last Modified:

05 Dec 2022 16:25

Publisher DOI:

10.3389/fneur.2022.999595

PubMed ID:

36188378

Uncontrolled Keywords:

cohort study decision tree discharge prediction stroke stroke unit validation

BORIS DOI:

10.48350/173469

URI:

https://boris.unibe.ch/id/eprint/173469

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