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Prediction of Disposition Within 48 Hours of Hospital Admission Using Patient Mobility Scores.

Authors :
Young DL
Colantuoni E
Friedman LA
Seltzer J
Daley K
Ye B
Brotman DJ
Hoyer EH
Source :
Journal of hospital medicine [J Hosp Med] 2020 Sep; Vol. 15 (9), pp. 540-543.
Publication Year :
2020

Abstract

Delayed hospital discharges for patients needing rehabilitation in a postacute setting can exacerbate hospital-acquired mobility loss, prolong functional recovery, and increase costs. Systematic measurement of patient mobility by nurses early during hospitalization has the potential to help identify which patients are likely to be discharged to a postacute care facility versus home. To test the predictive ability of this approach, a machine learning classification tree method was applied retrospectively to a diverse sample of hospitalized patients (N = 761) using training and validation sets. Compared with patients discharged to home, patients discharged to a postacute facility were older (median, 64 vs 56 years old) and had lower mobility scores at hospital admission (median, 32 vs 41). The final decision tree accurately classified the discharge location for 73% (95% CI, 67%-78%) of patients. This study emphasizes the value of systematically measuring mobility in the hospital and provides a simple decision tree to facilitate early discharge planning.

Details

Language :
English
ISSN :
1553-5606
Volume :
15
Issue :
9
Database :
MEDLINE
Journal :
Journal of hospital medicine
Publication Type :
Academic Journal
Accession number :
31869298
Full Text :
https://doi.org/10.12788/jhm.3332