Prediction of Disposition Within 48 Hours of Hospital Admission Using Patient Mobility Scores
Document Type
Article
Publication Date
12-18-2019
Publication Title
Journal of Hospital Medicine
Volume
15
Issue
10
First page number:
540
Last page number:
543
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.
Disciplines
Medicine and Health Sciences | Physical Therapy | Rehabilitation and Therapy
Language
English
Repository Citation
Young, D. L.,
Colantuoni, E.,
Friedman, L. A.,
Seltzer, J.,
Daley, K.,
Ye, B.,
Brotman, D. J.,
Hoyer, E. H.
(2019).
Prediction of Disposition Within 48 Hours of Hospital Admission Using Patient Mobility Scores.
Journal of Hospital Medicine, 15(10),
540-543.
http://dx.doi.org/10.12788/jhm.3332