Prediction of disposition within 48 hours of hospital admission using patient mobility scores

Daniel L. Young, Elizabeth Colantuoni, Lisa Aronson Friedman, Jason Seltzer, Kelly Daley, Bingqing Ye, Daniel J. Brotman, Erik H. Hoyer

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Delayed hospital discharges for patients needing validation sets. Compared with patients discharged rehabilitation in a postacute setting can exacerbate to home, patients discharged to a postacute facility hospital-acquired mobility loss, prolong functional were older (median, 64 vs 56 years old) and had recovery, and increase costs. Systematic measurement lower mobility scores at hospital admission (median, of patient mobility by nurses early during 32 vs 41). The final decision tree accurately classified hospitalization has the potential to help identify which the discharge location for 73% (95% CI, 67%-78%) patients are likely to be discharged to a postacute care of patients. This study emphasizes the value of facility versus home. To test the predictive ability of systematically measuring mobility in the hospital and this approach, a machine learning classification tree provides a simple decision tree to facilitate early method was applied retrospectively to a diverse sample discharge planning. Journal of Hospital Medicine of hospitalized patients (N = 761) using training and 2020;15:540-543.

Original languageEnglish (US)
Pages (from-to)540-543
Number of pages4
JournalJournal of Hospital Medicine
Issue number9
StatePublished - Sep 2020

ASJC Scopus subject areas

  • Internal Medicine
  • Leadership and Management
  • Fundamentals and skills
  • Health Policy
  • Care Planning
  • Assessment and Diagnosis


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