PDF icon Download PDF
Appl Clin Inform 2025; 16(04): 753-759
DOI: 10.1055/a-2576-1505
Research Article

From Steps to Mobility Levels: Validating a Consumer-Grade Activity Monitor for Automated Recording of Patient Mobility in Hospitals

Jan Stenum
1   Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
,
Eric Stewart
1   Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
,
Daniel L. Young
1   Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
2   Department of Physical Therapy, University of Nevada Las Vegas, Las Vegas, Nevada, United States
,
Ioannis Collector
1   Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
,
Karli Funk
3   Department of Physical Medicine and Rehabilitation, The Johns Hopkins Hospital, Baltimore, Maryland, United States
,
Lydia Vincent
3   Department of Physical Medicine and Rehabilitation, The Johns Hopkins Hospital, Baltimore, Maryland, United States
,
Elizabeth Colantuoni
4   Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States
,
Erik H. Hoyer
1   Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
› Author Affiliations
Funding None.
› Further Information
Also available ateRef
   Permissions and Reprints
Preview

Abstract

Background

Patient mobility during hospitalization is essential for high-quality healthcare as mobility is linked to physical function and quality of life. The Johns Hopkins Highest Level of Mobility (JH-HLM) scale is a validated method to assess mobility in hospitalized patients. Although the JH-HLM is widely utilized, it has limitations including ceiling effects, unobserved mobility events going unrecorded, and the staff time needed to observe and document.

Objectives

We explored the feasibility of using a consumer-grade activity monitor (Fitbit) to predict JH-HLM scores and address these limitations.

Methods

JH-HLM scores and step counts were recorded simultaneously using behavioral mapping and analyzed over 1-hour periods among inpatients. We predicted JH-HLM scores based on step counts by fitting ordinal logistic regressions, according to three categorizations of JH-HLM scores reflecting increasing mobility-granularity.

Results

We collected data for 189 patient-hours in a cohort of 20 participants. Step counts increased with higher JH-HLM mobility scores. When predicting JH-HLM scores from step counts, there was a trade-off between accuracy and mobility granularity: overall accuracy was 75% when categorizing patient-hours as immobility (JH-HLM of 1 to 5) or mobility (JH-HLM of 6 to 8); accuracy was 68% when categorizing immobility, shorter walking behavior (JH-HLM of 6 to 7), and longer walking behavior (JH-HLM of 8); accuracy was 61% when categorizing immobility and three progressively higher volumes of walking (JH-HLM of 6, 7 and 8).

Conclusion

Step counts from the activity monitor could be used to predict whether a patient was immobile or mobile but may lack the sensitivity to accurately predict specific mobility levels.

Keywords

Fitbit - step count - JH-HLM - mobility - automation

Protection of Human and Animal Subjects

Institutional review board approval (IRB00205546) for this study was obtained from the Johns Hopkins University Institutional Review Board. Oral consent was obtained from all participating patients at the beginning of each observation day.




Publication History

Received: 30 September 2024

Accepted: 05 April 2025

Article published online:
06 August 2025

© 2025. Thieme. All rights reserved.

Georg Thieme Verlag KG
Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany