Association of Longitudinal Mobility Levels in the Hospital and Injurious Inpatient Falls.

Am J Phys Med Rehabil

From the Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland (EH, DY); Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland (VK, JYZ); Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland (EC); Department of Nursing, The Johns Hopkins Hospital, Baltimore, Maryland (HF); Malone Center for Engineering in Healthcare and Johns Hopkins Institute for Assured Autonomy, Baltimore, Maryland (AD); Department of Physical Therapy, University of Nevada Las Vegas, Las Vegas, Nevada (EH, DY); and Department of Civil and Systems Engineering, Malone Center for Engineering in Healthcare, Center for Systems Science and Engineering, Whiting School of Engineering, Baltimore, Maryland (KG).

Published: March 2024

Falls are one of the most common adverse events in hospitals, and patient mobility is a key risk factor. In hospitals, risk assessment tools are used to identify patient-centered fall risk factors and guide care plans, but these tools have limitations. To address these issues, we examined daily patient mobility levels before injurious falls using the Johns Hopkins Highest Level of Mobility, which quantifies key patient mobility milestones from low-level to community distances of walking. We aimed to identify longitudinal characteristics of patient mobility before a fall to help identify fallers before the event. Conducting a retrospective matched case-control analysis, we compared mobility levels in the days leading up to an injurious fall between fallers and nonfallers. We observed that patients who experienced an injurious fall, on average, spent 28% of their time prefall at a low mobility level (Johns Hopkins Highest Level of Mobility levels 1-4), compared with nonfallers who spent 19% of their time at a low mobility level (mean absolute difference, 9%; 95% confidence interval, 1%-16%; P = 0.026; relative difference, 44%). This suggests that assessing a patient's mobility levels over time can help identify those at an increased risk for falls and enable hospitals to manage mobility problems more effectively.

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Source
http://dx.doi.org/10.1097/PHM.0000000000002355DOI Listing

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