Revealing the tension: The relationship between high fall risk categorization and low patient mobility

Abstract

Background Using an inpatient fall risk assessment tool helps categorize patients into risk groups which can then be targeted with fall prevention strategies. While potentially important in preventing patient injury, fall risk assessment may unintentionally lead to reduced mobility among hospitalized patients. Here we examined the relationship between fall risk assessment and ambulatory status among hospitalized patients. Methods We conducted a retrospective cohort study of consecutively admitted adult patients (n = 48,271) to a quaternary urban hospital that provides care for patients of broad socioeconomic and demographic backgrounds. Non‐ambulatory status, the primary outcome, was defined as a median Johns Hopkins Highest Level of Mobility <6 (i.e., patient walks less than 10 steps) throughout hospitalization. The primary exposure variable was the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) category (Low, Moderate, High). The capacity to ambulate was assessed using the Activity Measure for Post‐Acute Care (AM‐PAC). Multivariable regression analysis controlled for clinical demographics, JHFRAT items, AM‐PAC, comorbidity count, and length of stay. Results 8% of patients at low risk for falls were non‐ambulatory, compared to 25% and 54% of patients at moderate and high risk for falls, respectively. Patients categorized as high risk and moderate risk for falls were 4.6 (95% CI: 3.9–5.5) and 2.6 (95% CI: 2.4–2.9) times more likely to be non‐ambulatory compared to patients categorized as low risk, respectively. For patients with high ambulatory potential (AM‐PAC 18–24), those categorized as high risk for falls were 4.3 (95% CI: 3.5–5.3) times more likely to be non‐ambulatory compared to patients categorized as low risk. Conclusions Patients categorized into higher fall risk groups had decreased mobility throughout their hospitalization, even when they had the functional capacity to ambulate.

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

“…10,[18][19][20] Lower mobility levels may also indicate that a patient has more pain or certain restrictions that may alter the way they move around, which may increase their risk. 4,21,22 These results suggest that incorporating more precise measures of patient mobility on a regular basis may improve care plan strategies to mitigate fall risk. In this study, we used the JH-HLM that captures a range of patient mobility milestones and is scored daily as part of standard of care in the electronic medical record.…”

“…Spending more time with low mobility may also contribute to a physiologic decline and increase a patient’s fall risk, such as increasing frailty and orthostatic intolerance 10,18–20 . Lower mobility levels may also indicate that a patient has more pain or certain restrictions that may alter the way they move around, which may increase their risk 4,21,22 …”

“…Falls are one of the most common adverse events in hospitals, and they can lead to serious injury and even death 1,2 . Mobility issues are a significant risk factor for falls, accounting for up to 30% of falls in hospitals 3,4 . To reduce the risk of falls, hospitals need to ensure that they are managing mobility problems effectively.…”

Towards human-centered AI and robotics to reduce hospital falls: finding opportunities to enhance patient-nurse interactions during toileting

“…Additionally, On the “high-tech” front, Artificial Intelligence (AI) approaches could provide better fall risk predictions ( Marschollek et al, 2012 ; Novin et al, 2021 ). However, some research has indicated that individuals who are labeled as higher risk of falls may be given less mobility opportunities, which can also lead to poorer outcomes ( Capo-Lugo et al, 2023 ). Assistive robots could reduce the burden on nursing staff by supporting their patient care activities ( Pepito and Locsin, 2019 ; Christoforou et al, 2020 ).…”