Creating a Safer Patient Room Environment: The Contribution of Patient Bed Height

Elderly patient falls are expensive and may cause serious harm. Studies have identified the sit-to-stand-and-walk (STSW) task as the task where the greatest number of elderly patient falls occur. There is a great need to identify the particular movement and environmental conditions that lead to these elderly patient falls. This study begins to address this gap by evaluating the elderly patient during self-selected hospital bed egress. Using an observed fall risk episode (FRE) as a fall proxy, statistically significant parameters were identified which include bed height, pausing prior to initiating gait, level of fall risk, and Stand phase. Low bed height was identified as the least safe bed height. Patient-specific bed height (PSBH) using the patient’s lower leg length (LLL) is recommended. In addition, suggested guidelines are presented for clinical application in setting PSBH without measuring the patient’s LLL.

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Evaluation and intervention in the risk of falls in institutionalized elderly using smartphone sensors (Preprint)

10.2196/preprints.29265 ◽

2021 ◽

Author(s):

María Pilar Molés Julio ◽

José Francisco Pedrero-Sánchez ◽

María Viecenta Lucas-Miralles ◽

Irene Carmona-Fortuño ◽

David Garrido-Jaén ◽

...

Keyword(s):

Nursing Homes ◽

Functional Capacity ◽

Fall Risk ◽

Muscle Power ◽

Inertial Sensor ◽

Age Groups ◽

The Elderly ◽

Test Execution ◽

Sit To Stand ◽

Experimental Group

BACKGROUND Aging produces a deterioration in the older person and this affects the neuromuscular system among others, reducing muscle mass, strength and muscle power and this generates a decrease in functional capacity in the elderly, can cause falls and disability. OBJECTIVE The aim of this study is to analyze the ability to know the functional capacity and fall risk of elderly people in nursing homes through a novel short-test using a single inertial sensor embedded in an Android device. METHODS Study participants included 47 older people (over 55 years old) resided in two nursing homes. Functional assessment with FallSkip® which includes static balance, gait analysis, lower limb power when sit to stand, test execution time and reaction time. The patients were randomly divided into two study groups, control and experimental group. The experimental group underwent individualized rehabilitation therapy based on the results obtained by the modified Timed Up and Go falls risk test. Subsequently, the results obtained between the two residences and between the experimental groups were compared. RESULTS 70% of people in nursing homes are over 75 years old, which the female participants were mostly found in the older age groups, unlike their male counterparts, who were concentrated in the younger age groups. When comparing the anthropometric variables and clinical scales for the two nursing homes no statistically significant differences appeared (p > 0.05) only on the fall risk score (p < 0.05) and the sit to stand power (p < 0.05). CONCLUSIONS The comfort of evaluating the functional status of the elderly in the nursing homes by an objective and simple functional test has allowed us to carry out individualized rehabilitation interventions for each participant; as well as to know the functional level of the people in the nursing homes.

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Fall risk screening in the elderly: A comparison of the minimal chair height standing ability test and 5-repetition sit-to-stand test

Archives of Gerontology and Geriatrics ◽

10.1016/j.archger.2016.03.004 ◽

2016 ◽

Vol 65 ◽

pp. 133-139 ◽

Cited By ~ 11

Author(s):

Nadia Reider ◽

Catherine Gaul

Keyword(s):

Fall Risk ◽

The Elderly ◽

Risk Screening ◽

Ability Test ◽

Stand Test ◽

Sit To Stand ◽

Fall Risk Screening

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Development of a Scale to Identify the Fall-Prone Patient

Canadian Journal on Aging / La Revue canadienne du vieillissement ◽

10.1017/s0714980800008576 ◽

1989 ◽

Vol 8 (4) ◽

pp. 366-377 ◽

Cited By ~ 221

Author(s):

Janice M. Morse ◽

Robert M. Morse ◽

Suzanne J. Tylko

Keyword(s):

Elderly Patient ◽

Predictive Value ◽

Interrater Reliability ◽

The Elderly ◽

Analysis Procedure ◽

Prevention Strategies ◽

Risk Of Falling ◽

Patient Falls ◽

A Prospective Study ◽

Patient At Risk

ABSTRACTPatient falls are a serious problem, contributing to the morbidity and mortality of the elderly patient. This study reports on the development of the Morse Fall Scale. The scale consists of six scored items and discriminant analysis correctly classifies 80.5% of the patients. Validation of the scale by computer modeling was conducted. Data were randomly split and that analysis procedure repeated. Variables were obtained and weighted using half of these data, and these weights were tested on the remaining data. Similar results were obtained. Sensitivity of the scale was 78% and the positive predictive value, 10.3%. Conversely, specificity was 83% and the negative predictive value, 99.3%. Interrater reliability scores were r=.96. A prospective study in three clinical areas showed that the scale is sensitive to different patient conditions and to length of stay. Thus, the scale permits identification of the patient at risk of falling so that prevention strategies may be targeted to those individuals.

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Development of a Novel Computational Model for Evaluating Fall Risk in Patient Room Design

HERD Health Environments Research & Design Journal ◽

10.1177/1937586720959766 ◽

2020 ◽

pp. 193758672095976

Author(s):

Roya Sabbagh Novin ◽

Ellen Taylor ◽

Tucker Hermans ◽

Andrew Merryweather

Keyword(s):

Risk Assessment ◽

Computational Model ◽

Fall Risk ◽

Assessment Tools ◽

Optimization Approach ◽

Patient Room ◽

Patient Falls ◽

Room Design ◽

Risk Of Fall ◽

The Relationship

Objectives: This study proposes a computational model to evaluate patient room design layout and features that contribute to patient stability and mitigate the risk of fall. Background: While common fall risk assessment tools in nursing have an acceptable level of sensitivity and specificity, they focus on intrinsic factors and medications, making risk assessment limited in terms of how the physical environment contributes to fall risk. Methods: We use literature to inform a computational model (algorithm) to define the relationship between these factors and the risk of fall. We use a trajectory optimization approach for patient motion prediction. Results: Based on available data, the algorithm includes static factors of lighting, flooring, supportive objects, and bathroom doors and dynamic factors of patient movement. This preliminary model was tested using four room designs as examples of typical room configurations. Results show the capabilities of the proposed model to identify the risk associated with different room layouts and features. Conclusions: This innovative approach to room design evaluation and resulting estimation of patient fall risk show promise as a proactive evidence-based tool to evaluate the relationship of potential fall risk and room design. The development of the model highlights the challenge of heterogeneity in factors and reporting found in the studies of patient falls, which hinder our understanding of the role of the built environment in mitigating risk. A more comprehensive investigation comparing the model with actual patient falls data is needed to further refine model development.

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