Quality Indicators as Predictors of Future Inspection Performance in Ontario Nursing Homes

Mashouri, Pouria; Taati, Babak; Quirt, Hannah; Iaboni, Andrea

doi:10.1016/j.jamda.2019.09.007

Cited by 8 publications

(4 citation statements)

References 30 publications

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“…Reduced physical restraint can be considered a quality indicator of long‐term care (Fashaw et al, 2020 ; Mashouri et al, 2020 ) and is, therefore, associated with physical injuries in the older people, such as immobilization leading to functional decline, pressure sores, falls and cognitive decline (Hofmann & Hahn, 2014 ), depression (Fariña‐López et al, 2013 ), and quality of life (Hubbs, 2013 ; Möhler et al, 2012 ). None of the included trials investigated the impact of the restraint reduction program on physical functioning, pressure sores and depression of residents in nursing homes.…”

Section: Discussionmentioning

confidence: 99%

The optimal intervention for preventing physical restraints among older adults living in the nursing home: A systematic review

Liang

Huang

2023

Nursing Open

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Aim This study aimed to evaluate the effectiveness of restraint reduction programs for nursing home care providers in enforcing physical restraint on residents and identify the best strategies for such programs. Design Systematic Review. Methods We searched for randomized controlled trials published until February 2021 for systematic review. The systematic review captured multifactorial interventions, education and consultation measures, including nursing home residents' and care providers' results. Study quality was assessed using the Cochrane Collaboration criteria. Results In all seven trials, the interventions were led by a nurse specialist or unit leader and targeted at care providers. Five of the restraint reduction programs effectively reduced the rate of physical restraint use; two increased knowledge of restraint reduction for care providers; and one each promoted positive attitudes and behaviours. Duration of at least 6 weeks significantly improved the knowledge of care providers.

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Section: Discussionmentioning

confidence: 99%

The optimal intervention for preventing physical restraints among older adults living in the nursing home: A systematic review

Liang

Huang

2023

Nursing Open

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“…There are multiple concerns regarding the feasibility of these approaches in the LTC population [10]- [12]. For example, over 60% of LTC residents have dementia [13] and many have difficulty following instructions and steps required to complete clinical fall risk assessments. It is therefore desirable to develop and validate methods that could unobtrusively assess fall risk in this population.…”

Section: Related Workmentioning

confidence: 99%

Ambient Monitoring of Gait and Machine Learning Models for Dynamic and Short-Term Falls Risk Assessment in People With Dementia

Korhani¹,

Taati²,

Iaboni³

et al. 2023

Preprint

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“…There are multiple concerns regarding the feasibility of these approaches in the LTC population [10], [13], [14]. For example, over 60% of LTC residents have dementia [5] and many have difficulty following instructions and steps required to complete clinical fall risk assessments. It is therefore desirable to develop and validate methods that could unobtrusively assess fall risk in this population.…”

Section: Related Workmentioning

confidence: 99%

“…Falls are one of the leading causes of injury, loss of independence, and mortality in older adults [1].In particular, the annual incidence of falls in older adults with dementia is 70%-80% [2], approximately twice the incidence of falls in cognitively healthy older adults [3], [4]. In long-term care (LTC) homes, where the majority of residents have dementia [5], about 25% of falls result in injuries, 15% severe enough to require medical care [6]. Since falls have a major impact on functional ability, caregiver burden, and quality of life, fall prevention has become an important public health goal in high-risk populations such as people with dementia and residents of LTC homes [7].…”

Section: Introductionmentioning

confidence: 99%

Ambient Monitoring of Gait and Machine Learning Models for Dynamic and Short-Term Falls Risk Assessment in People With Dementia

Adeli

Korhani

Sabo

et al. 2023

IEEE J. Biomed. Health Inform.

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Falls are a leading cause of morbidity and mortality in older adults with dementia residing in long-term care. Having access to a frequently updated and accurate estimate of the likelihood of a fall over a short time frame for each resident will enable care staff to provide targeted interventions to prevent falls and resulting injuries. To this end, machine learning models to estimate and frequently update the risk of a fall within the next 4 weeks were trained on longitudinal data from 54 older adult participants with dementia. Data from each participant included baseline clinical assessments of gait, mobility, and fall risk at the time of admission, daily medication intake in three medication categories, and frequent assessments of gait performed via a computer vision-based ambient monitoring system. Systematic ablations investigated the effects of various hyperparameters and feature sets and experimentally identified differential contributions from baseline clinical assessments, ambient gait analysis, and daily medication intake. In leave-one-subject-out cross-validation, the best performing model predicts the likelihood of a fall over the next 4 weeks with a sensitivity and specificity of 72.8 and 73.2, respectively, and achieved an area under the receiver operating characteristic curve (AUROC) of 76.2. By contrast, the best model excluding ambient gait features achieved an AUROC of 56.2 with a sensitivity and specificity of 51.9 and 54.0, respectively. Future research will focus on externally validating these findings to prepare for the implementation of this technology to reduce fall and This work was supported by the Walter and

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Quality Indicators as Predictors of Future Inspection Performance in Ontario Nursing Homes

Cited by 8 publications

References 30 publications

The optimal intervention for preventing physical restraints among older adults living in the nursing home: A systematic review

The optimal intervention for preventing physical restraints among older adults living in the nursing home: A systematic review

Ambient Monitoring of Gait and Machine Learning Models for Dynamic and Short-Term Falls Risk Assessment in People With Dementia

Ambient Monitoring of Gait and Machine Learning Models for Dynamic and Short-Term Falls Risk Assessment in People With Dementia

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