[Physical restraint use in relation to falls risk in a nursing home]

[Use of physical restraints in the elderly in an emergency department. Analysis of clinical, environmental and health care team organization factors associated with decision making]

OBJETIVE

To determine the influence of different factors involved in the decision to apply physical restraints (PR) in the management the elderly people with conduct disorders in an emergency department (ED) METHODS: A prospective observational study was conducted in the ED of the Hospital Universitario Severo Ochoa (Leganés, Madrid). We included 125 elderly people with disruptive behaviors and collected clinical, patient handling, organizational and environmental variables. Individuals who had undergone PR were analyzed to learn what factors were related to the final decision to restrain.

RESULTS

32.8% of the participants underwent PR. The aspects that most influenced the decision to restrain were those related to the organization and environment: specific staff training decreased the probability of restraint by 50% (P<.05) and good support from the whole team reduced the risk of using SF by up to 75% (P<.0005). Related patient handling factors such as verbal restraint, pain relief, family accompaniment and early mobilization significantly reduced the use of PR (P<.05). The only patient-dependent clinical aspect that increased the risk of SF was male sex (P<.05). Other factors unrelated to the probability of applying PR were, among others, nurse-patient ratio, type of behavior, age, or functional/cognitive status.

CONCLUSIONS

Exclusively clinical factors of the patient had little influence on the decision to restrain the elderly in an ED. However, environmental, organizational, and behavioral handling variables could favor more respectful alternatives and thus reduce the use of PR in the elderly with disruptive behaviors in the ED.

Construction of key quality indicators for aged care facilities in China: A two-tier Delphi study: Key aged care quality indicators in ACF by Delphi method

AIM

To construct key quality indicators for aged care facilities in China.

BACKGROUND

Evaluating the care quality in aged care facilities is problematic. Evaluation of nursing care quality is important for improving nursing and self-supervision in aged care facilities. However, a few regulations and studies regarding care quality evaluation have been implemented in China.

DESIGN AND METHOD

This two-tier Delphi study aimed to achieve consensus on key quality indicators for aged care facilities in China. The entry pool was determined by literature review and research team discussion, followed by a discussion by a panel of experts to establish the items of the Delphi study. Finally, key care quality indicators were established through a two-round Delphi study. This study followed the SQUIRE 2.0 guidelines.

RESULTS

The initial 16 quality indicators of the entry pool was developed based on a literature review and a group discussion. Sixteen quality indicators were reduced to eight after the expert discussion. After two rounds of expert consultation, the eight quality indicators became nine, which were then evaluated for importance, formula rationality, and operability using Kendall's harmony coefficients (first round: 0.150, 0.143 and 0.169, respectively; second round: 0.209, 0.159 and 0.173, respectively).

CONCLUSIONS

Key quality indicators provide quantifiable evidence for evaluating the care quality in aged care facilities, but their applicability needs continuous improvement.

RELEVANCE TO CLINICAL PRACTICE

Nine key quality indicators were selected from numerous indicators for measuring the care quality in aged care facilities, supporting the evaluation of the care quality and self-supervision for aged care facilities.

ELDERLY OR PUBLIC CONTRIBUTION

No elderly or public contribution.

Interventions for preventing and reducing the use of physical restraints for older people in all long-term care settings

BACKGROUND

Physical restraints (PR), such as bedrails and belts in chairs or beds, are commonly used for older people receiving long-term care, despite clear evidence for the lack of effectiveness and safety, and widespread recommendations that their use should be avoided. This systematic review of the efficacy and safety of interventions to prevent and reduce the use of physical restraints outside hospital settings, i.e. in care homes and the community, updates our previous review published in 2011.

OBJECTIVES

To evaluate the effects of interventions to prevent and reduce the use of physical restraints for older people who require long-term care (either at home or in residential care facilities) SEARCH METHODS: We searched ALOIS, the Cochrane Dementia and Cognitive Improvement Group's register, MEDLINE (Ovid Sp), Embase (Ovid SP), PsycINFO (Ovid SP), CINAHL (EBSCOhost), Web of Science Core Collection (ISI Web of Science), LILACS (BIREME), ClinicalTrials.gov and the World Health Organization's meta-register, the International Clinical Trials Registry Portal, on 3 August 2022.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) and controlled clinical trials (CCTs) that investigated the effects of interventions intended to prevent or reduce the use of physical restraints in older people who require long-term care. Studies conducted in residential care institutions or in the community, including patients' homes, were eligible for inclusion. We assigned all included interventions to categories based on their mechanisms and components.

DATA COLLECTION AND ANALYSIS

Two review authors independently selected the publications for inclusion, extracted study data, and assessed the risk of bias of all included studies. Primary outcomes were the number or proportion of people with at least one physical restraint, and serious adverse events related to PR use, such as death or serious injuries. We performed meta-analyses if necessary data were available. If meta-analyses were not feasible, we reported results narratively. We used GRADE methods to describe the certainty of the evidence.

MAIN RESULTS

We identified six new studies and included 11 studies with 19,003 participants in this review update. All studies were conducted in long-term residential care facilities. Ten studies were RCTs and one study a CCT. All studies included people with dementia. The mean age of the participants was approximately 85 years. Four studies investigated organisational interventions aiming to implement a least-restraint policy; six studies investigated simple educational interventions; and one study tested an intervention that provided staff with information about residents' fall risk. The control groups received usual care only in most studies although, in two studies, additional information materials about physical restraint reduction were provided. We judged the risk of selection bias to be high or unclear in eight studies. Risk of reporting bias was high in one study and unclear in eight studies. The organisational interventions intended to promote a least-restraint policy included a variety of components, such as education of staff, training of 'champions' of low-restraint practice, and components which aimed to facilitate a change in institutional policies and culture of care. We found moderate-certainty evidence that organisational interventions aimed at implementation of a least-restraint policy probably lead to a reduction in the number of residents with at least one use of PR (RR 0.86, 95% CI 0.78 to 0.94; 3849 participants, 4 studies) and a large reduction in the number of residents with at least one use of a belt for restraint (RR 0.54, 95% CI 0.40 to 0.73; 2711 participants, 3 studies). No adverse events occurred in the one study which reported this outcome. There was evidence from one study that organisational interventions probably reduce the duration of physical restraint use. We found that the interventions may have little or no effect on the number of falls or fall-related injuries (low-certainty evidence) and probably have little or no effect on the number of prescribed psychotropic medications (moderate-certainty evidence). One study found that organisational interventions result in little or no difference in quality of life (high-certainty evidence) and another study found that they may make little or no difference to agitation (low-certainty evidence). The simple educational interventions were intended to increase knowledge and change staff attitudes towards PR. As well as providing education, some interventions included further components to support change, such as ward-based guidance. We found pronounced between-group baseline imbalances in PR prevalence in some of the studies, which might have occurred because of the small number of clusters in the intervention and control groups. One study did not assess bedrails, which is the most commonly used method of restraint in nursing homes. Regarding the number of residents with at least one restraint, the results were inconsistent. We found very-low certainty evidence and we are uncertain about the effects of simple educational interventions on the number of residents with PR. None of the studies assessed or reported any serious adverse events. We found moderate-certainty evidence that simple educational interventions probably result in little or no difference in restraint intensity and may have little or no effect on falls, fall-related injuries, or agitation (low-certainty evidence each). Based on very low-certainty evidence we are uncertain about the effects of simple educational interventions on the number of participants with a prescription of at least one psychotropic medication. One study investigated an intervention that provided information about residents' fall risk to the nursing staff. We found low-certainty evidence that providing information about residents' fall risk may result in little or no difference in the mean number of PR or the number of falls. The study did not assess overall adverse events.

AUTHORS' CONCLUSIONS

Organisational interventions aimed to implement a least-restraint policy probably reduce the number of residents with at least one PR and probably largely reduce the number of residents with at least one belt. We are uncertain whether simple educational interventions reduce the use of physical restraints, and interventions providing information about residents' fall risk may result in little to no difference in the use of physical restraints. These results apply to long-term care institutions; we found no studies from community settings.

A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study

BACKGROUND

Numerous studies have identified risk factors for physical restraint (PR) use in older adults in long-term care facilities. Nevertheless, there is a lack of predictive tools to identify high-risk individuals.

OBJECTIVE

We aimed to develop machine learning (ML)-based models to predict the risk of PR in older adults.

METHODS

This study conducted a cross-sectional secondary data analysis based on 1026 older adults from 6 long-term care facilities in Chongqing, China, from July 2019 to November 2019. The primary outcome was the use of PR (yes or no), identified by 2 collectors' direct observation. A total of 15 candidate predictors (older adults' demographic and clinical factors) that could be commonly and easily collected from clinical practice were used to build 9 independent ML models: Gaussian Naïve Bayesian (GNB), k-nearest neighbor (KNN), decision tree (DT), logistic regression (LR), support vector machine (SVM), random forest (RF), multilayer perceptron (MLP), extreme gradient boosting (XGBoost), and light gradient boosting machine (Lightgbm), as well as stacking ensemble ML. Performance was evaluated using accuracy, precision, recall, an F score, a comprehensive evaluation indicator (CEI) weighed by the above indicators, and the area under the receiver operating characteristic curve (AUC). A net benefit approach using the decision curve analysis (DCA) was performed to evaluate the clinical utility of the best model. Models were tested via 10-fold cross-validation. Feature importance was interpreted using Shapley Additive Explanations (SHAP).

RESULTS

A total of 1026 older adults (mean 83.5, SD 7.6 years; n=586, 57.1% male older adults) and 265 restrained older adults were included in the study. All ML models performed well, with an AUC above 0.905 and an F score above 0.900. The 2 best independent models are RF (AUC 0.938, 95% CI 0.914-0.947) and SVM (AUC 0.949, 95% CI 0.911-0.953). The DCA demonstrated that the RF model displayed better clinical utility than other models. The stacking model combined with SVM, RF, and MLP performed best with AUC (0.950) and CEI (0.943) values, as well as the DCA curve indicated the best clinical utility. The SHAP plots demonstrated that the significant contributors to model performance were related to cognitive impairment, care dependency, mobility decline, physical agitation, and an indwelling tube.

CONCLUSIONS

The RF and stacking models had high performance and clinical utility. ML prediction models for predicting the probability of PR in older adults could offer clinical screening and decision support, which could help medical staff in the early identification and PR management of older adults.

Use of physical restraints and its associated risk factors in the aged care facilities: A multicentre cross-sectional study

AIMS AND OBJECTIVES

To investigate the use of physical restraints in aged care facilities(ACFs)and analyse its associated risk factors.

BACKGROUND

Physical restraints have been widely used in ACFs worldwide, but they can cause physical and mental harm to older people. It is important to regulate the use of physical restraint.

DESIGN

A cross-sectional observational and correlational multicentre study.

METHODS

By convenience sampling method, we selected eight ACFs in four representative regions of Hunan province, China, for this study. The ACF-related information was obtained by interviewing the managers and reviewing records. We conducted investigation and observation on the elderly in the ACFs to understand the use of physical restraints at three different times: 9:30-11:30, 16:00-18:00 and 19:30-21:30 on a working day. The STROBE checklist was followed for this cross-sectional study.

RESULTS

This study found that the utilisation rate of physical restraints was 23.2%. The critical risk factors affecting the use of physical restrains include the following: (1) the ratio of nursing staff to the elderly residents; (2)whether there is a dementia care unit at the facility; (3) the number of elderly residents in each room; (4) the elderly residents' age, degree of education, marital status, care dependence and cognitive impairment; (5) whether the elderly has suffered from a stroke or senile dementia; (6) whether the elderly carries medical catheters.

CONCLUSION

There is a lack of standardisation in the use of physical restraints in ACFs of central China. Chinese ACFs should develop guidelines and reduction measures to standardise the use of physical restraints, basing on the key factors affecting the use of physical restraints.

RELEVANCE TO CLINICAL PRACTICE

The use of physical restraints in ACFs is threatening the safety of the elderly residents. Understanding the implementation of physical restraint in ACFs can provide reference for reducing the use of physical restraint.