Fall risk assessment tools for use among older adults in long-term care settings: A systematic review of the literature

Development and External Validation of a Machine Learning-based Fall Prediction Model for Nursing Home Residents: A Prospective Cohort Study

OBJECTIVES

To develop and externally validate a machine learning-based fall prediction model for ambulatory nursing home residents. The focus is on predicting fall occurrences within 6 months after baseline assessment through a binary classification task, aiming to provide staff with an effective and user-friendly fall-risk assessment tool.

DESIGN

Prospective cohort study.

SETTING AND PARTICIPANTS

A total of 864 older residents living in 4 nursing homes between May 2022 and March 2023 in China.

METHODS

Potential fall-risk predictors were collected through in-person interviews and assessments of anthropometric and physical function. Participants were followed for 6 months, with falls recorded by trained nurses. Seven machine learning algorithms, including Logistic Regression (LR), Gradient Boosting Machine (GBM), eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), Neural Networks (NN), and Decision Tree (DT), were used to develop prediction models. Performance was evaluated using the area under the receiver operating characteristic curve (ROC-AUC) and Precision-Recall curve (PR-AUC), with calibration assessed via a calibration curve. Feature importance was visualized using SHapley Additive exPlanations (SHAP).

RESULTS

The 6 selected predictors were balance, grip strength, fatigue, fall history, age, and comorbidity. The ROC-AUC for the models ranged from 0.710 to 0.750, PR-AUC from 0.415 to 0.473, sensitivity from 0.704 to 0.914, and specificity from 0.511 to 0.687 in the validation cohort. The LR model was converted into a nomogram.

CONCLUSIONS AND IMPLICATIONS

The machine learning-based fall-prediction models effectively identified nursing home residents at high risk of falls. The developed nomogram can be integrated into clinical practice to enhance fall risk assessment protocols, ultimately improving patient safety and care in nursing homes.

Older people's experiences of elder abuse in residential care settings: A scoping review

BACKGROUND

Elder abuse is a global human rights issue, particularly in residential care settings where there is limited understanding of older people's experiences of this phenomenon. This scoping review aims to map and describe the existing literature on this phenomenon.

METHODS

Using Arksey and O'Malley's scoping review methodology, further developed by Levac et al. and the Joanna Briggs Institute, a systematic search of six databases was conducted to identify relevant studies published from inception to January 2023. Studies were included if they focused on older people's experience of abuse within residential care settings. A comprehensive data extraction process was employed to identify key themes from the included studies.

RESULTS

The initial search yielded a total of 3701 articles of which eight met the inclusion criteria. The findings revealed a range of abusive experiences encountered by older people living in residential care settings, including psychological, physical, financial, neglect and sexual abuse. The common attributes of residents vulnerable to abuse were evident throughout each of the studies. Finally, the theme of organizational neglect was apparent through the absence of effective safeguarding measures in the included studies. The findings revealed the insufficient implementation of safeguarding measures increases the risk of abuse among residents.

CONCLUSION

This scoping review highlights the limited research on the experiences of older people who have encountered elder abuse in residential care settings. The findings stress the need for further research exploring the complex interplay of factors contributing to elder abuse within aged care settings. The insights gained from this scoping review can inform the development of comprehensive safeguarding strategies to prevent and address elder abuse in residential care settings, promoting the well-being and safety of older people.

PATIENT OR PUBLIC CONTRIBUTION

This project is a scoping review of the literature; therefore, no patient or public contribution was deemed necessary.

WHAT THIS PAPER CONTRIBUTES TO THE WIDER GLOBAL COMMUNITY

Most research on elder abuse has been conducted in the community rather than in Residential Care Settings where there is a limited understanding of older people's experiences of abuse within the published literature. The scoping review highlights the presence of inadequate safeguarding strategies in Residential Care Settings within the reviewed studies, providing recommendations for developing and improving safeguarding measures in Residential Care Settings to prevent abuse, neglect, and harm in the future.

Development and internal validation of a dynamic fall risk prediction and monitoring tool in aged care using routinely collected electronic health data: a landmarking approach

OBJECTIVES

Falls pose a significant challenge in residential aged care facilities (RACFs). Existing falls prediction tools perform poorly and fail to capture evolving risk factors. We aimed to develop and internally validate dynamic fall risk prediction models and create point-based scoring systems for residents with and without dementia.

MATERIALS AND METHODS

A longitudinal cohort study using electronic data from 27 RACFs in Sydney, Australia. The study included 5492 permanent residents, with a 70%-30% split for training and validation. The outcome measure was the incidence of falls. We tracked residents for 60 months, using monthly landmarks with 1-month prediction windows. We employed landmarking dynamic prediction for model development, a time-dependent area under receiver operating characteristics curve (AUROCC) for model evaluations, and a regression coefficient approach to create point-based scoring systems.

RESULTS

The model identified 15 independent predictors of falls in dementia and 12 in nondementia cohorts. Falls history was the key predictor of subsequent falls in both dementia (HR 4.75, 95% CI, 4.45-5.06) and nondementia cohorts (HR 4.20, 95% CI, 3.87-4.57). The AUROCC across landmarks ranged from 0.67 to 0.87 for dementia and from 0.66 to 0.86 for nondementia cohorts but generally remained between 0.75 and 0.85 in both cohorts. The total point risk score ranged from -2 to 57 for dementia and 0 to 52 for nondementia cohorts.

DISCUSSION

Our novel risk prediction models and scoring systems provide timely person-centered information for continuous monitoring of fall risk in RACFs.

CONCLUSION

Embedding these tools within electronic health records could facilitate the implementation of targeted proactive interventions to prevent falls.

Existing hip joint disease is associated with an increased incidence of hip fracture in adults: A retrospective survey of 9710 individuals from a single center

Objective

In hip disease patients, pain and movement restrictions might cause changes in bone strength and increase the likelihood of falls, finally leading to hip fracture. The aim of this study was to identify the incidence of, characteristics of and risk factors for hip fracture in patients with existing hip disease.

Methods

This was a retrospective cohort study. Patients with existing hip disease treated at both outpatient and inpatient departments of our institute were identified by searching the electronic medical record system and followed retrospectively for the occurrence of hip fracture. Demographic and clinical characteristics, such as age, sex and kind of primary hip disease, were collected from the electronic medical record system. The incidence and timing of hip fracture were estimated, and a Cox regression model was built to identify the independent risk factors for hip fracture in these patients.

Results

A total of 9710 eligible patients were included. After a mean follow-up of 3.97 years, hip fractures were identified in 95 patients, for an estimated incidence of hip fracture of 978.37 per 100,000 patients. The femoral neck was involved in 49 fractures (51.58 %), and the femoral trochanter was involved in 45 fractures (47.37 %). Four independent risk factors and one protective factor for hip fracture in patients with hip diseases were identified: age (HR = 1.116, 95 % CI = 1.094-1.138), the presence of osteonecrosis of the femoral head (HR = 2.201, 95 % CI = 1.217-3.980), a lower Harris hip score (HR = 0.966, 95 % CI = 0.949-0.982), a history of previous hip surgery (HR = 2.126, 95 % CI = 1.304-3.466) and the use of walking aids (HR = 0.588, 95 % CI = 0.354-0.975). A scoring system with a total score of 20 points was built, which included all of the above risk factors. The predictive scores for a low risk (estimated incidence of hip fracture ≤30 %), a moderate risk (estimated incidence of hip fracture 31 %-69 %), and a high risk (estimated incidence of hip fracture ≥70 %) of hip fracture were ≤8.5 points, 9.0-13.0 points and ≥13.5 points, respectively.

Conclusion

The incidence of hip fracture in the special population of patients with existing hip disease was determined. Elderly patients, patients with a history of hip surgery, patients with osteonecrosis and patients with poor Harris hip scores were at increased risk of hip fracture. In patients with a predictive score greater than 9 points, indicating a moderate to high risk of hip fracture, the use of a walking aid might reduce the risk of hip fracture.

Capturing key function-focused care problems, nursing diagnoses, and interventions for nursing home patients using a web-based case management system

PURPOSE

The aim of this study is to identify the key functional care problems, NANDA-I nursing diagnoses, and intervention plans related to function-focused care (FFC) using a web-based case management system for patients who present different cognitive status.

METHODS

This study employed a retrospective descriptive research design. Data were obtained from system records on patients after the research team trained the case management system at a nursing home in Dangjin in South Chungcheong Province, South Korea. A total of 119 inpatient records were analyzed.

RESULTS

The key physical, cognitive, and social functional problems, nursing diagnoses in six domains (health promotion, elimination and exchange, activity/rest, perception/cognition, coping/stress tolerance, and safety/protection), and intervention plans were identified.

CONCLUSION

The identified FFC case management information of interdisciplinary caregivers will provide evidence for the implementation of effective interventions according to a patient's functional status. Additional studies related to the establishment of a large clinical database of advanced case management systems focusing on interdisciplinary caregivers' functional management are needed to support the prioritization of functional care.

Interventions to reduce falls in community-dwelling adults with intellectual disability: a systematic review

BACKGROUND

People with intellectual disability have a high risk of falls and falls-related injuries. Although people with intellectual disability are at increased risk of falls, there is a need to better understand the efficacy of interventions that can help reduce falls and address risk factors in this population. This systematic review aimed to evaluate the type, nature and effectiveness of interventions undertaken to reduce falls with community-dwelling adults with intellectual disability and the quality of this evidence.

METHOD

Four electronic databases were searched: Ovid MEDLINE, PsycINFO, CINAHL Plus and the Cochrane Library. Studies were included if they involved people aged 18 years or over, at least 50% of study participants had intellectual disability, participants were community-dwelling, and the study evaluated any interventions aiming to reduce falls. Study quality was assessed using the National Institutes of Health study quality assessment tools. Reporting of the review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

RESULTS

Seven studies were eligible for review, with a total of 286 participants and mean age of 50.4 years. As only one randomised trial was identified, a narrative synthesis of results was undertaken. Five studies evaluated exercise interventions, one evaluated a falls clinic programme, and one evaluated stretch fabric splinting garments. Methodological quality varied (two studies rated as good, four as fair, and one as poor). Exercise interventions varied in terms of exercise type and dosage, frequency and intensity, and most did not align with recommendations for successful falls prevention exercise interventions reported for older people. While the majority of studies reported reduced falls, they differed in methods of reporting falls, and most did not utilise statistical analyses to evaluate outcomes.

CONCLUSION

This review identified a small number of falls prevention intervention studies for people with intellectual disability. Although several studies reported improvements in fall outcomes, ability to draw conclusions about intervention effectiveness is limited by small sample sizes and few studies. Further large-scale research is required to implement and evaluate falls prevention interventions specifically for adults with intellectual disability.

Fall Prevalence and Associated Risk Factors in the Hospitalised Adult Population: A Crucial Step Towards Improved Hospital Care

Background Falls among the adult population are a major global health concern with severe repercussions for individuals and healthcare systems. The purpose of this study was to investigate the prevalence and associated risk factors of falls in hospitalized patients in order to improve hospital care for elderly adults. Materials and methods The research was conducted at two institutions of tertiary care in Abbottabad, Pakistan. After extensive screening and obtaining informed consent, a total of 210 participants aged 50 and older were enrolled in the study. Mental status, history of falls, ambulation/elimination status, vision, gait/balance, systolic blood pressure, medication use, and predisposing diseases were evaluated using the Long Term Care Fall Risk Assessment Form. Additionally, the Dynamic Gait Index was utilized to evaluate various aspects of gait. Results 58.6% of participants reported a history of falls in the previous year, according to the findings. BMI, imbalance, vertigo, and fear of falling were significantly associated with an increased risk of falls in older individuals. The Long-Term Care Fall Risk Assessment, the Montreal Cognitive Assessment (MoCA), the Dynamic Gait Index (DGI), and the Mini-BESTest scores revealed that patients with a history of falls had inferior functional and cognitive outcomes. Falls were more common among individuals with a robust BMI, especially men. Conclusions The study results highlight the multifactorial nature of falls in the adult population and the need for targeted interventions to address modifiable risk factors. To enhance hospital care for high-risk patients, proactive fall prevention strategies, including regular risk assessments and individualized interventions, should be implemented. This study provides important insights into the prevalence and causes of accidents among hospitalized patients, particularly in developing nations such as Pakistan. ​​​​​​.

Simulation Versus Written Fall Prevention Education in Older Hospitalized Adults: A Randomized Controlled Study

Using a randomized controlled, non-blinded, two-group design, differences in fall risk assessment, post-discharge sustainable fall risk changes, fall events and re-hospitalization were examined in 77 older adults who received a simulation (n = 36) or written (n = 41) education intervention. Between-group differences and changes in pre- versus post-fall risk assessment scores were examined using Pearson's chi-square, Wilcoxon rank sum or Fisher's exact tests (categorical variables) and two-sample t-tests (continuous variables). There were no statistically significant differences between groups in demographic characteristics. Patients who received simulation education had higher fall risk post-assessment scores than the written education group, p = .022. Change in fall risk assessment scores (post-vs.-pre; 95% confidence intervals) were higher in the simulation group compared to the written education group, 1.43 (0.37, 2.50), p = .009. At each post-discharge assessment, fall events were numerically fewer but not significantly different among simulation and education group participants. There were no statistically significant between-group differences in re-hospitalization.

Falls across Health Care Settings: Findings from a Geriatric Screening Program

Falls are a major public health problem for older adults, resulting in injuries and mortality. Screening is recommended to identify the multifactorial fall risks that can be addressed with interventions to prevent future falls. This study examined the utility of using the Rapid Geriatric Assessment (RGA) tool to identify fall risks across multiple settings. RGA data was collected at primary care sites, hospitals, long-term care settings, and community events (n = 8686, 65% female, mean age 77.6). Multinomial logistic regression was used to determine predictors of falls using the RGA. The FRAIL, SARC-F, Rapid Cognitive Screen and SNAQ measures all significantly predicted history of falls. The RGA provides a brief screening that can be used in any setting by multiple providers to identify fall risk.

Multimodal Mobility Assessment Predicts Fall Frequency and Severity in Cerebellar Ataxia

This cohort study aims to evaluate the predictive validity of multimodal clinical assessment and quantitative measures of in- and off-laboratory mobility for fall-risk estimation in patients with cerebellar ataxia (CA).Occurrence, severity, and consequences of falling were prospectively assessed for 6 months in 93 patients with hereditary (N = 36) and sporadic or secondary (N = 57) forms of CA and 63 healthy controls. Participants completed a multimodal clinical and functional fall risk assessment, in-laboratory gait examination, and a 2-week inertial sensor-based daily mobility monitoring. Multivariate logistic regression analyses were performed to evaluate the predictive capacity of all clinical and in- and off-laboratory mobility measures with respect to fall (1) status (non-faller vs. faller), (2) frequency (occasional vs. frequent falls), and (3) severity (benign vs. injurious fall) of patients. 64% of patients experienced one or recurrent falls and 65% of these severe fall-related injuries during prospective assessment. Mobility impairments in patients corresponded to a mild-to-moderate ataxic gait disorder. Patients' fall status and frequency could be reliably predicted (78% and 81% accuracy, respectively), primarily based on their retrospective fall status. Clinical scoring of ataxic symptoms and in- and off-laboratory gait and mobility measures improved classification and provided unique information for the prediction of fall severity (84% accuracy).These results encourage a stepwise approach for fall risk assessment in patients with CA: fall history-taking readily and reliably informs the clinician about patients' general fall risk. Clinical scoring and instrument-based mobility measures provide further in-depth information on the risk of recurrent and injurious falling.

Factors Associated with Falls in Canadian Long Term Care Homes: a Retrospective Cohort Study

Background

Half of Canadians living in long-term care (LTC) homes will fall each year resulting in consequences to independence, quality of life, and health. The objective in this study was to analyze factors that contribute to, or are protective against, falls in Canadian LTC homes.

Methods

We analyzed of a retrospective cohort of a stratified random sample of Canadian LTC homes in Western Canada from 2011-2017. We accessed variables from the RAI-MDS 2.0 to assess the association of the dependent variable "fall within the last 31-180 days" with multiple independent factors, using generalized estimating equation models.

Results

A total of 28,878 LTC residents were analyzed. Factors found to increase the odds of falling were other fractures (OR 3.64 [95% confidence interval; CI 3.27, 4.05]), hip fractures (OR 3.58 [3.27, 3.93]), moderately impaired cognitive skills (OR 2.45 [2.28, 2.64]), partial support to balance standing (OR 2.44 [2.30, 2.57]), wandering (OR 2.31 [2.18, 2.44]).

Conclusion

A range of factors identified were associated with falls for people living in LTC homes. Individual physical ability represented the largest group of independent factors contributing to falls. Residents who experience any fracture or an acute change in behaviour, mobility, or activities of daily living (ADL) should be considered at increased risk of falls.

Assessment Tools of Biopsychosocial Frailty Dimensions in Community-Dwelling Older Adults: A Narrative Review

Frailty is a complex interplay between several factors, including physiological changes in ageing, multimorbidities, malnutrition, living environment, genetics, and lifestyle. Early screening for frailty risk factors in community-dwelling older people allows for preventive interventions on the clinical and social determinants of frailty, which allows adverse events to be avoided. By conducting a narrative review of the literature employing the International Narrative Systematic Assessment tool, the authors aimed to develop an updated framework for the main measurement tools to assess frailty risks in older adults, paying attention to use in the community and primary care settings. This search focused on the biopsychosocial domains of frailty that are covered in the SUNFRAIL tool. The study selected 178 reviews (polypharmacy: 20; nutrition: 13; physical activity: 74; medical visits: 0; falls: 39; cognitive decline: 12; loneliness: 15; social support: 5; economic constraints: 0) published between January 2010 and December 2021. Within the selected reviews, 123 assessment tools were identified (polypharmacy: 15; nutrition: 15; physical activity: 25; medical visits: 0; falls: 26; cognitive decline: 18; loneliness: 9; social support: 15; economic constraints: 0). The narrative review allowed us to evaluate assessment tools of frailty domains to be adopted for multidimensional health promotion and prevention interventions in community and primary care.

Risk of Falls in adults 45-64 years old in the United States

Falls among the older adults (64+ years old [YO]) are considered public health issues. However, fall prevention in middle adulthood (age 45-64) has received less attention. We studied the associations between the number of falls and fall-related injuries and indicators for socio-demographics, chronic diseases, and difficulties in conducting activities in two age groups, 45-64 YO and 64+. In this secondary data analysis, we used the Behavioral Risk Factor Surveillance System (BRFSS) 2018 data. The study showed respondents in the 45-64 YO have higher average falls and fall-related injuries than those 64+ (P < .001). Variables that link to more falls and fall-related injuries in 64+ correspond to more falls and fall-related injuries in 45-64 YO. The finding indicates that the odds of falls and fall-related injuries are comparable across age groups when considering demographic characteristics. However, odds of falling in the presence of arthritis and asthma are higher for respondents in 45-64 YO than the 64+ YO. The risk of falls and fall-related injuries are not specific to older adults. Factors that matter to the number of falls and fall-related injuries in the older adults also count in the younger age group. Nurses are asked to validate available fall assessment tools for adults 45-64 years old and evaluate all clients over 45 for fall risk.

Falls prediction using the nursing home minimum dataset

OBJECTIVE

The purpose of the study was to develop and validate a model to predict the risk of experiencing a fall for nursing home residents utilizing data that are electronically available at the more than 15 000 facilities in the United States.

MATERIALS AND METHODS

The fall prediction model was built and tested using 2 extracts of data (2011 through 2013 and 2016 through 2018) from the Long-term Care Minimum Dataset (MDS) combined with drug data from 5 skilled nursing facilities. The model was created using a hybrid Classification and Regression Tree (CART)-logistic approach.

RESULTS

The combined dataset consisted of 3985 residents with mean age of 77 years and 64% female. The model's area under the ROC curve was 0.668 (95% confidence interval: 0.643-0.693) on the validation subsample of the merged data.

DISCUSSION

Inspection of the model showed that antidepressant medications have a significant protective association where the resident has a fall history prior to admission, requires assistance to balance while walking, and some functional range of motion impairment in the lower body; even if the patient exhibits behavioral issues, unstable behaviors, and/or are exposed to multiple psychotropic drugs.

CONCLUSION

The novel hybrid CART-logit algorithm is an advance over the 22 fall risk assessment tools previously evaluated in the nursing home setting because it has a better performance characteristic for the fall prediction window of ≤90 days and it is the only model designed to use features that are easily obtainable at nearly every facility in the United States.

The use and predictive performance of the Peninsula Health Falls Risk Assessment Tool (PH-FRAT) in 25 residential aged care facilities: a retrospective cohort study using routinely collected data

BACKGROUND

The Peninsula Health Falls Risk Assessment Tool (PH-FRAT) is a validated and widely applied tool in residential aged care facilities (RACFs) in Australia. However, research regarding its use and predictive performance is limited. This study aimed to determine the use and performance of PH-FRAT in predicting falls in RACF residents.

METHODS

A retrospective cohort study using routinely-collected data from 25 RACFs in metropolitan Sydney, Australia from Jul 2014-Dec 2019. A total of 5888 residents aged ≥65 years who were assessed at least once using the PH-FRAT were included in the study. The PH-FRAT risk score ranges from 5 to 20 with a score > 14 indicating fallers and ≤ 14 non-fallers. The predictive performance of PH-FRAT was determined using metrics including area under receiver operating characteristics curve (AUROC), sensitivity, specificity, sensitivity_{Event Rate(ER)} and specificity_ER.

RESULTS

A total of 27,696 falls were reported over 3,689,561 resident days (a crude incident rate of 7.5 falls /1000 resident days). A total of 38,931 PH-FRAT assessments were conducted with a median of 4 assessments per resident, a median of 43.8 days between assessments, and an overall median fall risk score of 14. Residents with multiple assessments had increased risk scores over time. The baseline PH-FRAT demonstrated a low AUROC of 0.57, sensitivity of 26.0% (sensitivity_ER 33.6%) and specificity of 88.8% (specificity_ER 82.0%). The follow-up PH-FRAT assessments increased sensitivity_ER values although the specificity_ER decreased. The performance of PH-FRAT improved using a lower risk score cut-off of 10 with AUROC of 0.61, sensitivity of 67.5% (sensitivity_ER 74.4%) and specificity of 55.2% (specificity_ER 45.6%).

CONCLUSIONS

Although PH-FRAT is frequently used in RACFs, it demonstrated poor predictive performance raising concerns about its value. Introducing a lower PH-FRAT cut-off score of 10 marginally enhanced its predictive performance. Future research should focus on understanding the feasibility and accuracy of dynamic fall risk predictive tools, which may serve to better identify residents at risk of falls.

The use of predictive fall models for older adults receiving aged care, using routinely collected electronic health record data: a systematic review

BACKGROUND

Falls in older adults remain a pressing health concern. With advancements in data analytics and increasing uptake of electronic health records, developing comprehensive predictive models for fall risk is now possible. We aimed to systematically identify studies involving the development and implementation of predictive falls models which used routinely collected electronic health record data in home-based, community and residential aged care settings.

METHODS

A systematic search of entries in Cochrane Library, CINAHL, MEDLINE, Scopus, and Web of Science was conducted in July 2020 using search terms relevant to aged care, prediction, and falls. Selection criteria included English-language studies, published in peer-reviewed journals, had an outcome of falls, and involved fall risk modelling using routinely collected electronic health record data. Screening, data extraction and quality appraisal using the Critical Appraisal Skills Program for Clinical Prediction Rule Studies were conducted. Study content was synthesised and reported narratively.

RESULTS

From 7,329 unique entries, four relevant studies were identified. All predictive models were built using different statistical techniques. Predictors across seven categories were used: demographics, assessments of care, fall history, medication use, health conditions, physical abilities, and environmental factors. Only one of the four studies had been validated externally. Three studies reported on the performance of the models.

CONCLUSIONS

Adopting predictive modelling in aged care services for adverse events, such as falls, is in its infancy. The increased availability of electronic health record data and the potential of predictive modelling to document fall risk and inform appropriate interventions is making use of such models achievable. Having a dynamic prediction model that reflects the changing status of an aged care client is key to this moving forward for fall prevention interventions.

The risk of fall-related hospitalisations at entry into permanent residential aged care

Background

Entering permanent residential aged care (PRAC) is a vulnerable time for individuals. While falls risk assessment tools exist, these have not leveraged routinely collected and integrated information from the Australian aged and health care sectors. Our study examined individual, system, medication, and health care related factors at PRAC entry that are predictors of fall-related hospitalisations and developed a risk assessment tool using integrated aged and health care data.

Methods

A retrospective cohort study was conducted on N = 32,316 individuals ≥65 years old who entered a PRAC facility (01/01/2009-31/12/2016). Fall-related hospitalisations within 90 or 365 days were the outcomes of interest. Individual, system, medication, and health care-related factors were examined as predictors. Risk prediction models were developed using elastic nets penalised regression and Fine and Gray models. Area under the receiver operating characteristics curve (AUC) assessed model discrimination.

Results

64.2% (N = 20,757) of the cohort were women and the median age was 85 years old (interquartile range 80-89). After PRAC entry, 3.7% (N = 1209) had a fall-related hospitalisation within 90 days and 9.8% (N = 3156) within 365 days. Twenty variables contributed to fall-related hospitalisation prediction within 90 days and the strongest predictors included fracture history (sub-distribution hazard ratio (sHR) = 1.87, 95% confidence interval (CI) 1.63-2.15), falls history (sHR = 1.41, 95%CI 1.21-2.15), and dementia (sHR = 1.39, 95%CI 1.22-1.57). Twenty-seven predictors of fall-related hospitalisation within 365 days were identified, the strongest predictors included dementia (sHR = 1.36, 95%CI 1.24-1.50), history of falls (sHR = 1.30, 95%CI 1.20-1.42) and fractures (sHR = 1.28, 95%CI 1.15-1.41). The risk prediction models had an AUC of 0.71 (95%CI 0.68-0.74) for fall-related hospitalisations within 90 days and 0.64 (95%CI 0.62-0.67) for within 365 days.

Conclusion

Routinely collected aged and health care data, when integrated at a clear point of action such as entry into PRAC, can identify residents at risk of fall-related hospitalisations, providing an opportunity for better targeting risk mitigation strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02640-w.

Usability of Electronic Health records in Predicting Short-term falls: Machine learning Applications in Senior Care Facilities (Preprint)

Background

Short-term fall prediction models that use electronic health records (EHRs) may enable the implementation of dynamic care practices that specifically address changes in individualized fall risk within senior care facilities.

Objective

The aim of this study is to implement machine learning (ML) algorithms that use EHR data to predict a 3-month fall risk in residents from a variety of senior care facilities providing different levels of care.

Methods

This retrospective study obtained EHR data (2007-2021) from Juniper Communities’ proprietary database of 2785 individuals primarily residing in skilled nursing facilities, independent living facilities, and assisted living facilities across the United States. We assessed the performance of 3 ML-based fall prediction models and the Juniper Communities’ fall risk assessment. Additional analyses were conducted to examine how changes in the input features, training data sets, and prediction windows affected the performance of these models.

Results

The Extreme Gradient Boosting model exhibited the highest performance, with an area under the receiver operating characteristic curve of 0.846 (95% CI 0.794-0.894), specificity of 0.848, diagnostic odds ratio of 13.40, and sensitivity of 0.706, while achieving the best trade-off in balancing true positive and negative rates. The number of active medications was the most significant feature associated with fall risk, followed by a resident’s number of active diseases and several variables associated with vital signs, including diastolic blood pressure and changes in weight and respiratory rates. The combination of vital signs with traditional risk factors as input features achieved higher prediction accuracy than using either group of features alone.

Conclusions

This study shows that the Extreme Gradient Boosting technique can use a large number of features from EHR data to make short-term fall predictions with a better performance than that of conventional fall risk assessments and other ML models. The integration of routinely collected EHR data, particularly vital signs, into fall prediction models may generate more accurate fall risk surveillance than models without vital signs. Our data support the use of ML models for dynamic, cost-effective, and automated fall predictions in different types of senior care facilities.

Established Trauma Triage Score Predicts Risk of Falling After Femoral Neck Fracture Arthroplasty Surgery

INTRODUCTION

The purpose of this study is to determine whether the Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) patients is able to predict fall, fracture, periprosthetic fracture, or dislocation risk after femoral neck fracture arthroplasty surgery.

METHODS

Four hundred one patients who underwent hip arthroplasty surgery after a femoral neck fracture at one urban academic medical center were stratified into groups based on their risk scores assigned at femoral neck fracture presentation. The cohort was reviewed for the occurrence of postdischarge falls, secondary fractures, and prosthetic dislocations that resulted in a presentation to the emergency department (ED) after discharge from their hip fracture surgery. The incidence and timing of these complications after discharge were compared between the low-risk and high-risk groups.

RESULTS

The low-risk group included 201 patients, and the high-risk group included 200 patients. The high-risk group had significantly more postdischarge falls resulting in ED presentation (49 vs. 32, p = .035) that occurred significantly sooner (12.6 vs. 18.3 months, p = .034) after discharge.

CONCLUSIONS

The STTGMA model was able to successfully stratify patients who are at a higher risk of sustaining a fall after an arthroplasty procedure for a femoral neck fracture.

FallSkip device is a useful tool for fall risk assessment in sarcopenic older community people

PURPOSE

Fall prevention is a major health concern for the ageing population. Sarcopenia is considered a risk factor for falls. Some instruments, such as Time Up and Go (TUG), are used for screening risk. The use of sensors has also been shown to be a viable tool that can provide accurate, cost-effective, and easy to manage assessment of fall risk. One novel sensor for assessing fall risk in older people is the Fallskip device. The present study evaluates the performance of the FallSkip device against the TUG method in fall risk screening and assesses its measurement properties in sarcopenic older people.

METHODS

A cross-sectional study was made in a sample of community-dwelling sarcopenic and non-sarcopenic older people aged 70 years or over.

RESULTS

The study sample consisted of 34 older people with a mean age of 77.03 (6.58) years, of which 79.4% (n = 27) were females, and 41.2% (n = 14) were sarcopenic. The Pearson correlation coefficient between TUG time and FallSkip time was 0.70 (p < 0.001). The sarcopenic individuals took longer in performing both TUG and FallSkip. They also presented poorer reaction time, gait and sit-to-stand - though no statistically significant differences were observed. The results in terms of feasibility, acceptability, reliability and validity in sarcopenic older people with FallSkip were acceptable.

CONCLUSIONS

The FallSkip device has suitable metric properties for the assessment of fall risk in sarcopenic community-dwelling older people. FallSkip analyses more parameters than TUG in assessing fall risk and has greater discriminatory power in evaluating the risk of falls.

A novel model to quantify balance alterations in older adults based on the center of pressure (CoP) measurements with a cross-sectional study

Background

The timely detection of fall risk or balance impairment in older adults is transcendental because, based on a reliable diagnosis, clinical actions can be taken to prevent accidents. This study presents a statistical model to estimate the fall risk from the center of pressure (CoP) data.

Methods

This study is a cross-sectional analysis from a cohort of community-dwelling older adults aged 60 and over living in Mexico City. CoP balance assessments were conducted in 414 older adults (72.2% females) with a mean age of 70.23 ± 6.68, using a modified and previously validated Wii Balance Board (MWBB) platform. From this information, 78 CoP indexes were calculated and analyzed. Multiple logistic regression models were fitted in order to estimate the relationship between balance alteration and the CoP indexes and other covariables.

Results

The CoP velocity index in the Antero-Posterior direction with open eyes (MVELAPOE) had the best value of area under the curve (AUC) to identify a balance alteration (0.714), and in the adjusted model, AUC was increased to 0.827. Older adults with their mean velocity higher than 14.24 mm/s had more risk of presenting a balance alteration than those below this value (OR (Odd Ratio) = 2.94, p<0.001, 95% C.I.(Confidence Interval) 1.68–5.15). Individuals with increased age and BMI were more likely to present a balance alteration (OR 1.17, p<0.001, 95% C.I. 1.12–1.23; OR 1.17, p<0.001, 95% C.I. 1.10–1.25). Contrary to what is reported in the literature, sex was not associated with presenting a balance alteration (p = 0.441, 95% C.I. 0.70–2.27).

Significance

The proposed model had a discriminatory capacity higher than those estimated by similar means and resources to this research and was implemented in an embedded standalone system which is low-cost, portable, and easy-to-use, ideal for non-laboratory environments. The authors recommend using this technology to support and complement the clinical tools to attend to the serious public health problem represented by falls in older adults.

Impact of the introduction of falls risk assessment toolkit on falls prevention and psychotropic medicines' utilisation in Walsall: an interrupted time series analysis

OBJECTIVE

To determine the impact of the introduction of a falls risk assessment toolkit (FRAT) in a UK medical centre on the number and cost of non-elective admissions for falls and psychotropic medication utilisation.

DESIGN

Interrupted time series analysis quantifying the number and cost of non-elective admissions for falls and primary care use data for Rushall Medical Centre before and after the implementation of FRAT at July 2017.

SETTING

Data on the monthly number and cost of non-elective admissions for falls and number of referrals and assessment to the falls service were provided by Walsall Clinical Commissioning Group. Primary care prescribing cost and volume data for Rushall Medical Centre was derived from the Openprescribing.net website for prescriptions dispensed between April 2015 and November 2018.

PRIMARY AND SECONDARY OUTCOME MEASURES

The number and cost of non-elective admissions for falls and number of referrals and assessment to the falls service, and the volume of utilisation of psychotropic medicines.

RESULTS

Following the implementation of FRAT at Rushall Medical Centre in July 2017, the number of non-elective admissions for falls decreased at a rate of 0.414 admissions per month (p<0.033, 95% CI -0.796 to -0.032). The utilisation of psychotropic medications (alimemazine, citalopram, escitalopram, fluoxetine, mirtazapine, olanzapine and risperidone) decreased. The expenditure on psychotropic medications prescribed/used at Rushall Medical Centre decreased by at least £986 per month (p<0.001, 95% CI -2067 to -986).

CONCLUSIONS

The implementation of FRAT at Rushall Medical Centre was associated with a reduction in the number of non-elective admissions for falls. Assessment of these patients together with deprescribing of psychotropic medications resulted in a reduction in the number of non-elective admissions for falls and associated costs.

Fall incidents in nursing home residents: development of a predictive clinical rule (FINDER)

OBJECTIVES

To develop (part I) and validate (part II) an electronic fall risk clinical rule (CR) to identify nursing home residents (NH-residents) at risk for a fall incident.

DESIGN

Observational, retrospective case-control study.

SETTING

Nursing homes.

PARTICIPANTS

A total of 1668 (824 in part I, 844 in part II) NH-residents from the Netherlands were included. Data of participants from part I were excluded in part II.

PRIMARY AND SECONDARY OUTCOME MEASURES

Development and validation of a fall risk CR in NH-residents. Logistic regression analysis was conducted to identify the fall risk-variables in part I. With these, three CRs were developed (ie, at the day of the fall incident and 3 days and 5 days prior to the fall incident). The overall prediction quality of the CRs were assessed using the area under the receiver operating characteristics (AUROC), and a cut-off value was determined for the predicted risk ensuring a sensitivity ≥0.85. Finally, one CR was chosen and validated in part II using a new retrospective data set.

RESULTS

Eleven fall risk-variables were identified in part I. The AUROCs of the three CRs form part I were similar: the AUROC for models I, II and III were 0.714 (95% CI: 0.679 to 0.748), 0.715 (95% CI: 0.680 to 0.750) and 0.709 (95% CI: 0.674 to 0.744), respectively. Model III (ie, 5 days prior to the fall incident) was chosen for validation in part II. The validated AUROC of the CR, obtained in part II, was 0.603 (95% CI: 0.565 to 0.641) with a sensitivity of 83.41% (95% CI: 79.44% to 86.76%) and a specificity of 27.25% (95% CI 23.11% to 31.81%).

CONCLUSION

Medication data and resident characteristics alone are not sufficient enough to develop a successful CR with a high sensitivity and specificity to predict fall risk in NH-residents.

TRIAL REGISTRATION NUMBER

Not available.

Trends of Nursing Research on Accidental Falls: A Topic Modeling Analysis

This descriptive study analyzed 1849 international and 212 Korean studies to explore the main topics of nursing research on accidental falls. We extracted only nouns from each abstract, and four topics were identified through topic modeling, which were divided into aspects of fall prevention and its consequences. "Fall prevention program and scale" is popular among studies on the validity of fall risk assessment tools and the development of exercise and education programs. "Nursing strategy for fall prevention" is common in studies on nurse education programs and practice guidelines to improve the quality of patient safety care. "Hospitalization by fall injury" is used in studies about delayed discharge, increased costs, and deaths of subjects with fall risk factors hospitalized at medical institutions due to fall-related injuries. "Long-term care facility falls" is popular in studies about interventions to prevent fall injuries that occur in conjunction with dementia in long-term care facilities. It is necessary to establish a system and policy for fall prevention in Korean medical institutions. This study confirms the trends in domestic and international fall-related research, suggesting the need for studies to address insufficient fall-related policies and systems and translational research to be applied in clinical trials.

Technology-Based Fall Risk Assessments for Older Adults in Low-Income Settings: Protocol for a Cross-sectional Study

Background

One-third of older adults have maladaptive fall risk appraisal (FRA), a condition in which there is a discrepancy between the level of fear of falling (FOF) and physiological fall risk (balance performance). Older adults who overestimate their physiological fall risk and report a high FOF are less likely to participate in physical activity. Limited data suggest that the association among FOF, body composition, and physical activity intensity differs by fear severity.

Objective

This study aims to examine the associations among FRA, body composition, and physical activity using assistive health technology, including the BTrackS balance system, bioelectrical impedance analysis, and activity monitoring devices. This study also aims to examine the feasibility of recruitment and acceptability of technologies and procedures for use among older adults in low-income settings.

Methods

This cross-sectional study will be conducted in older adults’ homes or apartments in low-income settings in Central Florida, United States. Following consent, participants will be contacted, and our team will visit them twice. The first visit includes questionnaire completion (eg, sociodemographic or FOF) and balance performance test using the BTrackS balance system. The participants will be stratified by the FRA matrix. In addition, they will perform hand grip strength and dynamic balance performance tests. Participants will then be asked to wear the ActiGraph GT9X Link wireless activity monitor on the nondominant wrist for 7 consecutive days. The second visit includes body composition testing and a structured interview about the acceptability of the technologies and procedures.

Results

Ethical approval was obtained from the institutional review board of the University of Central Florida (protocol number 2189; September 10, 2020). As of December 2020, participation enrollment is ongoing and the results are expected to be published in Summer 2022.

Conclusions

Accurate FRA is essential for implementing physical activity programs, especially in older adults with low income. This study will provide data for developing technology-based fall risk assessments to improve participation in physical activity, thus enhancing healthy longevity among older adults in low-income settings.

International Registered Report Identifier (IRRID)

PRR1-10.2196/27381

Fall prediction in neurological gait disorders: differential contributions from clinical assessment, gait analysis, and daily-life mobility monitoring

Objective

To evaluate the predictive validity of multimodal clinical assessment outcomes and quantitative measures of in- and off-laboratory mobility for fall-risk estimation in patients with different forms of neurological gait disorders.

Methods

The occurrence, severity, and consequences of falls were prospectively assessed for 6 months in 333 patients with early stage gait disorders due to vestibular, cerebellar, hypokinetic, vascular, functional, or other neurological diseases and 63 healthy controls. At inclusion, participants completed a comprehensive multimodal clinical and functional fall-risk assessment, an in-laboratory gait examination, and an inertial-sensor-based daily mobility monitoring for 14 days. Multivariate logistic regression analyses were performed to identify explanatory characteristics for predicting the (1) the fall status (non-faller vs. faller), (2) the fall frequency (occasional vs. frequent falls), and (3) the fall severity (benign vs. injurious fall) of patients.

Results

40% of patients experienced one or frequent falls and 21% severe fall-related injuries during prospective fall assessment. Fall status and frequency could be reliably predicted (accuracy of 78 and 91%, respectively) primarily based on patients' retrospective fall status. Instrumented-based gait and mobility measures further improved prediction and provided independent, unique information for predicting the severity of fall-related consequences.

Interpretation

Falls- and fall-related injuries are a relevant health problem already in early stage neurological gait disorders. Multivariate regression analysis encourages a stepwise approach for fall assessment in these patients: fall history taking readily informs the clinician about patients' general fall risk. In patients at risk of falling, instrument-based measures of gait and mobility provide critical information on the likelihood of severe fall-related injuries.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-021-10504-x.

A prospective cohort study of the risk factors for new falls and fragility fractures in self-caring elderly patients aged 80 years and over

BACKGROUND

This study aimed to prospectively analyze the risk factors for new falls and fragility fractures in self-caring elderly patients and to find suitable evaluation tools for community screening and follow-up interventions.

METHODS

A total of 300 participants (187 male and 113 female), aged 80 or above and capable of caring for themselves, were enrolled in this study and observed for a period of 12 months. Their medical histories were collected, various indicators were measured, and the risk factors for new falls and fragility fractures were analyzed.

RESULTS

A total of 290 participants were included in the statistical analysis. Eighty-seven participants (30%) had new falls. The incidence was negatively correlated with the activities of daily living (ADL, represented by the Barthel Index) score (P=0.008) but was positively correlated with the timed up-and-go (TUG) test score> 12 s (P=0.021). The results also revealed that 33 fragility fractures occurred in 29 patients (10.0%), which was positively correlated with new falls (P=0.000). New fragility fractures were negatively correlated with the bone mineral density (BMD) of the lumbar vertebrae (P=0.012) and walking speed (P=0.000).

CONCLUSION

TUG, walking speed, the ADL score, and the fall risk assessment scale can simply and effectively assess the risk of new falls and fragility fractures in the elderly population, and their use should be widely implemented in the community.

Predicting Falls in Nursing Homes: A Prospective Multicenter Cohort Study Comparing Fall History, Staff Clinical Judgment, the Care Home Falls Screen, and the Fall Risk Classification Algorithm

OBJECTIVES

To evaluate and compare the predictive accuracy of fall history, staff clinical judgment, the Care Home Falls Screen (CaHFRiS), and the Fall Risk Classification Algorithm (FRiCA).

DESIGN

Prospective multicenter cohort study with 6 months' follow-up.

SETTING AND PARTICIPANTS

A total of 420 residents from 15 nursing homes participated.

METHODS

Fall history, clinical judgment of staff (ie, physiotherapists, nurses and nurses' aides), and the CaHFRiS and FRiCA were assessed at baseline, and falls were documented in the follow-up period. Predictive accuracy was calculated at 1, 3, and 6 months by means of sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio, Youden Index, and overall accuracy.

RESULTS

In total, 658 falls occurred and 50.2% of the residents had at least 1 fall with an average fall rate of 1.57 (SD 2.78, range 0-20) per resident. The overall accuracy for all screening methods at all measuring points ranged from 54.8% to 66.5%. Fall history, FRiCA, and a CaHFRiS score of ≥4 had better sensitivity, ranging from 64.4% to 80.8%, compared with the clinical judgment of all disciplines (sensitivity ranging from 47.4% to 71.2%). The negative predictive value (ranging from 92.9% at 1 month to 59.6% at 6 months) had higher scores for fall history, FRiCA, and a CaHFRiS score of ≥4. Specificity ranged from 50.3% at 1 month to 77.5% at 6 months, with better specificity for clinical judgment of physiotherapists and worse specificity for FRiCA. Positive predictive value ranged from 22.2% (clinical judgment of nurses' aides) at 1 month to 67.8% at 6 months (clinical judgment of physiotherapists).

CONCLUSIONS AND IMPLICATIONS

No strong recommendations can be made for the use of any screening method. More research on identifying residents with the highest fall risk is crucial, as these residents benefit the most from multifactorial assessments and subsequent tailored interventions.

Association of Deprescribing With Reduction in Mortality and Hospitalization: A Pragmatic Stepped-Wedge Cluster-Randomized Controlled Trial

OBJECTIVES

Deprescribing has gained awareness recently, but the clinical benefits observed from randomized trials are limited. The aim of this study was to examine the effectiveness of a pharmacist-led 5-step team-care deprescribing intervention in nursing homes to reduce falls (fall risks and fall rates). Secondary aims include reducing mortality, number of hospitalized residents, pill burden, medication cost, and assessing the deprescribing acceptance rate.

DESIGN

Pragmatic multicenter stepped-wedge cluster randomized controlled trial.

SETTING AND PARTICIPANTS

Residents across 4 nursing homes in Singapore were included if they were aged 65 years and above, and taking 5 or more medications.

METHODS

The intervention involved a 5-step deprescribing intervention, which involved a multidisciplinary team-care medication review with pharmacists, physicians, and nurses (in which pharmacists discussed with other team members the feasibility of deprescribing and implementation using the Beers and STOPP criteria) or to an active waitlist control for the first 3 months.

RESULTS

Two hundred ninety-five residents from 4 nursing homes participated in the study from February 2017 to March 2018. At 6 months, the deprescribing intervention did not reduce falls. Subgroup analysis showed that intervention reduced fall risk scores within the deprescribing-naïve group by 0.18 (P = .04). Intervention was associated with a reduction in mortality [hazard ratio (HR) 0.16, 95% confidence interval 0.07, 0.41; P < .001] and number of hospitalized residents (HR 0.16, 95% CI 0.10, 0.26; P < .001). Pre-post analysis witnessed a reduction in pill burden at the end of the study, and a conservative daily cost saving estimate of US$11.42 (SG$15.65) for the study population. Approximately three-quarters of deprescribing interventions initiated by the pharmacists were accepted by the physicians.

CONCLUSIONS AND IMPLICATIONS

Multidisciplinary medication review-directed deprescribing was associated with reductions in mortality and number of hospitalized residents in nursing homes and should be considered for all nursing home residents.

Factors included in adult fall risk assessment tools (FRATs): a systematic review

Falls often have severe financial and environmental consequences, not only for those who fall, but also for their families and society at large. Identifying fall risk in older adults can be of great use in preventing or reducing falls and fall risk, and preventative measures that are then introduced can help reduce the incidence and severity of falls in older adults. The overall aim of our systematic review was to provide an analysis of existing mechanisms and measures for evaluating fall risk in older adults. The 43 included FRATs produced a total of 493 FRAT items which, when linked to the ICF, resulted in a total of 952 ICF codes. The ICF domain with the most used codes was body function, with 381 of the 952 codes used (40%), followed by activities and participation with 273 codes (28%), body structure with 238 codes (25%) and, lastly, environmental and personal factors with only 60 codes (7%). This review highlights the fact that current FRATs focus on the body, neglecting environmental and personal factors and, to a lesser extent, activities and participation. This over-reliance on the body as the point of failure in fall risk assessment clearly highlights the need for gathering qualitative data, such as from focus group discussions with older adults, to capture the perspectives and views of the older adults themselves about the factors that increase their risk of falling and comparing these perspectives to the data gathered from published FRATs as described in this review.

Translating healthcare research evidence into practice: The role of linked boundary objects

Recent years have seen widespread interest in the process of evidence implementation and growth of implementation science. Whilst this work has drawn attention to the challenges and complexities of implementing evidence into everyday practice, for the most part, studies of implementation uphold the ideal of a linear 'pipeline' between research and front-line care. In contrast, this paper adopts a practice perspective on knowledge, and draws on science and technology studies concepts to identify how the socio-material environment contributes to the translation of evidence across multiple organisational and professional boundaries. Findings report on a qualitative case study of implementing fall prevention research evidence at a large teaching hospital in Portugal. Data is from forty-six in-depth semi-structured interviews with clinical and non-clinical staff. The case highlights how linked boundary objects bridge temporally sequential boundaries between research and different practice communities, hence facilitating the translation of research evidence into everyday practice. The initial boundary object (the 'Morse' fall risk assessment scale) contributed to evidence being taken up by specialist nurses within the hospital, while a second boundary object (a pink patient wristband) engendered a change in practice of a wider network of actors. Nevertheless, the symbolic connection between the two linked boundary objects remained precarious, dependent on networks of interaction and communication. The study highlights the role of material objects in the ongoing translation of research evidence into everyday clinical practice.

Semi-Automatic Calibration Method for a Bed-Monitoring System Using Infrared Image Depth Sensors

With the aging of society, the number of fall accidents has increased in hospitals and care facilities, and some accidents have happened around beds. To help prevent accidents, mats and clip sensors have been used in these facilities but they can be invasive, and their purpose may be misinterpreted. In recent years, research has been conducted using an infrared-image depth sensor as a bed-monitoring system for detecting a patient getting up, exiting the bed, and/or falling; however, some manual calibration was required initially to set up the sensor in each instance. We propose a bed-monitoring system that retains the infrared-image depth sensors but uses semi-automatic rather than manual calibration in each situation where it is applied. Our automated methods robustly calculate the bed region, surrounding floor, sensor location, and attitude, and can recognize the spatial position of the patient even when the sensor is attached but unconstrained. Also, we propose a means to reconfigure the spatial position considering occlusion by parts of the bed and also accounting for the gravity center of the patient’s body. Experimental results of multi-view calibration and motion simulation showed that our methods were effective for recognition of the spatial position of the patient.

The Aachen Falls Prevention Scale: Multi-Study Evaluation and Comparison

Background

Fall risk assessment is a time-consuming and resource-intensive activity. Patient-driven self-assessment as a preventive measure might be a solution to reduce the number of patients undergoing a full clinical fall risk assessment.

Objective

The aim of this study was (1) to analyze test accuracy of the Aachen Falls Prevention Scale (AFPS) and (2) to compare these results with established fall risk assessment measures identified by a review of systematic reviews.

Methods

Sensitivity, specificity, and receiver operating curves (ROC) of the AFPS were calculated based on data retrieved from 2 independent studies using the AFPS. Comparison with established fall risk assessment measures was made by conducting a review of systematic reviews and corresponding meta-analysis. Electronic databases PubMed, Web of Science, and EMBASE were searched for systematic reviews and meta-analyses that reviewed fall risk assessment measures between the years 2000 and 2018. The review of systematic reviews was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement. The Revised Assessment of Multiple SysTemAtic Reviews (R-AMSTAR) was used to assess the methodological quality of reviews. Sensitivity, specificity, and ROC were extracted from each review and compared with the calculated values of the AFPS.

Results

Sensitivity, specificity, and ROC of the AFPS were evaluated based on 2 studies including a total of 259 older adults. Regarding the primary outcome of the AFPS subjective risk of falling, pooled sensitivity is 57.0% (95% CI 0.467-0.669) and specificity is 76.7% (95% CI 0.694-0.831). If 1 out of the 3 subscales of the AFPS is used to predict a fall risk, pooled sensitivity could be increased up to 90.0% (95% CI 0.824-0.951), whereas mean specificity thereby decreases to 50.0% (95% CI 0.42-0.58). A systematic review for fall risk assessment measures produced 1478 articles during the study period, with 771 coming from PubMed, 530 from Web of Science, and 177 from EMBASE. After eliminating doublets and assessing full text, 8 reviews met the inclusion criteria. All were of sufficient methodological quality (R-AMSTAR score ≥22). A total number of 9 functional or multifactorial fall risk assessment measures were extracted from identified reviews, including Timed Up and Go test, Berg Balance Scale, Performance-Oriented Mobility Assessment, St Thomas’s Risk Assessment Tool in Falling Elderly, and Hendrich II Fall Risk Model. Comparison of these measures with pooled sensitivity and specificity of the AFPS revealed a sufficient quality of the AFPS in terms of a patient-driven self-assessment tool.

Conclusions

It could be shown that the AFPS reaches a test accuracy comparable with that of the established methods in this initial investigation. However, it offers the advantage that the users can perform the self-assessment independently at home without involving trained health care professionals.

Polypharmacy and potentially inappropriate medication use in older patients with multiple myeloma, related to fall risk and autonomous neuropathy

Purpose

Multiple myeloma is a chronic, uncurable hematological cancer with the involvement of multiple organ systems. As a disease affecting older patients, the treatment of multiple myeloma should be based on individual patient characteristics. Polypharmacy is an increasing problem in the care of older patients and in patients with multiple myeloma, polypharmacy is almost inevitable. We aimed to evaluate the applicability of polypharmacy definitions and the relation of polypharmacy with disease outcomes in patients with multiple myeloma.

Methods

Eighty patients older than 65 years and diagnosed with multiple myeloma were retrospectively enrolled. Patient files, prescriptions, evaluations for polypharmacy were determined according to Beers and START/STOPP criteria. Outcomes were recorded from files in terms of fractures, autonomous neuropathy, and renal functions.

Results

Polypharmacy with ≥4 drugs was observed in 65 patients while polypharmacy with ≥5 drugs was observed in 51 patients. Autonomous neuropathy, polypharmacy with more than four or five medications, and use of multiple medications in the same category were related with poor ECOG performance status in women, while prolonged use of benzodiazepines and central nervous system (CNS) affecting drugs and inappropriate polypharmacy were more frequent in men with poor ECOG performance status. The majority of patients aged 75–84 years were observed to use inappropriate polypharmacy. Autonomous neuropathy and fall risk were observed to be significantly related with inappropriate polypharmacy.

Conclusions

Drugs affecting balance and perception should be reconsidered in patients with multiple myeloma.

Reducing waste in evaluation studies on fall risk assessment tools for older people

OBJECTIVES

To critically appraise the recognition of methodological challenges in evaluation studies on assessment tools and nurses' clinical judgment on fall risk in older people and suggest how to reduce respective research waste.

STUDY DESIGN AND SETTING

Opinion article and narrative review covering systematic reviews on studies assessing diagnostic accuracy and impact of assessment tools and/or nurses' clinical judgment.

RESULTS

Eighteen reviews published in the last 15 years were analyzed. Only one reflects potentially important factors threatening the accuracy of assessments using delayed verification with fall events as reference after a certain period of time, that is, natural course, preventive measures, and treatment paradox where accurate assessment leads to prevention of falls, that is, influencing the reference standard and falsely indicating low diagnostic accuracy. In addition, only one review mentions randomized controlled trials as appropriate study design for the investigation of the impact of fall risk assessment tools on patient-important outcomes. Until now, only one randomized controlled trial dealing with this question has been performed showing no effect on falls and injuries. Instead of investigating the diagnostic accuracy of fall assessment tools, the focus of future research should be on the effectiveness of the implementation of fall assessment tools at reducing falls and injuries.