scholarly journals Proposals for continued research to determine older adults’ falls risk

2020 ◽  
Vol 05 (04) ◽  
pp. 89-91
Author(s):  
Beatrice Pettersson ◽  
Ellinor Nordin ◽  
Anna Ramnemark ◽  
Lillemor Lundin-Olsson
Keyword(s):  
Older Adults ◽  
Risk Assessment ◽  
Fall Risk ◽  
Assessment Tools ◽  
Risk Of Falling ◽  
Self Assessment ◽  
Preventative Measures ◽  
Increased Risk ◽  
Risk Assessment Tools ◽  
Falls Prediction

Early detection of older adults with an increased risk of falling could enable early onset of preventative measures. Currently used fall risk assessment tools have not proven sufficiently effective in differentiating between high and low fall risk in community-living older adults. There are a number of tests and measures available, but many timed and observation-based tools are performed on a flat floor without interaction with the surrounding. To improve falls prediction, measurements in other areas that challenge mobility in dynamic conditions and that take a persons’ own perception of steadiness into account should be further developed and evaluated as single or combined measures. The tools should be easy to apply in clinical practice or used as a self-assessment by the older adults themselves.

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

2020 ◽  
pp. 1-25
Author(s):  
Hendrika de Clercq ◽  
Alida Naudé ◽  
Juan Bornman
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Risk Assessment ◽  
Fall Risk ◽  
The Body ◽  
Assessment Tools ◽  
Personal Factors ◽  
Fall Risk Assessment ◽  
Environmental Consequences ◽  
Preventative Measures

Abstract 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.

scholarly journals Validated Fall Risk Assessment Tools for Use with Older Adults: A Systematic Review

2018 ◽  
Vol 36 (4) ◽  
pp. 331-353 ◽  
Author(s):  
Marcello Ruggieri ◽  
Biagio Palmisano ◽  
Giancarlo Fratocchi ◽  
Valter Santilli ◽  
Roberta Mollica ◽  
...  
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Risk Assessment ◽  
Fall Risk ◽  
Assessment Tools ◽  
Fall Risk Assessment ◽  
Risk Assessment Tools

scholarly journals Coping with adequate and inadequate self-assessment of older people’s risk of falling: a mixed-methods study in Germany.

2019 ◽  
Author(s):  
Nicole Strutz ◽  
Hanna Brodowski ◽  
Sandra Mümken ◽  
Ursula Müller-Werdan ◽  
Jörn Kiselev
Keyword(s):  
Older People ◽  
Coping Strategies ◽  
Fall Risk ◽  
Qualitative Content Analysis ◽  
Self Awareness ◽  
Risk Of Falling ◽  
Self Assessment ◽  
Functional Changes ◽  
Positive Coping ◽  
Increased Risk

Abstract Background: Older people are exposed to an increased risk of falling due to a multitude of physiological and functional changes and fear of falling. The risk of falling is assessed and managed differently. It should be found out whether the coping strategies of older people differ with regard to their activities in daily life depending on the adequacy of their self-assessed fall risk. Methods: Adequacy of the perceived fall risk was evaluated with the de Morton Mobility Index and the Activities-specific Balance Confidence Scale among 100 older people. Additionally, semi-structured interviews were conducted in 16 participants with an identified fall risk. Coding techniques, based on structuring qualitative content analysis and the half-split method were applied. Results: Six out of 16 interviewees assessed their fall risk adequately. Interviews with the seniors resulted in topics such as coping strategies and awareness and several sub-topics in each category. Participants who adequately assessed their own fall risk reported an “active/positive” coping behavior and awareness of themselves. In contrast, those who assessed their own risk of falling inadequately covered all identified categories with no identifiable pattern. Conclusion: An adequate self-assessment of fall risks is accompanied by positive coping strategies to maintain an active lifestyle. In contrast, a lack of an adequate self-awareness seems to lead to arbitrary coping strategies. Assisting older people in their self-awareness regarding their own fall risk should be emphasized in order to adopt positive coping strategies. Future studies are necessary to better understand the underlying mechanisms that lead to an adequate or inadequate self-assessment in older people fall risk.

scholarly journals Novel Approach to Inpatient Fall Risk Prediction and Its Cross-Site Validation Using Time-Variant Data (Preprint)

2018 ◽  
Author(s):  
Insook Cho ◽  
Eun-Hee Boo ◽  
Eunja Chung ◽  
David W. Bates ◽  
Patricia Dykes
Keyword(s):  
Risk Assessment ◽  
Error Rate ◽  
Fall Risk ◽  
Assessment Tool ◽  
Assessment Tools ◽  
Fall Risk Assessment ◽  
C Statistic ◽  
Risk Assessment Tools ◽  
Hospital Days ◽  
Cross Site

BACKGROUND Electronic medical records (EMRs) contain a considerable amount of information about patients. The rapid adoption of EMRs and the integration of nursing data into clinical repositories have made large quantities of clinical data available for both clinical practice and research. OBJECTIVE In this study, we aimed to investigate whether readily available longitudinal EMR data including nursing records could be utilized to compute the risk of inpatient falls and to assess their accuracy compared with existing fall risk assessment tools. METHODS We used 2 study cohorts from 2 tertiary hospitals, located near Seoul, South Korea, with different EMR systems. The modeling cohort included 14,307 admissions (122,179 hospital days), and the validation cohort comprised 21,172 admissions (175,592 hospital days) from each of 6 nursing units. A probabilistic Bayesian network model was used, and patient data were divided into windows with a length of 24 hours. In addition, data on existing fall risk assessment tools, nursing processes, Korean Patient Classification System groups, and medications and administration data were used as model parameters. Model evaluation metrics were averaged using 10-fold cross-validation. RESULTS The initial model showed an error rate of 11.7% and a spherical payoff of 0.91 with a c-statistic of 0.96, which represent far superior performance compared with that for the existing fall risk assessment tool (c-statistic=0.69). The cross-site validation revealed an error rate of 4.87% and a spherical payoff of 0.96 with a c-statistic of 0.99 compared with a c-statistic of 0.65 for the existing fall risk assessment tool. The calibration curves for the model displayed more reliable results than those for the fall risk assessment tools alone. In addition, nursing intervention data showed potential contributions to reducing the variance in the fall rate as did the risk factors of individual patients. CONCLUSIONS A risk prediction model that considers longitudinal EMR data including nursing interventions can improve the ability to identify individual patients likely to fall.

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