Diagnostic validity of the STRATIFY and Downton instruments for evaluating the risk of falls by hospitalised acute-care patients: a multicentre longitudinal study

Aranda-Gallardo, Marta; Luna-Rodríguez, Margarita Enríquez de; Vazquez-Blanco, M. José; Canca-Sánchez, José Carlos; Moya-Suárez, Ana Belén; Morales-Asencio, José Miguel

doi:10.1186/s12913-017-2214-3

Cited by 16 publications

(13 citation statements)

References 27 publications

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“…24 The sensitivity and specificity of the fall risk assessment tool were lower than those previously reported for the STRATIFY. 25 They were also lower than the results reported in a systematic review by Matarese et al 13 The positive and negative predictive values were similar to those reported in a study 17 where an MFS cutoff score of 50 was used for neurological patients. The sensitivity, specificity, and predictability of the tool were low overall, which suggests the need to develop a tool reflecting the characteristics of the clinical setting to accurately predict falls.…”

Section: Discussionsupporting

confidence: 64%

Factors Influencing Falls in High- and Low-Risk Patients in a Tertiary Hospital in Korea

et al. 2019

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Objective The purpose of this study was to explore the characteristics and predictors of falls in high- and low-risk inpatients in a tertiary hospital in Korea. Methods Fallers' data were extracted from quality improvement reports and electronic health records from June 1, 2014, to May 31, 2015. Data on nonfallers matched by the length of hospitalization and medical departments of fallers were extracted from electronic health records. Participants were classified into a high- or a low-risk group based on their Morse Fall Scale score, fall risk–related symptoms, and medications known to increase fall risk. Characteristics of falls and risk factors were analyzed using descriptive statistics and logistic regression analysis, respectively. Results In the high-risk group, education, surgery, department, impaired mobility, intravenous catheter placement, use of ambulatory aid, gait disturbance, and some medications were significantly different between the fallers and nonfallers. From these variables, education, operation, department, intravenous catheter placement, gait disturbance, and use of narcotics, vasodilators, antiarrhythmics, and hypnotics were statistically significant factors for falls. In the low-risk group, sex, age, length of hospitalization, surgery, department, diagnosis, and mental status were significantly different between the fallers and nonfallers. From these, sex, age, length of hospitalization, surgery, and liver-digestive diseases were statistically significant factors for falls. Conclusions Characteristics and risk factors for falls differed between the risk groups. Fall prevention strategies need to be tailored to the risk groups and fall risk assessment tools need to be revised accordingly.

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Section: Discussionsupporting

confidence: 64%

Factors Influencing Falls in High- and Low-Risk Patients in a Tertiary Hospital in Korea

et al. 2019

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“…Among the models that have been tested in different clinical groups (Aranda‐Gallardo, Luna‐Rodrigues, Vazquez‐Blanco, Canca‐Sanchez, & Morales‐Asencio, ; Poe et al., ) there has been substantial variability in sensitivity and specificity values: the Morse Fall Scale (sensitivity 78%, specificity 83%) (Morse et al., ); the STRATIFY tool (score ≥2 sensitivity 92%, specificity 68% and score ≥3 sensitivity 54%, specificity 88%) (Oliver et al., ); the Hendrich II Fall Risk Model (sensitivity 74%, specificity 73%) (Hendrich et al., ) and the Johns Hopkins Fall Risk Assessment Tool (sensitivity 69%, specificity 60%) (Poe et al., ).…”

Section: Introductionmentioning

confidence: 99%

A predictive model for fall risk in hospitalized adults: A case–control study

Severo

Kuchenbecker

Vieira

et al. 2018

Journal of Advanced Nursing

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Aim:To develop and validate a predictive model for falls in hospitalized adult clinical and surgical patients, assessing intrinsic (i.e. patient-related) and extrinsic factors (i.e. care process-related). Background:To identify factors predictive of falls and enable appropriate management of fall risk it is necessary to understand patient and environmental factors, along with care delivery processes. Design:A matched case-control study. Methods:This study was conducted in the medical and surgical wards of a Brazilian teaching hospital. The sample included 536 patients, with data collected in 2013- Data analysis included descriptive statistics and conditional logistic regression.Cases of patients aged 18 years or older who fell while hospitalized were included.One patient who did not fall during hospitalization, matched by sex, ward and admission date, was selected as a control for each included case. Results: The SAK Fall Scale (Severo-Almeida-Kuchenbecker) was developed and validated. The scale includes seven variables: disorientation/confusion, frequent urination, walking limitations, lack of caregiver, postoperative status, previous falls and number of medications administered within 72 hr prior to the fall. This scale showed acceptable predictive accuracy. Conclusions: The newly developed SAK Fall Scale includes five intrinsic and two extrinsic variables and differs from other predictive scales for falls. The findings of this study are broad and the scale, which is easy to apply, can be used worldwide by nurses in health services. In advanced practice, the testing of a new model for fall risk contributes to preventive interventions and thus has an impact on patient safety. K E Y W O R D S adult, advanced practice, falls, nurses, patient safety, risk management *Member of the Study Group on Adult and Elderly Care -GEPECADI -CNPq.• The study gives data for a new prediction model that should be used to predict fall risk.• The findings should be used to support the care and safety of hospitalized clinical and surgical patients. 564 | SEVERO ET AL.

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“…The compilation of the scale is not performed through direct observation of the patient, but the evaluator reports the score based on information obtained from the previous observation or from other caregivers. STRATIFY has been extensively studied in intensive care units in Australia, Europe and Canada [ 48 ] and has also been applied in numerous geriatric and rehabilitation departments [ 49 ]. In these contexts, it has long been considered the “Gold standard” tool to be used at patient admission thanks to the high sensitivity value demonstrated by numerous studies (between 73.7% and 93.0%) and the simplicity and speed of application (3 min).…”

Section: Discussionmentioning

confidence: 99%

Fall Risk Assessment Scales: A Systematic Literature Review

Strini

Schiavolin

Prendin³

2021

Nursing Reports

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Background: Falls are recognized globally as a major public health problem. Although the elderly are the most affected population, it should be noted that the pediatric population is also very susceptible to the risk of falling. The fall risk approach is the assessment tool. There are different types of tools used in both clinical and territorial settings. Material and methods: In the month of January 2021, a literature search was undertaken of MEDLINE, CINHAL and The Cochrane Database, adopting as limits: last 10 years, abstract available, and English and Italian language. The search terms used were “Accidental Falls” AND “Risk Assessment” and “Fall Risk Assessment Tool” or “Fall Risk Assessment Tools”. Results: From the 115 selected articles, 38 different fall risk assessment tools were identified, divided into two groups: the first with the main tools present in the literature, and the second represented by tools of some specific areas, of lesser use and with less supporting literature. Most of these articles are prospective cohort or cross-sectional studies. All articles focus on presenting, creating or validating fall risk assessment tools. Conclusion: Due to the multidimensional nature of falling risk, there is no “ideal” tool that can be used in any context or that performs a perfect risk assessment. For this reason, a simultaneous application of multiple tools is recommended, and a direct and in-depth analysis by the healthcare professional is essential.

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Diagnostic validity of the STRATIFY and Downton instruments for evaluating the risk of falls by hospitalised acute-care patients: a multicentre longitudinal study

Cited by 16 publications

References 27 publications

Factors Influencing Falls in High- and Low-Risk Patients in a Tertiary Hospital in Korea

Factors Influencing Falls in High- and Low-Risk Patients in a Tertiary Hospital in Korea

A predictive model for fall risk in hospitalized adults: A case–control study

Fall Risk Assessment Scales: A Systematic Literature Review

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