Journal of Korean Academy of Fundamentals of Nursing
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v.19
no.4
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pp.444-452
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2012
Purpose: To explore the usefulness of previous fall history as a triage variable for inpatients. Methods: Medical records of 21,382 patients, admitted to medical units of one tertiary hospital, were analyzed retrospectively. Inpatient falls were identified from the hospital's self-report system. Non-falls in 1,125 patients were selected by a stratified matching sampling with 125 patients with falls (0.59%). A comparative and predictive accuracy analysis was conducted to describe differences between the two groups with and without a history of falls. Logistic regression was used to measure the effect size of the fall history. Results: The fall history group showed higher prevalence by 9 fold than the non-fall history group. The relationships between falls and relevant variables which were significant in the non-fall history group, were not significant for the fall history group. Falls in the fall history group were 25 times more likely than in the non-fall group. Predictive accuracy of the risk assessment tool showed almost zero specificity in the fall history group. Conclusion: The presence of fall history, the fall prevalence, variables relevant to falls, and the accuracy of the risk tool were different, which support the usefulness of the fall history as a triage variable.
Purpose: The purpose of the study was to validate fall risk assessment scales among hospitalized adult patients in South Korea using the electronic medical records by comparing sensitivity, specificity, positive predictive values, and negative predictive values of Morse Fall Scale (MFS), Bobath Memorial Hospital Fall Risk Assessment Scale (BMFRAS), and Johns Hopkins Hospital Fall Risk Assessment tool (JHFRAT). Methods: A total of 120 patients who experienced fall episodes during their hospitalization from June 2010 to December 2013 was categorized into the fall group. Another 120 patients, who didn't experience fall episodes with age, sex, clinical departments, and the type of wards matched with the fall group, were categorized to the comparison group. Data were analyzed for the comparisons of sensitivity, specificity, positive and negative predictive values, and the area under the curve of the three tools. Results: MFS at a cut-off score of 48 had .806 for ROC curves, 76.7% for sensitivity, 77.5% for specificity, 77.3% for positive predictive value, and 76.9% for negative predictive value, which were the highest values among the three fall assessment scales. Conclusion: The MFS with the highest score and the highest discrimination was evaluated to be suitable and reasonable for predicting falls of inpatients in med-surg units of university hospitals.
Purpose: This study was conducted to verify fall predictive power and reasonable fall risk assessment tool by a comparative analysis of the sensitivity, specificity, positive forecast and negative forecast of each tool by applying Morse Fall Scale (MFS), Johns Hopkins Fall Risk Assessment Tool (JHFRAT), and Fall Assessment Scale-Korean version (FAS-K) through electronic medical records to adult patients hospitalized in a general hospital in Korea. Methods: We performed a retrospective evaluation study from January to December 2018, 123 fall groups experiencing falls during hospitalization and 123 non-falls groups were selected. Data presented a reasonable assessment tool that predicts and distinguishes fall high-risk patients through area comparison based on the ROC curve for each tool. Results: In the ROC curve analysis by fall risk assessment group, the AUC of MFS is shown to be .706 (good), JHFRAT is shown to be .649 (sufficient) and FAS-K is shown to be .804 (very good). FAS-K at a cut-off score of 4, sensitivity, specificity, and positive and negative prediction values were 83.7%, 60.2%, 67.8%, and 78.7%, respectively. Conclusion: Based on the above findings, it is believed that the FAS-K was presented as a suitable and reasonable tool for predicting falls for adult patients in general hospitals.
Purpose: This study aimed to investigate the factors that increase fall risk in the residential environment and the perceived fall risk among community-dwelling elderly through comparisons between fallers and non-fallers. Methods: The subjects were 95 community-dwelling elderly aged 65 years and over residing in the metropolitan city of Ulsan. A structured questionnaire consisting of items on sociodemographics and health- and fall-related characteristics was used and data were collected from July to August 2015. The data were analyzed with the SPSS/WIN program. Results: Among recent fallers, 38.9% had diagnosed diseases when the fall occurred, 56.87% were fearful of a recurrent fall, and 86.5% stated that they were increasing their carefulness but that had led to a decrease in activity. There were significant differences between elders who had fallen at least once and elders who had no falls in age, health status, depression, the experience of falling, fear of falling, diseases, and medications. Conclusion: The results indicate a need to assess risk factors to identify older adults with a high risk for falling and the need to develop multifactorial intervention programs that consider both environmental and perceived risk factors as well as physical risk factors to reduce and prevent falls among the elderly.
Sohng, Kyeong-Yae;Park, Mi Hwa;Chaung, Seung Kyo;Park, Hye Ja
Journal of Korean Public Health Nursing
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v.28
no.3
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pp.495-508
/
2014
Purpose: This study was conducted in order to evaluate the reliability, validity, sensitivity, and specificity of the Short Form of Bobath Memorial Hospital Fall Risk Assessment Scale (BMFRAS-SF). Methods: A validation study was conducted on 207 elderly patients aged over 65 who were admitted to Bobath Memorial Hospital. Fall risk scores of BMFRAS, composed of eight subscales (age, fall history, physical activity, consciousness level, communication, fall risk factors, underlying disease, and medications) were assessed from the electronic medical record. BMFRAS-SF was derived from eight subscales of the BMFRAS representing the significance between fallers and non-fallers (fall history, physical activity, fall risk factors, underlying disease, and medications). Internal consistency reliability and interrater reliability were assessed by Cronbach's alpha and kappa coefficient. Validity was assessed by Spearman correlation analysis, factor analysis. Sensitivity, specificity, positive predictive and negative predictive values, and a receiver-operating characteristic curve (ROC) were generated. Results: Fallers had significantly higher risk scores than non-fallers in fall history, physical activity, fall risk factors, underlying disease, and medication scales. The BMFRAS-SF demonstrated acceptable Cronbach's alpha (.706) and kappa coefficients of .95. The BMFRAS-SF subscales showed good convergent validity and construct validity. The BMFRAS-SF presented good sensitivity(86.7%), specificity(67.9%), positive predictive value(42.9%) and good negative predictive value(94.8%) at a cut-off score of 5. Areas under the ROC curves were .860 for the BMFRAS and .861 for the BMFRAS-SF. Conclusion: The BMFRAS-SF was proved to be reliable and valid. It could be used for time-saving assessment and evaluation of the high risks for falls in clinical practice settings.
Background : To estimate fall incidence rate and associated factors in inpatients from a general hospital. Method : The data were collected from 104 fall incident reports developed by the patient safety committee in a general hospital in Seoul from 01 January 2007 to 31 December 2008. Information included general characteristics of patients, factors related to fall, types, places, circumstances and outcomes of fall. Result : The incidence rate of fall, which was 4.4 per 1,000 total discharged patients and 0.5 per 1,000 patient-days, was much lower than that of several hospitals in the United States. The difference may reflect the different incidence reporting system of each hospital. Fall-prone patients were, in general, $$\geq_-$$65 years of age, had an alert mental status, were ambulatory with some assistance, and were dependent on and ambulatory device. High incidence of falls was associated with patients with circulatory disease. The majority of fall events usually occurred in bed or at the bedside in the patient's room, and occurred more often during the night than during the day or evening. Risk factors of fall were use of drugs (antihypertensive or neuropsychiatric drugs) and environmental factors (e.g., overly high bed height, surrounding objects, inadequate fitness shoes and slippery floor). Physical injury occurred in 43.3% of fall events, which typically required diagnosis of injury and treatment such as suturing. Risk factors for repeated falls were use of a neuropsychiatric drug (odds ratio=13.9) and gait disturbance (odds ratio=91.2). Risk factors for fall-related injury were alert mental status (odds ratio=3.3 times more likely to fall than those who were drowsy or in a stupor) and general weakness(odds ratio=3.3 times more likely to fall than those who were not generally weak). Conclusion : Medical and nursing staff should be aware of the fall risk factors of hospitalized patients and should intensively pursue preventative strategies. Development of fall prevention education based on these results is recommended.
Purpose: This study is to determine the predictive validity of the St. Thomas Risk Assessment Tool in Falling Elderly Inpatients (STRATIFY) for inpatients' fall risk. Methods: A literature search was performed to identify all studies published between 1946 and 2014 from periodicals indexed in Ovid Medline, Embase, CINAHL, KoreaMed, NDSL and other databases, using the following key words; 'fall', 'fall risk assessment', 'fall screening', 'mobility scale', and 'risk assessment tool'. The QUADAS-II was applied to assess the internal validity of the diagnostic studies. Fourteen studies were analyzed using meta-analysis with MetaDisc 1.4. Results: The predictive validity of STRATIFY was as follows; pooled sensitivity .75 (95% CI: 0.72~0.78), pooled specificity .69 (95% CI: 0.69~0.70) respectively. In addition, the pooled sensitivity in the study that targets only the over 65 years of age was .89 (95% CI: 0.85~0.93). Conclusion: The STRATIFY's predictive validity for fall risk is at a moderate level. Although there is a limit to interpret the results for heterogeneity between the literature, STRATIFY is an appropriate tool to apply to hospitalized patients of the elderly at a potential risk of accidental fall in a hospital.
Choi, Eun Hee;Ko, Mi Suk;Lee, Shin Ae;Park, Jung Ha
Journal of Korean Clinical Nursing Research
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v.26
no.2
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pp.265-273
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2020
Purpose: The purpose of this study was to test the predictive validity of the Fall Assessment Scale-Korean version (FAS-K) and to find the most appropriate cutoff score to screen high-risk fall groups in adult patients in general hospitals in Korea. Methods: We performed a prospective evaluation study in medical and surgical ward patients at two major general hospitals in Seoul. Data were collected from Nov. 1, 2018 to Feb. 28, 2019, nurses performed 651 observation series. The researcher measured the fall risk assessment score by applying FAS-K, MFS (Morse Fall Scale), and JHFRAT (Johns Hopkins Hospital Fall Risk Assessment tool) to the patients twice a week between 10 am and 12 noon. Data were analyzed using Pearson's corelation coefficients, and the sensitivity, specificity, predictive value, and the area under the curve (AUC) of the three tools. Results: The FAS-K was positively correlated with the MFS (r=.70, p<.001) and the JHFRAT (r=.82, p<.001). According to the receiver operating characteristics (ROC) curve analysis of the FAS-K, sensitivity, specificity, and positive and negative prediction values were 85.3%, 49.4%, 8.5%, and 98.4%, respectively, when the FAS-K score was 4. Therefore, the cut-off score of the FAS-K to identify groups with high fall risk was 4. Conclusion: The FAS-K is a valid tool for measuring fall risk in adult inpatients. In addition, the FAS-K score, 4, can be used to identify high-risk fall groups and know specific points in time to provide active interventions to prevent falls.
Purpose: Patients' perception of fall risk is a promising new indicator for fall prevention. Therefore, a fall risk perception questionnaire that can be used rapidly and repeatedly in acute care settings is required. This study aimed to develop a short version of the fall risk perception questionnaire (Short-FRPQ) for inpatients. Methods: For the psychometric measurements, 246 inpatients were recruited from an acute care hospital. The construct (using confirmatory factor analysis and discriminant validity of each item), convergent, and known-group validities were tested to determine the validity of the Short-FRPQ. McDonald's omega coefficient was used to examine the internal consistency of reliability. Results: In the confirmatory factor analysis, the fit indices of the Short-FRPQ, comprising 14 items and three factors, appeared to be satisfactory. The Short-FRPQ had a significantly positive correlation with the original scale, the Korean Falls Efficacy Scale-International, and the Morse Fall Scale. The risk of falls group, assessed using the Morse Fall Scale, had a higher score on the Short-FRPQ. McDonald's omega coefficient was .90. Conclusion: The Short-FRPQ presents good reliability and validity. As patient participation is essential in fall interventions, evaluating the fall risk perception of inpatients quickly and repeatedly using scales of acceptable validity and reliability is necessary.
Junwoo Park;Jongwon Choi;Seyoung Lee;Kitaek Lim;Woochol Joseph Choi
Physical Therapy Korea
/
v.30
no.2
/
pp.102-109
/
2023
Background: While efforts have been made to differentiate fall risk in older adults using wearable devices and clinical methodologies, technologies are still infancy. We applied a decision tree (DT) algorithm using inertial measurement unit (IMU) sensor data and clinical measurements to generate high performance classification models of fall risk of older adults. Objects: This study aims to develop a classification model of fall risk using IMU data and clinical measurements in older adults. Methods: Twenty-six older adults were assessed and categorized into high and low fall risk groups. IMU sensor data were obtained while walking from each group, and features were extracted to be used for a DT algorithm with the Gini index (DT1) and the Entropy index (DT2), which generated classification models to differentiate high and low fall risk groups. Model's performance was compared and presented with accuracy, sensitivity, and specificity. Results: Accuracy, sensitivity and specificity were 77.8%, 80.0%, and 66.7%, respectively, for DT1; and 72.2%, 91.7%, and 33.3%, respectively, for DT2. Conclusion: Our results suggest that the fall risk classification using IMU sensor data obtained during gait has potentials to be developed for practical use. Different machine learning techniques involving larger data set should be warranted for future research and development.
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