The Fall Risk Screening Scale Is Suitable for Evaluating Adult Patient Fall

Chen, Li‐Chen; Shen, Yung-Chao; Ho, Lun‐Hui; Shih, Whei-Mei

doi:10.3390/healthcare10030510

Cited by 5 publications

(5 citation statements)

References 21 publications

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“…This result is consistent with previously mentioned research of the Medicare system, as fall events demonstrated a decrease in hospitalized patients within 4 major medical conditions between 2010 and 2019 28 . Screening for patient falls has become a routine part of admission procedures in all of Taiwan’s hospitals 29,30 . Similarly, we noted reductions in the incidence and severity of tube-related MAEs.…”

Section: Discussionsupporting

confidence: 92%

“…28 Screening for patient falls has become a routine part of admission procedures in all of Taiwan's hospitals. 29,30 Similarly, we noted reductions in the incidence and severity of tube-related MAEs. Reducing tube-related MAEs was incorporated into national patient safety goals in 2008, 31 and since then, remarkable improvements have been achieved in the establishment of standard operating procedures for restraining patients, in communication with patients and their families, and in early tracheotomy interventions.…”

Section: Discussionsupporting

confidence: 61%

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Trend Analysis of Inpatient Medical Adverse Events in Taiwan (2014–2020): Findings From Taiwan Patient Safety Reporting System

Munkhtogoo,

Liu,

Hung

et al. 2024

J Patient Saf

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Objectives Medical adverse event (MAE) reporting and management are essential for patient safety campaigns. An epidemiological assessment of MAE trends is crucial for understanding the effectiveness of patient safety improvement efforts. This study analyzed the trends of inpatient MAEs, focusing on MAE incidence and harm severity. Methods Longitudinal secondary data (over 2014–2020) on MAEs reported by 18 hospitals were retrieved from the Taiwan Patient-safety Reporting system. The numbers and incidence rates (per 1000 inpatient days) of reported MAEs were calculated. The harm severity levels of six major MAE categories were analyzed. Trend and generalized estimating equation analyses were conducted to investigate changes in MAE patterns. Results Trend analyses revealed significant decreasing trends in the number (4763–3107 per year; Jonckheere-Terpstra test = −1.952, P = 0.05) and incidence rates (0.92–0.62 per 1000 inpatient days; β = −0.5017, P = 0.00) of harmful MAEs over 7-year study period. Among the most frequently reported MAEs, tube-related events exhibited the most significant decreasing trend (28%–23.8%; Jonckheere-Terpstra test = −2.854, P = 0.00). The reported numbers, incidence rates, and severity of falls and tube-related events dropped significantly. Conclusions By analyzing representative longitudinal MAE data, this study demonstrated the effectiveness of nationwide patient safety improvement campaigns in Taiwan. Our data reveal significant reductions in the reported numbers, incidence rates, and severity of several major MAEs. Specifically, our data indicate significant reductions in the incidence and severity of tube-related events, which can be beneficial for patient safety improvement efforts.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionsupporting

confidence: 61%

Trend Analysis of Inpatient Medical Adverse Events in Taiwan (2014–2020): Findings From Taiwan Patient Safety Reporting System

Munkhtogoo,

Liu,

Hung

et al. 2024

J Patient Saf

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“…A shorter fall assessment time means that the patient can be moved to the next stage of day surgery care more quickly, reducing the time spent waiting for assessment results. Also, more patients can be screened per unit of time, leading to a higher volume of patients being managed efficiently (Chen et al, 2022; Strini et al, 2021). Reducing the assessment time of falls while ensuring patient safety is an important aspect of a viable solution to increase work efficiency (Jellett et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Timely cataract surgery can be effective in improving visual function and decreasing fall risk, although there are still many potential fall risk factors in day surgery settings (Gutiérrez‐Robledo et al, 2021; Keay et al, 2022). Fall risk assessment in identifying patients at different risks is the most important step in preventing falls and avoiding their consequences (Chen et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a concise fall risk stratification among older adults with cataracts in day surgery settings: A historically controlled study

Wang,

Dai,

Ou‐yang

et al. 2023

Japan Journal Nursing Sci

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AimThis study aimed to evaluate the use of a concise fall risk stratification in assessing and predicting falls compared with the Morse Falls Scale among older adults with cataracts in day surgery settings.MethodsA historically controlled study conducted from July 2020 to June 2022 was used in a municipal ophthalmic hospital in China. The concise fall risk stratification which directly graded fall risk by multifactorial judgment was used during the intervention period, while the Morse Falls Scale which graded fall risk by scale scores was used during the control period. The fall risk levels, fall assessment time, fall rates, fall‐related injuries, predictive validity, and patient satisfaction with day surgery care were extracted. Propensity score matching was performed to balance baselines.ResultsAfter matching, 4132 patients were included in the final analysis. Compared with the control group, the intervention group had significantly higher assessment results for fall risk level, a significantly shorter (by 48.15%) fall assessment time, and higher patient satisfaction. There were no differences in fall rates and fall‐related injuries. Compared with the Morse Falls Scale, the concise fall risk stratification had higher sensitivity and negative predictive validity, and lower specificity and positive predictive validity, while the area under curve did not differ significantly.ConclusionThe use of the concise fall risk stratification reduced fall assessment time, improved patient satisfaction, and is unlikely to impact falls with an overall predictive performance comparable to that of the Morse Falls Scale for older cataract adults in day surgery settings.

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“…Multiple fall prediction models have been developed to prevent falls. [4][5][6] These models have often been designed for specific settings, including community-dwelling individuals (outpatients), 7 older inpatients, 8 acute care hospitals, 9 tertiary hospitals, 10 rehabilitation wards, 11,12 patients with liver cirrhosis, 13 patients with chronic obstructive pulmonary disease, 14 and long-term care facilities. 15,16 These prediction models are typically intended for specific populations and settings.…”

Section: Introductionmentioning

confidence: 99%

Validation and Improvement of the Saga Fall Risk Model: A Multicenter Retrospective Observational Study

Tago,

Hirata,

Katsuki

et al. 2024

CIA

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Purpose We conducted a pilot study in an acute care hospital and developed the Saga Fall Risk Model 2 (SFRM2), a fall prediction model comprising eight items: Bedriddenness rank, age, sex, emergency admission, admission to the neurosurgery department, history of falls, independence of eating, and use of hypnotics. The external validation results from the two hospitals showed that the area under the curve (AUC) of SFRM2 may be lower in other facilities. This study aimed to validate the accuracy of SFRM2 using data from eight hospitals, including chronic care hospitals, and adjust the coefficients to improve the accuracy of SFRM2 and validate it. Patients and Methods This study included all patients aged ≥20 years admitted to eight hospitals, including chronic care, acute care, and tertiary hospitals, from April 1, 2018, to March 31, 2021. In-hospital falls were used as the outcome, and the AUC and shrinkage coefficient of SFRM2 were calculated. Additionally, SFRM2.1, which was modified from the coefficients of SFRM2 using logistic regression with the eight items comprising SFRM2, was developed using two-thirds of the data randomly selected from the entire population, and its accuracy was validated using the remaining one-third portion of the data. Results Of the 124,521 inpatients analyzed, 2,986 (2.4%) experienced falls during hospitalization. The median age of all inpatients was 71 years, and 53.2% were men. The AUC of SFRM2 was 0.687 (95% confidence interval [CI]:0.678–0.697), and the shrinkage coefficient was 0.996. SFRM2.1 was created using 81,790 patients, and its accuracy was validated using the remaining 42,731 patients. The AUC of SFRM2.1 was 0.745 (95% CI: 0.731–0.758). Conclusion SFRM2 showed good accuracy in predicting falls even on validating in diverse populations with significantly different backgrounds. Furthermore, the accuracy can be improved by adjusting the coefficients while keeping the model’s parameters fixed.

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The Fall Risk Screening Scale Is Suitable for Evaluating Adult Patient Fall

Cited by 5 publications

References 21 publications

Trend Analysis of Inpatient Medical Adverse Events in Taiwan (2014–2020): Findings From Taiwan Patient Safety Reporting System

Trend Analysis of Inpatient Medical Adverse Events in Taiwan (2014–2020): Findings From Taiwan Patient Safety Reporting System

Evaluation of a concise fall risk stratification among older adults with cataracts in day surgery settings: A historically controlled study

Validation and Improvement of the Saga Fall Risk Model: A Multicenter Retrospective Observational Study

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