Evaluation of falls by inpatients in an acute care hospital in Korea using the Morse Fall Scale

Abstract

The purpose of this study was to determine the cut-off values of the Korean version of the Morse Fall Scale (MFS-K) that would be most useful in identifying hospitalized patients at risk of falls in an acute-care setting in Korea. This study was conducted using the medical records of 66 patients who fell and 100 patients who did not fall (no-fall patients) sampled from inpatients hospitalized at a tertiary acute-care hospital in Seoul during the period from 1 January to 30 November 2009. The optimal cut-off point for the MFS-K was found to be 45 points, which produced an acceptable sensitivity and a fairly good specificity, negative predictive value and accuracy. The highest peak on the receiver operating characteristic curve was a cut-off score of 45 points in the MFS-K. Further research needs to be performed to determine the optimal cut-off score according to subjects' conditions through daily measurement with the MFS in medical or surgical patients who are relatively homogeneous in terms of individual and disease-related factors.

Evaluation of the safety of hospitalized older adults as for the risk of falls

“…The results showed: about 52% of older adults hospitalized who were part of this study had high risk for falls according to the Morse scale score. In South Korea, 50% of patients had high risk of falls (30) . In a study conducted with patients from 18 to 88 years old in a hospital in Spain, it was assessed the risk of falls and then the falls that occurred throughout hospitalization.…”

Validity of Tools for Assessing the Risk of Falls in Patients

“…These retrieved studies (Table 2) were analyzed and data on their validity were identified ( Table 1). The most common fall risk assessment tool was the Morse Fall Scale (MFS) tested in 8 studies, including one in which the scale was adapted for use in the South Korean healthcare system (Sung et al, 2014), followed by the Hendrich II Fall Risk Model (5 studies). Four studies validated the St Thomas's Risk Assessment Tool in Falling Elderly Inpatients (STRATIFY); in one, the scale was modified as The Northern Hospital Modified St Thomas's Risk Assessment Tool (TNH-STRATIFY).…”

Predictive Value of the Morse Fall Scale

“…Sensitivity and specificity have an inverse relationship: i.e., high sensitivity may be achieved at the expense of low specificity, and vice versa; however, a clinically useful predictive score should combine at least 70% sensitivity, and 70% specificity (Baek et al, 2014;Healey, Haines, 2013). Studies with a testing cut-off of 21 (Baek et al, 2014), 40 (Kim et al, 2007;Sung et al, 2014;Sung-Hee Yoo et al, 2015), 45 (Sung et al, 2014), 51 (Chapman et al, 2011;Kim et al, 2011;Baek et al, 2014), and 55 (Schwendimann et al, 2006) come closest to these values. Watson et al (2016) point to the predictive ability of the MFS to distinguish between high and low fall risk patients.…”

“…In the analysed studies (Table 1) the authors validated various cut-off score values, frequently using the values of 40 (Kim et al, 2007), 45 (Chow et al, 2007;Sung et al, 2014), 51 (Beak et al, 2013 and 55 (Watson et al, 2016). The cut-off is understood as an acceptable score value to differentiate the normal from the abnormal (Polit, Beck, 2010), and helps to predict the fall risk for each patient; i.e., it distinguishes between low fall risk patients, and high fall risk patients, for whom preventative strategies should be implemented.…”

“…They occur in all age categories, and clinical and diagnostic departments. For patients, they represent potentially serious health consequences, create additional clinical complications, prolong hospitalisation, and increase the costs of care (Nassar, Helou, Madi, 2014;Swartzell et al, 2013;Sung et al, 2014;Tang et al, 2014). Literary sources describe a variety of fall risk factorsinternal and external (Virani et al, 2011;Gray-Miceli, Quigley, 2012;Ganz et al, 2013); the identification of individual factors enables the selection of targeted interventions for care plans.…”