SHM Converge Scientific Abstract ePoster Gallery-External Validation of a Fall Predictive Model for Inpatients in Japanese Long-Term Care Hospitals: A Multi-Centered Observational Study Using the Saga Fall Risk Model 2

External Validation of a Fall Predictive Model for Inpatients in Japanese Long-Term Care Hospitals: A Multi-Centered Observational Study Using the Saga Fall Risk Model 2

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The document summarizes an external validation study of the Saga Fall Risk Model 2 (SFRM-2), a simple fall prediction tool originally developed for acute care hospitals. SFRM-2 uses eight admission-based factors, including age, sex, emergency admission, admitting department, hypnotic use, history of falls, eating ability, and bedriddenness rank. Each factor contributes to a total score, with higher scores indicating greater fall risk.<br /><br />The study aimed to test whether SFRM-2 works well in long-term care hospital settings. It was a multicenter retrospective observational study conducted in three long-term care hospitals, including all inpatients aged 20 years and older from April 1, 2018 to March 31, 2021. The outcome measured was in-hospital falls.<br /><br />Results showed that the patient population was elderly, with a median age of 86 years; 45.5% were male, and the median hospital stay was 27 days. SFRM-2 demonstrated strong predictive performance in this setting, with an area under the curve (AUC) of 0.889 (95% CI: 0.861–0.916) and a shrinkage coefficient of 0.975, indicating good model stability and discrimination.<br /><br />The authors concluded that SFRM-2 has high discriminatory power when used in long-term care hospitals. They suggest it may be especially useful in this environment because patients tend to be in more stable condition than those in acute care hospitals, making the model more applicable and potentially practical for fall prevention.

Asset Subtitle

Risa Hirata

Meta Tag

Author List Chihiro Saito, Eiji Nakatani, Hidetoshi Aihara, Hitomi Shimada, Kaori Amari, Kazuya Kurogi, Kiyoshi Shikino, Maiko Ono, Mariko Yoshimura, Masaki Tago, Midori Tokushima, Motoshi Fujiwara, Naoko E. Katsuki, Risa Hirata, Shizuka Yaita, Shun Yamashita, T

Category Research

Concept Saga Fall Risk Model 2

Concept Fall Risk Prediction

Concept Scoring Coefficient

Concept External Validation

Concept AUC

Distinguished Non-Finalist

Presenter Organization Saga University Hospital

Presenting Author Risa Hirata

Track Patient Safety

Keywords

Saga Fall Risk Model 2

SFRM-2

fall prediction

long-term care hospitals

external validation

in-hospital falls

risk assessment

predictive performance

AUC 0.889

fall prevention

Saga Fall Risk Model 2

Fall Risk Prediction

Scoring Coefficient

External Validation

AUC