Predictive Factors and the Predictive Scoring System for Falls in Acute Care Inpatients: Retrospective Cohort Study - Chihiro Saito; Eiji Nakatani; Hatoko Sasaki; Naoko E Katsuki; Masaki Tago; Kiyoshi Harada (JMIR Human Factors)
Abstract BackgroundFalls in hospitalized patients are a serious problem, resulting in physical injury, secondary complications, impaired activities of daily living, prolonged hospital stays, and increased medical costs. Establishing a fall prediction scoring system to identify patients most likely to fall can help prevent falls among hospitalized patients. ObjectivesThis study aimed to identify predictive factors of falls in acute care hospital patients, develop a scoring system, and evaluate its validity. MethodsThis single-center, retrospective cohort study involved patients aged 20 years or older admitted to Shizuoka General Hospital between April 2019 and September 2020. Demographic data, candidate predictors at admission, and fall occurrence reports were collected from medical records. The outcome was the time from admission to a fall requiring medical resources. Two-thirds of cases were randomly selected as the training set for analysis, and univariable and multivariable Cox regression analyses were used to identify factors affecting fall risk. We scored the fall risk based on the estimated hazard ratios (HRs) and constructed a fall prediction scoring system. The remaining one-third of cases was used as the test set to evaluate the predictive performance of the new scoring system. ResultsA total of 13,725 individuals were included. During the study period, 2.4% (326/13,725) of patients experienced a fall. In the training dataset (n=9150), Cox regression analysis identified sex (male: HR 1.60, 95% CI 1.21‐2.13), age (65 to <80 years: HR 2.26, 95% CI 1.48‐3.44; ≥80 years: HR 2.50, 95% CI 1.60‐3.92 vs 20-<65 years), BMI (18.5 to <25 kg/m²: HR 1.36, 95% CI 0.94‐1.97; <18.5 kg/m²: HR 1.57, 95% CI 1.01‐2.44 vs ≥25 kg/m²), independence degree of daily living for older adults with disabilities (bedriddenness rank A: HR 1.81, 95% CI 1.26‐2.60; rank B: HR 2.03, 95% CI 1.31‐3.14; rank C: HR 1.23, 95% CI 0.83‐1.83 vs rank J), department (internal medicine: HR 1.23, 95% CI 0.92‐1.64; emergency department: HR 1.81, 95% CI 1.26‐2.60 vs department of surgery), and history of falls within 1 year (yes: HR 1.66, 95% CI 1.21‐2.27) as predictors of falls. Using these factors, we developed a fall prediction scoring system categorizing patients into 3 risk groups: low risk (0-4 points), intermediate risk (5-9 points), and high risk (10-15 points). The c-index indicating predictive performance in the test set (n=4575) was 0.733 (95% CI 0.684‐0.782). ConclusionsWe developed a new fall prediction scoring system for patients admitted to acute care hospitals by identifying predictors of falls in Japan. This system may be useful for preventive interventions in patient populations with a high likelihood of falling in acute care settings.