A model for predicting fall experience in the elderly population over 65 years old: Decision tree analysis

Abstract

Purpose: This study aimed to construct a model to predict whether the elderly population over 65 years of age will experience falls according to multi-drug therapy and related factors. Methods: Decision tree analysis was used to analyze data from the 2020 national survey of the living condition and welfare needs of older Koreans. Results: The fall experience rate was 23.7%, which was the highest in the case of diet management due to disease while taking multi-drug therapy. In contrast, those who did not receive multi-drug therapy had good subjective health rates, and those who did not have arthritis showed the lowest fall experience rate (5.5%). Conclusion: The elderly population has a high prevalence of chronic diseases, and the number of people using multi-drug therapy is increasing accordingly. For this reason, healthcare providers should carefully prescribe medication for older adults. In addition, it is necessary to develop and apply a customized fall management program that reflects the demographic and health-related factors, which include diet, disease types, and health levels, with multi-drug therapy.