Leading hospitals in Japan, Fujifilm, and Juntendo have developed an AI model that leverages hospital data to predict patients’ risk of falls. This system helps healthcare professionals determine suitable preventive measures based on percentages and risk factors.
According to a news report by Mobihelth News, the team of researchers behind the risk-of-fall predicting AI leveraged the data from Fujifilm’s CITA Clinical Finder, a central data management platform for various hospital departments, to analyze and collate over 500 fall-associated features, including patients’ prescription histories and ages.
The researchers then used the data to train an AI model to help predict patients’ risk of falling in percentages and display the risk factors that could result in a falling incident. In an effectiveness test conducted at Juntendo Hospital using data from 70,000 outpatients, the AI system predicted and generated fall risk with 96% accuracy.
While Fujifilm and Juntendo stated their commitment to testing the AI and seeking early clinical application of the AI model in health facilities, the system holds hope for safer outpatient care in the future, with patients’ risk of falls easily detected in advance and preventive measures implemented.
Why the AI Model Matters
Japan has been experiencing a high rate of falls, with about 2 in every 10 elderly falling every year, according to the National Library of Medicine report.
Outpatient falls are a common phenomenon as hospitals do not have effective means of identifying patients susceptible to falls due to the limited time they spend in the health facilities, sparking the need for a more effective way to asses patient’s fall risk.
Although there have been studies in Japan on using AI to help prevent patient falls in hospitals and nursing homes, advancements in AI technology and machine learning have made possibilities of ever achieving that fete endless.
Earlier, Fujitsu and Wakayama Medical University worked on a trial focusing on using a combined sensor and AI technology to detect falls. The latest innovation adds to the company’s elderly care technology portfolio as it works to get the new AI model to the application phase.
