Konkuk University Publishes HFRS-Geriatric Syndrome Association in International Journal

Professor Shin Jin-young's research team from the Department of Family Medicine at Konkuk University Medical Center is drawing international attention by presenting groundbreaking advancements in the field of elderly healthcare. Through joi...

Feb 12, 2025 - 00:00
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Professor Shin Jin-young's research team from the Department of Family Medicine at Konkuk University Medical Center is drawing international attention by presenting groundbreaking advancements in the field of elderly healthcare. Through joint research with Mediplexer, they successfully demonstrated the clinical utility of the 'Hospital Frailty Risk Score (HFRS)' based on electronic medical records (EMR), a remarkable achievement with the results published in 'Geriatric Nursing,' a prestigious academic journal in geriatric nursing. This study re-examined the value of HFRS, which can quickly identify the risk of frailty in hospitalized patients by utilizing their diagnostic codes, without the need for complex in-person assessments. Analyzing a vast amount of EMR data from 8,205 hospitalized patients aged 65 and older from 2016 to 2021, the study revealed a strong correlation with major geriatric syndromes in patient groups with higher HFRS scores: a 2.1-fold increased risk of cognitive impairment, a 1.9-fold increased risk of depression, and a 1.3-fold increased likelihood of taking five or more medications. Professor Shin Jin-young stated, "This research clearly demonstrated how effectively EMR-based frailty risk assessment can be applied in real clinical settings," emphasizing, "HFRS will be an essential tool for early detection of vulnerability in elderly patients, enabling personalized treatment and preventative interventions optimized for each individual." These research achievements are expected to make significant contributions to establishing sophisticated treatment plans tailored to individual elderly patients and allocating hospital resources more efficiently in the future. Last year, Professor Shin's research team also collaborated with Mediplexer to successfully build a pseudonymized medical data-based database for elderly patients, continuously expanding the horizons of medical data research using EMR.

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