Establishment of an algorithm for assessing fall risk with considering medical and statistical perspectives

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K10323
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 58010:Medical management and medical sociology-related
• Research Institution: Sojo University
• Principal Investigator: Tokunori Ikeda 崇城大学, 薬学部, 准教授 (00613530)
• Co-Investigator(Kenkyū-buntansha): 山ノ内 祥訓 熊本大学, 病院, 特任助教 (40772348) ; 近本 亮 熊本大学, 病院, 教授 (10419640)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: 転倒転落 / アセスメントアルゴリズム / 医療教育

Outline of Final Research Achievements

In this study, we established an algorithm for assessing fall risk with considering medical and statistical perspectives, especially considering combinations of patient information (pathology, symptoms, and medical history) but not using conventional scoring methods. By using a program, we collected patient information including fall assessment sheet information and general patient data such as age and gender from electronic medical records of patients admitted to Kumamoto University Hospital over the past two years. Based on these data, we constructed a fall assessment algorithm and published the results in a paper. We also developed a web application based on the proposed assessment algorithm.

Free Research Field

医療教育

Academic Significance and Societal Importance of the Research Achievements

我々が開発した転倒転落アセスメントアルゴリズムは、(1) 実臨床に沿った形式で、転倒転落リスクに関係した9つの重要因子を利用、(2) スコア方式ではないため、看護師以外の医療者も理解しやすく、評価も可能、(3) 転倒転落リスク度に応じて4グループに分類、(4) 転倒を引き起こすリスク要因が多因子的であることを踏まえ、臨床症状の組み合わせを考慮した分岐図を採用という４つの特徴を有している。そのため、構築したアセスメントアルゴリズムは多くの病院に適応可能であり、広く社会に受け入れられる可能性が高い。