{"title":"基于文本挖掘视角的成人住院患者跌倒原因定量分析。","authors":"Ying Zhang, Guichun Zhao, Zhi Zhao, Jing Luo, Ping Feng, Yahui Tong, Jianfang Zhang, Liping Tan, Wenjie Sui","doi":"10.1080/08941939.2024.2397578","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This study harnesses the power of text mining to quantitatively investigate the causative factors of falls in adult inpatients, offering valuable references and guidance for fall prevention measures within hospitals.</p><p><strong>Methods: </strong>Employing KH Coder 3.0, a cutting-edge text mining software, we performed co-occurrence network analysis and text clustering on fall incident reports of 2,772 adult patients from a nursing quality control platform in a particular city in Jiangsu Province, spanning January 2017 to December 2022.</p><p><strong>Results: </strong>Among the 2,772 patients who fell, 80.23% were aged above 60, and 73.27% exhibited physical frailty. Text clustering yielded 16 distinct categories, with four clusters implicating patient factors, four linking falls to toileting processes, four highlighting dynamic interplays between patients, the environment, and objects, and another four clusters revealing the influence of patient-caregiver interactions in causing falls.</p><p><strong>Conclusion: </strong>This study highlights the complex, multifactorial nature of falls in adult inpatients. Effective prevention requires a collaborative effort among healthcare staff, patients, and caregivers, focusing on patient vulnerabilities, environmental factors, and improved care coordination. By strengthening these aspects, hospitals can significantly reduce fall risks and promote patient safety.</p>","PeriodicalId":16200,"journal":{"name":"Journal of Investigative Surgery","volume":"37 1","pages":"2397578"},"PeriodicalIF":2.1000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantitative Analysis of the Causes of Falls in Adult Hospitalized Patients Based on the Perspective of Text Mining.\",\"authors\":\"Ying Zhang, Guichun Zhao, Zhi Zhao, Jing Luo, Ping Feng, Yahui Tong, Jianfang Zhang, Liping Tan, Wenjie Sui\",\"doi\":\"10.1080/08941939.2024.2397578\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>This study harnesses the power of text mining to quantitatively investigate the causative factors of falls in adult inpatients, offering valuable references and guidance for fall prevention measures within hospitals.</p><p><strong>Methods: </strong>Employing KH Coder 3.0, a cutting-edge text mining software, we performed co-occurrence network analysis and text clustering on fall incident reports of 2,772 adult patients from a nursing quality control platform in a particular city in Jiangsu Province, spanning January 2017 to December 2022.</p><p><strong>Results: </strong>Among the 2,772 patients who fell, 80.23% were aged above 60, and 73.27% exhibited physical frailty. Text clustering yielded 16 distinct categories, with four clusters implicating patient factors, four linking falls to toileting processes, four highlighting dynamic interplays between patients, the environment, and objects, and another four clusters revealing the influence of patient-caregiver interactions in causing falls.</p><p><strong>Conclusion: </strong>This study highlights the complex, multifactorial nature of falls in adult inpatients. Effective prevention requires a collaborative effort among healthcare staff, patients, and caregivers, focusing on patient vulnerabilities, environmental factors, and improved care coordination. By strengthening these aspects, hospitals can significantly reduce fall risks and promote patient safety.</p>\",\"PeriodicalId\":16200,\"journal\":{\"name\":\"Journal of Investigative Surgery\",\"volume\":\"37 1\",\"pages\":\"2397578\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Investigative Surgery\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/08941939.2024.2397578\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/9/8 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"SURGERY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Investigative Surgery","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/08941939.2024.2397578","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/8 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"SURGERY","Score":null,"Total":0}
Quantitative Analysis of the Causes of Falls in Adult Hospitalized Patients Based on the Perspective of Text Mining.
Objective: This study harnesses the power of text mining to quantitatively investigate the causative factors of falls in adult inpatients, offering valuable references and guidance for fall prevention measures within hospitals.
Methods: Employing KH Coder 3.0, a cutting-edge text mining software, we performed co-occurrence network analysis and text clustering on fall incident reports of 2,772 adult patients from a nursing quality control platform in a particular city in Jiangsu Province, spanning January 2017 to December 2022.
Results: Among the 2,772 patients who fell, 80.23% were aged above 60, and 73.27% exhibited physical frailty. Text clustering yielded 16 distinct categories, with four clusters implicating patient factors, four linking falls to toileting processes, four highlighting dynamic interplays between patients, the environment, and objects, and another four clusters revealing the influence of patient-caregiver interactions in causing falls.
Conclusion: This study highlights the complex, multifactorial nature of falls in adult inpatients. Effective prevention requires a collaborative effort among healthcare staff, patients, and caregivers, focusing on patient vulnerabilities, environmental factors, and improved care coordination. By strengthening these aspects, hospitals can significantly reduce fall risks and promote patient safety.
期刊介绍:
Journal of Investigative Surgery publishes peer-reviewed scientific articles for the advancement of surgery, to the ultimate benefit of patient care and rehabilitation. It is the only journal that encompasses the individual and collaborative efforts of scientists in human and veterinary medicine, dentistry, basic and applied sciences, engineering, and law and ethics. The journal is dedicated to the publication of outstanding articles of interest to the surgical research community.