Fatimah Altuhaifa , Dalal Al Tuhaifa , Eman Al Ribh , Ezdehar Al Rebh
{"title":"识别和定义与坠落风险评估工具中发现的坠落风险因素事件相关的实体","authors":"Fatimah Altuhaifa , Dalal Al Tuhaifa , Eman Al Ribh , Ezdehar Al Rebh","doi":"10.1016/j.cmpbup.2023.100105","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><p>The contents of nursing notes play an important role in predicting patient fall risk. Based on data collected from fall risk assessment tools, we aimed to identify and define fall risk factors to support natural language processing, data mining of nursing notes, and automated fall prediction.</p></div><div><h3>Methods</h3><p>The PRISMA-ScR guidelines were used to summarize entities associated with the fall risk factors described in fall risk assessment tools. Fall risk factors (concepts) and their related words (entities) were extracted from the tools. In order to clarify the meaning of unclear fall risk factors and classify fall risk factor entities, we searched the websites of the World Health Organization and the governments of Victoria, Australia, and New South Wales (up to 20 December 2021). A nurse and a safety expert reviewed and assessed the extracted concepts and entities for clarity and relevance. Then, the NLPfallRisk tool was developed to extract entities associated with fall risk factors.</p></div><div><h3>Results</h3><p>We identified 20 validated fall risk assessment tools appropriate for hospitals and healthcare facilities. Using these tools, we extracted 19 especially significant risk factors as the most significant and identified 151 entities related to them.</p></div><div><h3>Conclusion</h3><p>We found that fall assessment tools considered a history of falls more frequently than any other risk factor. However, as fall risk tends to be multifaceted, risk assessments must take many factors into account.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"3 ","pages":"Article 100105"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying and defining entities associated with fall risk factors events found in fall risk assessment tools\",\"authors\":\"Fatimah Altuhaifa , Dalal Al Tuhaifa , Eman Al Ribh , Ezdehar Al Rebh\",\"doi\":\"10.1016/j.cmpbup.2023.100105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><p>The contents of nursing notes play an important role in predicting patient fall risk. Based on data collected from fall risk assessment tools, we aimed to identify and define fall risk factors to support natural language processing, data mining of nursing notes, and automated fall prediction.</p></div><div><h3>Methods</h3><p>The PRISMA-ScR guidelines were used to summarize entities associated with the fall risk factors described in fall risk assessment tools. Fall risk factors (concepts) and their related words (entities) were extracted from the tools. In order to clarify the meaning of unclear fall risk factors and classify fall risk factor entities, we searched the websites of the World Health Organization and the governments of Victoria, Australia, and New South Wales (up to 20 December 2021). A nurse and a safety expert reviewed and assessed the extracted concepts and entities for clarity and relevance. Then, the NLPfallRisk tool was developed to extract entities associated with fall risk factors.</p></div><div><h3>Results</h3><p>We identified 20 validated fall risk assessment tools appropriate for hospitals and healthcare facilities. Using these tools, we extracted 19 especially significant risk factors as the most significant and identified 151 entities related to them.</p></div><div><h3>Conclusion</h3><p>We found that fall assessment tools considered a history of falls more frequently than any other risk factor. However, as fall risk tends to be multifaceted, risk assessments must take many factors into account.</p></div>\",\"PeriodicalId\":72670,\"journal\":{\"name\":\"Computer methods and programs in biomedicine update\",\"volume\":\"3 \",\"pages\":\"Article 100105\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer methods and programs in biomedicine update\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666990023000149\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer methods and programs in biomedicine update","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666990023000149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identifying and defining entities associated with fall risk factors events found in fall risk assessment tools
Purpose
The contents of nursing notes play an important role in predicting patient fall risk. Based on data collected from fall risk assessment tools, we aimed to identify and define fall risk factors to support natural language processing, data mining of nursing notes, and automated fall prediction.
Methods
The PRISMA-ScR guidelines were used to summarize entities associated with the fall risk factors described in fall risk assessment tools. Fall risk factors (concepts) and their related words (entities) were extracted from the tools. In order to clarify the meaning of unclear fall risk factors and classify fall risk factor entities, we searched the websites of the World Health Organization and the governments of Victoria, Australia, and New South Wales (up to 20 December 2021). A nurse and a safety expert reviewed and assessed the extracted concepts and entities for clarity and relevance. Then, the NLPfallRisk tool was developed to extract entities associated with fall risk factors.
Results
We identified 20 validated fall risk assessment tools appropriate for hospitals and healthcare facilities. Using these tools, we extracted 19 especially significant risk factors as the most significant and identified 151 entities related to them.
Conclusion
We found that fall assessment tools considered a history of falls more frequently than any other risk factor. However, as fall risk tends to be multifaceted, risk assessments must take many factors into account.