{"title":"实现数据驱动的护理创新:以用户为中心的护理数据模块开发","authors":"Maren Warnecke, Daniela Holle, Anja Burmann","doi":"10.1515/cdbme-2023-1085","DOIUrl":null,"url":null,"abstract":"Abstract The documentation landscape for nursing care data in Germany is predominantly heterogeneous and unstructured. Therefore, insightful methods such as Artificial Intelligence (AI) are difficult to implement. We propose a stepwiseapproach that identifies relevant information from nursing theory and practice and maps it to a standardized nursing core data set to enable data-based improvement of nursing care. This can be used for various use-cases in care, such as risk detection and prevention in diverse care contexts. Many care processes can benefit of a cross-facility and standardized repository and associated applications. We propose an approach that enables the use of AI while leveraging consensus and evidenced-based expert knowledge from nursing science.","PeriodicalId":10739,"journal":{"name":"Current Directions in Biomedical Engineering","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enabling Data-Driven Nursing Innovations: User-centered Development of a Nursing Data Module\",\"authors\":\"Maren Warnecke, Daniela Holle, Anja Burmann\",\"doi\":\"10.1515/cdbme-2023-1085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The documentation landscape for nursing care data in Germany is predominantly heterogeneous and unstructured. Therefore, insightful methods such as Artificial Intelligence (AI) are difficult to implement. We propose a stepwiseapproach that identifies relevant information from nursing theory and practice and maps it to a standardized nursing core data set to enable data-based improvement of nursing care. This can be used for various use-cases in care, such as risk detection and prevention in diverse care contexts. Many care processes can benefit of a cross-facility and standardized repository and associated applications. We propose an approach that enables the use of AI while leveraging consensus and evidenced-based expert knowledge from nursing science.\",\"PeriodicalId\":10739,\"journal\":{\"name\":\"Current Directions in Biomedical Engineering\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Directions in Biomedical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/cdbme-2023-1085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Directions in Biomedical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/cdbme-2023-1085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
Enabling Data-Driven Nursing Innovations: User-centered Development of a Nursing Data Module
Abstract The documentation landscape for nursing care data in Germany is predominantly heterogeneous and unstructured. Therefore, insightful methods such as Artificial Intelligence (AI) are difficult to implement. We propose a stepwiseapproach that identifies relevant information from nursing theory and practice and maps it to a standardized nursing core data set to enable data-based improvement of nursing care. This can be used for various use-cases in care, such as risk detection and prevention in diverse care contexts. Many care processes can benefit of a cross-facility and standardized repository and associated applications. We propose an approach that enables the use of AI while leveraging consensus and evidenced-based expert knowledge from nursing science.