{"title":"Data Trauma: A Concept Analysis.","authors":"Erica Smith, Darryl Somayaji","doi":"10.1097/CIN.0000000000001218","DOIUrl":null,"url":null,"abstract":"<p><p>Today's healthcare landscape is becoming increasingly data-centric, with artificial intelligence and advanced computer algorithms becoming inextricably embedded in patient care. Although these technologies promise to make care more efficient and effective, they heighten the risk for unintended consequences. Using Walker and Avant's framework for concept analysis, we propose and explicate the emerging concept of iatrogenic data trauma, or ways in which the collection, storage, and use of sensitive and potentially stigmatizing patient data can cause harm. We conducted a careful and exhaustive review of traditional academic publications, as well as nontraditional digital sources to generate a rich and intersectional corpus of information pertaining to data justice, digital rights, and potential risks associated with the \"datafication\" of individuals. Using evidence synthesis and practical examples, we discuss how flawed data processes in healthcare settings can lead to data trauma among patients and explore how its presence can perpetuate health disparities, marginalization, loss of privacy, and breach of trust in patient-provider relationships. We discuss how this phenomenon arises and manifests across the healthcare continuum and is an important issue for professionals in multiple disciplines. We conclude by suggesting future opportunities for research through a trauma-informed lens.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cin-Computers Informatics Nursing","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/CIN.0000000000001218","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Today's healthcare landscape is becoming increasingly data-centric, with artificial intelligence and advanced computer algorithms becoming inextricably embedded in patient care. Although these technologies promise to make care more efficient and effective, they heighten the risk for unintended consequences. Using Walker and Avant's framework for concept analysis, we propose and explicate the emerging concept of iatrogenic data trauma, or ways in which the collection, storage, and use of sensitive and potentially stigmatizing patient data can cause harm. We conducted a careful and exhaustive review of traditional academic publications, as well as nontraditional digital sources to generate a rich and intersectional corpus of information pertaining to data justice, digital rights, and potential risks associated with the "datafication" of individuals. Using evidence synthesis and practical examples, we discuss how flawed data processes in healthcare settings can lead to data trauma among patients and explore how its presence can perpetuate health disparities, marginalization, loss of privacy, and breach of trust in patient-provider relationships. We discuss how this phenomenon arises and manifests across the healthcare continuum and is an important issue for professionals in multiple disciplines. We conclude by suggesting future opportunities for research through a trauma-informed lens.
期刊介绍:
For over 30 years, CIN: Computers, Informatics, Nursing has been at the interface of the science of information and the art of nursing, publishing articles on the latest developments in nursing informatics, research, education and administrative of health information technology. CIN connects you with colleagues as they share knowledge on implementation of electronic health records systems, design decision-support systems, incorporate evidence-based healthcare in practice, explore point-of-care computing in practice and education, and conceptually integrate nursing languages and standard data sets. Continuing education contact hours are available in every issue.