Development and Validation of Archetypes for Nursing Problems in Breast Cancer Patients

Y. Min, Hyeoun-Ae Park
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引用次数: 5

Abstract

Objective: Archetypes as structured models of clinical content are considered to be the key broker between the reference models and terminology. This study developed and validated archetypes for nursing problems with breast cancer patients. Methods: Archetypes were developed with the focuses and characterizing categories to describe the nursing problems identified from the perioperative nursing records of breast cancer patients, a literature review and experts’ survey. The archetypes were validated by experts and applied to the clinical cases. Results: Forty seven focuses and 22 characterizing categories of nursing problems were identified. Forty five archetypes, except for the symptoms of URI and vital signs, could be grouped into 16 different types. The symptoms of URI and vital signs were modeled by a combination of other archetypes. The experts’ evaluation and application to clinical cases demonstrated the validity of the archetypes developed. Conclusion: Archetypes for nursing problems developed in this study can ensure interoperability and contribute to the exchange and sharing of the high quality structured data and information. (Journal of Korean Society of Medical Informatics 15-4, 393-401, 2009)
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乳腺癌患者护理问题原型的发展与验证
目的:原型作为临床内容的结构化模型被认为是参考模型和术语之间的关键中介。本研究开发并验证了乳腺癌患者护理问题的原型。方法:根据乳腺癌患者围手术期护理记录、文献综述和专家调查发现的护理问题,采用重点和特征类别构建原型。这些原型经专家验证并应用于临床病例。结果:确定了47个护理问题重点和22个护理问题特征类别。45种原型,除了URI症状和生命体征外,可分为16种不同的类型。URI症状和生命体征由其他原型组合建模。专家的评价和临床案例的应用证明了所开发的原型的有效性。结论:本研究开发的护理问题原型可以保证互操作性,有助于高质量结构化数据和信息的交换和共享。(韩国医学信息学会杂志15- 4,393 -401,2009)
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Assessing the Quality of Structured Data Entry for the Secondary Use of Electronic Medical Records A Korean Version of the WHO International Classification for Patient Safety: A Validity Study Development and Validation of Archetypes for Nursing Problems in Breast Cancer Patients Comparison of Physicians' and Patients' Perception on the Effect of Internet Health Information Practical Guide to Clinical Data Management by Susanne Prokscha, 2007
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