Sociological refigurations of patient safety; ontologies of improvement and ‘acting with’ quality collaboratives in healthcare

The increasing focus on patient safety in the field of health policy is accompanied by research programs that articulate the role of the social sciences as one of contributing to enhancing safety in healthcare. Through these programs, new approaches to studying safety are facing a narrow definition of ‘usefulness’ in which researchers are to discover the factors that support or hamper the implementation of existing policy agendas. This is unfortunate since such claims for useful involvement in predefined policy agendas may undo one of the strongest assets of good social science research: the capacity to complexify the taken-for-granted conceptualizations of the object of study. As an alternative to this definition of ‘usefulness’, this article proposes a focus on multiple ontologies in the making when studying patient safety. Through such a focus, the role of social scientists becomes the involvement in refiguring the problem space of patient safety, the relations between research subjects and objects, and the existing policy agendas. This role gives medical sociologists the opportunity to focus on the question of which practices of ‘effective care’ are being enacted through different approaches for dealing with patient safety and what their consequences are for the care practices under study.     

A Knowledge-Based Clustering Algorithm Driven by Gene Ontology

Abstract

We have developed an algorithm for inferring the degree of similarity between genes by using the graph-based structure of Gene Ontology (GO). We applied this knowledge-based similarity metric to a clique-finding algorithm for detecting sets of related genes with biological classifications. We also combined it with an expression-based distance metric to produce a co-cluster analysis, which accentuates genes with both similar expression profiles and similar biological characteristics and identifies gene clusters that are more stable and biologically meaningful. These algorithms are demonstrated in the analysis of MPRO cell differentiation time series experiments.     

针灸学领域本体构建研究

本研究以针灸学为特定领域,在理解本体论理论和方法的基础上,探讨基于本体论的针灸学领域本体构建方法,并以protégé3.0为本体编辑工具,初步建立针灸学领域本体框架模型,为构建中医药学领域本体奠定理论基础,积累实践经验。     

医学论文统计设计语义模型与元数据创建

目的将统计设计的基本理论、基本知识整合成为计算机可识别的语义模型、语义槽及元数据,为语义网计算机推理提供知识本体。方法知识本体的建立以公认的医学统计理论为依据,采用知识本体编辑工具Prot啨g啨构建语义模型的层级结构,定义概念与概念之间的关系以及语义槽的专业词汇和其他元数据的规范描述。结果构建了包含试验设计基本要素、实验设计基本原则的语义模型,创建了19个语义槽和元数据,3个医学期刊论文研究设计的实例。结论构建计算机可识别和处理的统计知识本体,是计算机自动对网络信息进行逻辑推理操作的基础。根据统计设计语义模型中统计知识的电子化表示,医学研究者可自己创建实例或定义关于医学论文统计设计的描述文档,不需要使用复杂繁琐的本体语言。     

中国“儒、道、佛”生死伦理观比较

“儒、道、佛”生死观蕴涵了丰富的伦理思想，并积淀成中华民族生死伦理的主要元素，但三者有着许多不同之处，生死本体论不同：儒家以“仁”、道家Ⅸ“道”、佛家以“佛”为生死本体；生死价值论的不同：儒家重生的价值、道家生死价值等同、佛家重死的价值；生死态度的不同：儒家好生恶死、道家善生乐死、佛家恶生主死；生死超越论的不同：儒家由生观死、道家由死观生、佛家弃生观死。     

一种改进的基因功能网络术语相似度计算方法

阐述现有基因术语间语义相似度计算方法，提出基于融合高斯核函数的重启随机游走的基因本体术语相似度算法（Random Walk with Restart-based Similarity Measure，RWRSM），测试算法性能并进行分析，结果表明该算法优于其他算法，可以提高准确性及稳定性。     

The Importance of Body Part Labeling to Enable Enterprise Imaging: A HIMSS-SIIM Enterprise Imaging Community Collaborative White Paper

In order for enterprise imaging to be successful across a multitude of specialties, systems, and sites, standards are essential to categorize and classify imaging data. The HIMSS-SIIM Enterprise Imaging Community believes that the Digital Imaging Communications in Medicine (DICOM) Anatomic Region Sequence, or its equivalent in other data standards, is a vital data element for this role, when populated with standard coded values. We believe that labeling images with standard Anatomic Region Sequence codes will enhance the user’s ability to consume data, facilitate interoperability, and allow greater control of privacy. Image consumption—when a user views a patient’s images, he or she often wants to see relevant comparison images of the same lesion or anatomic region for the same patient automatically presented. Relevant comparison images may have been acquired from a variety of modalities and specialties. The Anatomic Region Sequence data element provides a basis to allow for efficient comparison in both instances. Interoperability—as patients move between health care systems, it is important to minimize friction for data transfer. Health care providers and facilities need to be able to consume and review the increasingly large and complex volume of data efficiently. The use of Anatomic Region Sequence, or its equivalent, populated with standard values enables seamless interoperability of imaging data regardless of whether images are used within a site or across different sites and systems. Privacy—as more visible light photographs are integrated into electronic systems, it becomes apparent that some images may need to be sequestered. Although additional work is needed to protect sensitive images, standard coded values in Anatomic Region Sequence support the identification of potentially sensitive images, enable facilities to create access control policies, and can be used as an interim surrogate for more sophisticated rule-based or attribute-based access control mechanisms. To satisfy such use cases, the HIMSS-SIIM Enterprise Imaging Community encourages the use of a pre-existing body part ontology. Through this white paper, we will identify potential challenges in employing this standard and provide potential solutions for these challenges.