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We have developed a new database system for forensic autopsies, called the Legal Medicine Information System, using the Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model (ODM). This system comprises two subsystems, namely the Institutional Database System (IDS) located in each institute and containing personal information, and the Central Anonymous Database System (CADS) located in the University Hospital Medical Information Network Center containing only anonymous information. CDISC ODM is used as the data transfer protocol between the two subsystems. Using the IDS, forensic pathologists and other staff can register and search for institutional autopsy information, print death certificates, and extract data for statistical analysis. They can also submit anonymous autopsy information to the CADS semi-automatically. This reduces the burden of double data entry, the time-lag of central data collection, and anxiety regarding legal and ethical issues. Using the CADS, various studies on the causes of death can be conducted quickly and easily, and the results can be used to prevent similar accidents, diseases, and abuse.  相似文献   
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数据管理标准临床数据交换标准协会(CDISC)已广泛应用于临床研究中,它能够优化临床研究数据采集、传递、储存,并简化申办者/研究者向管理部门递交数据的程序,从而提高临床研究的效率。CDISC包含临床数据采集标准(CDASH)、实验室数据模型(LAB)、操作数据模型(ODM)、研究数据表格模型(SDTM)、分析数据库模型(ADaM)等模块。文中从数据管理标准在医学研究中应用的意义、已经广泛应用的CDISC主要模块CDASH,SDTM,AdaM的介绍以及临床研究中数据管理标准CDISC的应用前景等方面加以阐述。  相似文献   
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Background

Semantic interoperability between routine healthcare and clinical research is an unsolved issue, as information systems in the healthcare domain still use proprietary and site-specific data models. However, information exchange and data harmonization are essential for physicians and scientists if they want to collect and analyze data from different hospitals in order to build up registries and perform multicenter clinical trials. Consequently, there is a need for a standardized metadata exchange based on common data models. Currently this is mainly done by informatics experts instead of medical experts.

Objectives

We propose to enable physicians to exchange, rate, comment and discuss their own medical data models in a collaborative web-based repository of medical forms in a standardized format.

Methods

Based on a comprehensive requirement analysis, a web-based portal for medical data models was specified. In this context, a data model is the technical specification (attributes, data types, value lists) of a medical form without any layout information. The CDISC Operational Data Model (ODM) was chosen as the appropriate format for the standardized representation of data models. The system was implemented with Ruby on Rails and applies web 2.0 technologies to provide a community based solution. Forms from different source systems – both routine care and clinical research – were converted into ODM format and uploaded into the portal.

Results

A portal for medical data models based on ODM-files was implemented (http://www.medical-data-models.org). Physicians are able to upload, comment, rate and download medical data models. More than 250 forms with approximately 8000 items are provided in different views (overview and detailed presentation) and in multiple languages. For instance, the portal contains forms from clinical and research information systems.

Conclusion

The portal provides a system-independent repository for multilingual data models in ODM format which can be used by physicians. It serves as a platform for discussion and enables the exchange of multilingual medical data models in a standardized way.  相似文献   
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BRIDG(Biomedical Research Integrated Domain Group)模型是一种介于医疗信息与临床研究信息之间的交换标准,它是连接HL7(Health Level Seven)和DCDISC(Clinical Data Interchange Standards Consortium)标准的桥梁。在通过医院信息系统(HIS)转出数据到临床数据管理(clinical data management,CDM)系统或电子数据采集(electronic data capture,EDC)系统时应用BRIDG模型,将为提高临床研究的效率、保证数据质量、促进数据共享等方面起到积极的作用。  相似文献   
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IntroductionIn order to further advance research and development on the Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model (ODM) standard, the existing research must be well understood. This paper presents a methodological review of the ODM literature. Specifically, it develops a classification schema to categorize the ODM literature according to how the standard has been applied within the clinical research data lifecycle. This paper suggests areas for future research and development that address ODM’s limitations and capitalize on its strengths to support new trends in clinical research informatics.MethodsA systematic scan of the following databases was performed: (1) ABI/Inform, (2) ACM Digital, (3) AIS eLibrary, (4) Europe Central PubMed, (5) Google Scholar, (5) IEEE Xplore, (7) PubMed, and (8) ScienceDirect. A Web of Science citation analysis was also performed. The search term used on all databases was “CDISC ODM.” The two primary inclusion criteria were: (1) the research must examine the use of ODM as an information system solution component, or (2) the research must critically evaluate ODM against a stated solution usage scenario. Out of 2686 articles identified, 266 were included in a title level review, resulting in 183 articles. An abstract review followed, resulting in 121 remaining articles; and after a full text scan 69 articles met the inclusion criteria.ResultsAs the demand for interoperability has increased, ODM has shown remarkable flexibility and has been extended to cover a broad range of data and metadata requirements that reach well beyond ODM’s original use cases. This flexibility has yielded research literature that covers a diverse array of topic areas. A classification schema reflecting the use of ODM within the clinical research data lifecycle was created to provide a categorized and consolidated view of the ODM literature. The elements of the framework include: (1) EDC (Electronic Data Capture) and EHR (Electronic Health Record) infrastructure; (2) planning; (3) data collection; (4) data tabulations and analysis; and (5) study archival. The analysis reviews the strengths and limitations of ODM as a solution component within each section of the classification schema. This paper also identifies opportunities for future ODM research and development, including improved mechanisms for semantic alignment with external terminologies, better representation of the CDISC standards used end-to-end across the clinical research data lifecycle, improved support for real-time data exchange, the use of EHRs for research, and the inclusion of a complete study design.ConclusionsODM is being used in ways not originally anticipated, and covers a diverse array of use cases across the clinical research data lifecycle. ODM has been used as much as a study metadata standard as it has for data exchange. A significant portion of the literature addresses integrating EHR and clinical research data. The simplicity and readability of ODM has likely contributed to its success and broad implementation as a data and metadata standard. Keeping the core ODM model focused on the most fundamental use cases, while using extensions to handle edge cases, has kept the standard easy for developers to learn and use.  相似文献   
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CDISC-CDASH为标准,完善临床试验既往病史、不良事件和合并用药的病例报告表设计,建立一套通用的数据的逻辑核查方案,用以清理三者普通逻辑错误和数据彼此矛盾的情况。从而标准化、模块化数据管理员该部分临床试验前期准备工作,降低试验成本,提高效率及数据质量。  相似文献   
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临床研究数据标准化越来越受到关注,国际临床研究数据标准主要包括文件格式标准、分析标准、交换标准和术语标准4大类.其中交换标准和分析标准目前备受关注的是CDISC标准.数据管理质量和水平的落后已经成为制约国内临床试验持续、快速和健康发展的桎梏,如何应用国际临床数据标准缩小中医药临床研究与国际先进水平的差距是个不断探索的课题.本文简要就CDISC和其具体的两个标准以及在中医药临床研究数据标准化中的意义进行了较深入的描述和分析,并针对目前中医药临床研究数据全面运用CDISC标准存在的问题进行讨论,提出加强相关中医语义结构及术语标准研究是解决全面应用CIDSC标准问题的关键和必由之路.  相似文献   
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