目的 探讨荧光标记法用于静脉用药调配中心(PIVAS)物表清洁消毒监控的应用效果.方法 应用荧光标记法在PIVAS 3个区域25类重点物体表面进行布点标记,监测荧光清除情况并计算清除率.结果 PIVAS洁净区、非洁净控制区和辅助工作区物体表面干预后的清除率分别为95.05％,88.57％,92.92％,显著高于干预前的57.79％,63.46％,39.20％(P<0.01).结论 荧光标记法用于PI-VAS物表清洁消毒监控有一定成效,且方法简便.

Objective To explore the potential relationships between health risk factors and personal health,and the impact of potential factors on measured variables.MethodsA cross-sectional survey using health risk appraisal questionnaire was conducted to collect health-related information about healthy people in one of Xi'an 3A hospitals.The structural equation model of health risk factors and personal health was completed to justify the interaction among different factors and the effect on the overall health.ResultsThere was a positive correlation between health consciousness and health behaviors.The direct effect of health behavior on physical health was 0.85,and the total effects of health consciousness on physical health were 0.78 which included the direct and indirect effect through influencing personal mental health.ConclusionsHealth behaviors and health consciousness are health risk factors which can be controlled,and they often affect physical health and mental health to some extent.Making changes on these factors can improve individual's overall health.

Numerous and diverse paper-based health record documents are currently used in China, which are not only different from each other but are also inconsistent with national regulations. If these documents are made to be structured and electronically available, the health records information can be processed by computers to promote a shareable electronic health record (EHR) across organizations. As such, this work was intended to develop a set of content modules to be employed as reusable building blocks for converting the paper-based health records to structured EHR documents. Therefore, in this study, we developed 77 content modules based on the documents of national specifications and implemented them to Wuwei City as a trial. According to the EHR requirements of Wuwei, we added two new content modules in addition to the 77 existing content modules. We then successfully established an EHR system based on the new content modules in combination with the original content modules. This paper could contribute to the construction of structured Chinese EHR documents and provide some experiences as a reference for building EHR systems.

为了有效提高人民的健康水平、遏制医疗经费的过快增长,世界卫生组织(WHO)和发达国家近年来提倡由传统的疾病管理转向全民健康管理,即通过健康管理(health management,health administration)的手段达到健康促进(health promotion)的目的[1-2].健康状况的科学度量、数量化分析与评估是健康评价从疾病管理转变为健康管理的先决条件.自评健康(self-rated health)和健康风险评估(health risk appraisal,HRA)是健康管理的基础工具和关键技术.目前,自评健康和健康风险评估已逐步发展成为流行病学、卫生统计学、行为医学、心理学等多种学科的交叉学科,是健康管理研究的热点问题[3-4].

It was reported in "PLoS One" on February 16,2010 that of the 2027 non-primate trace archives,454 (22.39%) were identified as contaminated with human sequence captured Alu elements in the human genome,by screening non-primate public databases from NCBI,Ensembl,JGl,and UCSC.This proposed an issue of trust in network data. Strictly speaking,all the statistical data from the network should be peer reviewed,and have the appropriate metadata to provide the information that is needed by people or systems to make proper and correct use of the real statistical data,in terms of capturing,reading,processing,interpreting,analyzing and presenting the information.This article discusses the importance of statistical metadata and the standard system in medical information.

Objective To build data models of community health records,and provide a set of reference indicators and its descriptive meta model so as to provide basis for developing information system and facilitating information exchange. Methods The indicators of community health records were determined according to international and national standards,and the latest research results of community health records.The Unified Modeling Language(UML) was used in data modeling. Results The conceptual data model of community health records contains four dimensions and 20 sub-dimensions.Among the 84 reference indicators in the data model,10 belong to the health conditions,25 to the non-medical factors,22 to the health system performance,and 27 to the community and health system.Meta model of indicators includes three basic data types which are qualitative,quantitative and descriptive,respectively. Conclusion The conceptual data model could serve as the basis for content design of community health record in various areas.The logical data model and indicators together could be consulted in development of community health records systems.The meta model of indicators might be as meta data standard in information exchange among different systems.

Background Long waiting times for registration to see a doctor is problematic in China, especially in tertiary hospitals. To address this issue, a web-based appointment system was developed for the Xijing hospital. The aim of this study was to investigate the efficacy of the web-based appointment system in the registration service for outpatients. Methods Data from the web-based appointment system in Xijing hospital from January to December 2010 were collected using a stratified random sampling method, from which participants were randomly selected for a telephone interview asking for detailed information on using the system. Patients who registered through registration windows were randomly selected as a comparison group, and completed a questionnaire on-site. Results A total of 5641 patients using the online booking service were available for data analysis. Of them, 500 were randomly selected, and 369 (73.8%) completed a telephone interview. Of the 500 patients using the usual queuing method who were randomly selected for inclusion in the study, responses were obtained from 463, a response rate of 92.6%. Between the two registration methods, there were significant differences in age, degree of satisfaction, and total waiting time ( P < 0.001). However, gender, urban residence, and valid waiting time showed no significant differences ( P > 0.05). Being ignorant of online registration, not trusting the internet, and a lack of ability to use a computer were three main reasons given for not using the web-based appointment system. The overall proportion of non-attendance was 14.4% for those using the web-based appointment system, and the non-attendance rate was significantly different among different hospital departments, day of the week, and time of the day ( P < 0.001). Conclusion Compared to the usual queuing method, the web-based appointment system could significantly increase patient's satisfaction with registration and reduce total waiting time effectively. However, further improvements are needed for broad use of the system.