OBJECTIVE: An automatic detection tool was created for examining health-related webpage quality we went further by examining its feasibility and performance. METHODS: We developed an automatic detection system to auto-assess the authorship quality indicator of an health-related information webpage for governmental websites in Taiwan. The system was integrated with the Chinese word segmentation system developed by the Academia Sinica in Taiwan and the SVM(light), which serve as an SVM (Support Vector Machine) Classifiers and a method of information extraction and identification. The system was coded in Visual Basic 6.0, using SQL 2000. RESULTS: We developed the first Chinese automatic webpage classification and information identifier to evaluate the quality of web information. The sensitivity and specificity of the classifier on the training set of webpages were both as high as 100% and only one health webpage in the test set was misclassified, due to the fact that it contained both health and non-health information content. The sensitivity of our authorship identifier is 75.3%, with a specificity of 87.9%. CONCLUSION: The technical feasibility of auto-assessment for the quality of health information on the web is acceptable. Although it is not sufficient to assure the total quality of web contents, it is good enough to be used to support the entire quality assurance program.
Asian Continental Ancestry Group ; Authorship ; Humans ; Quality Indicators, Health Care ; Sensitivity and Specificity ; Taiwan

Objective To develop a intelligentized delirium assessment system based on the Confusion Assessment Model for Intensive Care Unit ( CAM-ICU ) and test its usability among nurses in the ICU . Methods Through convenient sampling , investigators selected 68 ICU nurses from 3 hospitals in Beijing to participate in this study .Participants tried the new intelligentized system before they filled in the evaluation form named as "Usability analysis of the intelligentized CAM-ICU delirium assessment system interface evaluation questionnaire"which was adapted from the framework of "Technology Acceptance Model".Results Among the 68 ICU nurses, 51.5% had received delirium assessment training prior to the study , 79.4% had cared for delirious patient and 70.6% had actually identified delirious symptoms among the patients they cared in the past.The average score for the items in the questionnaire ranged from 3.4 to 4.0.The scores among nurses who had received delirium assessment training before the study had significant difference compared to the ones who did not (P<0.05).They had perceived that the design of the system was satisfactory , and they were willing to use this system in delirium assessment , and expressed that it could improve their ability in assessing delirium therefore promoted the overall quality nursing care of patients (χ2 =6.28,P =0.012).Conclusions The design of the intelligentized CAM-ICU delirium assessment system is simple to use and easy to operate , especially among those who have had knowledge related to delirium assessment prior to the study .It reflects that this system is useful in identification of delirious patient and can improve the accuracy of delirium diagnosis in the ICU.

This article describes the development of nursing informatics in Children's National Medical Center, including the organization of nursing informatics, the qualifications and scope of work of nursing information specialists, continuing education and training and professional development of nursing informatics. Based on the status quo of nursing information specialists in China, this paper also points out that Chinese hospitals need to set up full-time positions of nursing information specialists, build nursing information teams, strengthen nursing information training and call on relevant authorities to issue working standards and training certifications for nursing information specialists in China.