ObjectiveTo evaluate the application of Delone & Mclean (D&M) model in foreign health information technology (HIT), summarize each variable with its emphasis on HIT, in order to provide a reference and theoretical guidance for the evaluation HIT in clinical practice in China. MethodsOvid-medline, Embase, PubMed, Engineering Village, Web of Science, EBSCO, Wanfang Data, Chinese National Knowledge Infrastructure and VIP databases were searched from January 1993 to April 2015. Included articles focused on studies about D&M model applied in HIT. Two reviewers independently screened titles and abstracts to determine inclusion status. The process was completed by Endnote X6. ResultsFinally, there were 14 eligible full-text papers. In the evaluation, Europe and US accounted for 64.29% in the leading place, Australasia ranked second with 28.57%, and Asia was at last with 7.1%. So it is significant to draw lessons from foreign research. For the methods of data collection, survey was widely used (91.7%). The system quality, information quality and service quality had a significant positive correlation with users' satisfaction and net benefit. ConclusionD&M Model is a good tool to assess HIT.
Objective To investigate the current status and development of electronic health records (EHR) at home and abroad to grasp the development trends of EHR, so as to point out the direction of the development and relevant research on EHR. Methods Based on the Web of Science citation database and the principle of bibliometrics, we analyzed the retrieved literature in aspects of publication date, language, country/region, institution, author, etc. Results A total of 1 262 eligible studies were identified. The number of articles on EHR increased rapidly from only 2 in 1995 to 218 in 2012. In terms of country/region, the United States ranked the top in all countries (763 articles, accounting for 60.46%). In terms of institution, Harvard University ranked the top (135 articles, accounting for 10.70%). In terms of journal, the Journal of the American Medical Informatics Association ranked the top (106 articles, accounting for 8.40%). In terms of authors, David W. Bates ranked the top (45 articles, accounting for 3.57%). In terms of subject type, health care sciences services and medical informatics were mainly focused on. Conclusion The research on EHR has become a global hot spot and relevant bibliometrics will contribute to the timely and correctly grasp the whole picture of its development trends and main research direction.
In order to provide a reference and theoretical guidance of the evaluation of electronic medical record (EMR) and establishment of evaluation system in China, we applied a bibliometric analysis to assess the application of methodologies used at home and abroad, as well as to summarize the advantages and disadvantages of them. We systematically searched international medical databases of Ovid-MEDLINE, EBSCOhost, EI, EMBASE, PubMed, IEEE, and China's medical databases of CBM and CNKI between Jan.1997 and Dec.2012. We also reviewed the reference lists of articles for relevant articles. We selected some qualified papers according to the pre-established inclusion and exclusion criteria, and did information extraction and analysis to the papers. Eventually, 1 736 papers were obtained from online database and other 16 articles from manual retrieval. Thirty-five articles met the inclusion and exclusion criteria and were retrieved and assessed. In the evaluation of EMR, US counted for 54.28% in the leading place, and Canada and Japan stood side by side and ranked second with 8.58%, respectively. For the application of evaluation methodology, Information System Success Model, Technology Acceptance Model (TAM), Innovation Diffusion Model and Cost-Benefit Access Model were widely applied with 25%, 20%, 12.5% and 10%, respectively. In this paper, we summarize our study on the application of methodologies of EMR evaluation, which can provide a reference to EMR evaluation in China.
Heart failure is a disease that seriously threatens human health and has become a global public health problem. Diagnostic and prognostic analysis of heart failure based on medical imaging and clinical data can reveal the progression of heart failure and reduce the risk of death of patients, which has important research value. The traditional analysis methods based on statistics and machine learning have some problems, such as insufficient model capability, poor accuracy due to prior dependence, and poor model adaptability. In recent years, with the development of artificial intelligence technology, deep learning has been gradually applied to clinical data analysis in the field of heart failure, showing a new perspective. This paper reviews the main progress, application methods and major achievements of deep learning in heart failure diagnosis, heart failure mortality and heart failure readmission, summarizes the existing problems and presents the prospects of related research to promote the clinical application of deep learning in heart failure clinical research.
This article carries out a comprehensive review on otorhinolaryngologic-head and neck informatics, focusing on the definition, content and characteristics of otorhinolaryngologic informatics as well as the application of computer, communication and information technology in otorhinolaryngology-head and neck surgery. Otorhinolaryngologic informatics is the future development direction of otorhinolaryngology-head and neck surgery.