OBJECTIVES To retrospectively validate the new Chinese DIC scoring system (CDSS). METHODS This study retrospectively collected the information of 619 patients (371 cases with non-hematologic malignancies, 248 cases with hematologic malignancies) who suspected of DIC in Wuhan Union Hospital during 2013-4 to 2014-6. We validated CDSS by comparing it with three leading scoring systems, from Inte...

Clinical Decision Support System (CDSS) has become the ultimate point of care for healthcare sectors to assist public in terms Medical care. Through this research work, we propose design and development a Web-based (We-CDSS) using Django framework with an aim make CDSS accessible both common people clinicians on computers mobile devices that integrates Predictive Analytics involving LWGMK-NN al...

We conducted a descriptive, retrospective, cross-sectional study to assess the core activities and supportive functions of the communicable diseases surveillance system (CDSS) in Khartoum state, Sudan, for the period 2005-2007. This is the first assessment conducted for CDSS in Khartoum state. The CDSS was studied in terms of core activities and supportive functions. We found that knowledge of ...

One of the proposals for improving clinical practice is to introduce computerised decision support systems (CDSS) and integrate these with electronic medical records. Accordingly, this study sought to systematically review evidence on the effectiveness of CDSS in the management of depression. A search was performed in Medline, EMBASE and PsycInfo, in order to do this. The quality of quantitativ...

Clinical Decision Support Systems (CDSS) are typically constructed from expert knowledge and are often reliant on inputs that are difficult to obtain and on tacit knowledge that only experienced clinicians possess. Research described in this article uses empirical results from a clinical trial of a CDSS with a decision model based on expert knowledge to show that there are differences in how cl...

BACKGROUND A cloud-based clinical decision support system (CDSS) was implemented to remotely provide evidence-based guideline reminders in support of preventative health. Following implementation, we measured the agreement between preventive care reminders generated by an existing, local CDSS and the new, cloud-based CDSS operating on the same patient visit data. METHODS Electronic health rec...

Clinical Decision Support Systems (CDSS) have been shown to improve clinical performance and patient outcomes, but the failure rate of such systems is still over 50 percent. To contribute to a wider understanding of issues surrounding CDDS acceptance, we performed a systematic review of studies that evaluated CDSS implementations in clinical care to determine the factors that are associated wit...

Clinical decision support systems are important healthcare systems that help in improving healthcare quality and in reducing cost. These systems have multiple levels of outcomes on the individual, group, organization, and society levels. However, despite the abundant studies conducted to evaluate CDSS, most of these studies failed to recognize these multiple levels of impact and mostly focused ...

OBJECTIVE To assess whether a user-centred prototype clinical decision support system (CDSS) providing patient-specific advice better supports healthcare practitioners in terms of (a) types of usability problems detected and (b) effective and efficient retrieval of childhood cancer survivor's follow-up screening procedures compared to an expert-driven paper-based guideline. METHODS AND MATERI...

Introduction Artificial intelligence (AI) technologies are increasingly applied to empower clinical decision support systems (CDSS), providing patient-specific recommendations improve work. Equally important technical advancement is human, social, and contextual factors that impact the successful implementation user adoption of AI-empowered CDSS (AI-CDSS). With growing interest in human-centere...