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Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital. [ABSTRACT FROM AUTHOR]

The Logical Elements Rule Method (LERM) is a step-wise method for formalizing if-then clinical rules. We applied LERM to a set of 40 clinical rules used in pharmacological quality assessment initiatives to assess (1) the amenability of the rules to formalization for decision support application (2) comparing adherence to rules that can and cannot be formalized, and (3) the usefulness of LERM as a tool for this task. Five rules could not be formalized, all due to unclear decision criteria. The adherence to ambiguous, non-formalizable rules was significantly lower than for formalizable ones (<0.001). We modified LERM with three additions for this task: (a) adding the sub-step of restating the rules in a consistent natural-language grammar before decomposing them into normal form, (b) creating rules to use in lieu of a controlled vocabulary, and (c) adding the requirement that a time frame must be defined for all medications (before hospitalization, current medication, new medication, or discharge medication). Although the clinical rules in this sample are all stated as semi-structured if-then recommendations and are used in quality assessment initiatives, many ambiguities and inconsistencies in the clinical rules were identified by using LERM. [ABSTRACT FROM AUTHOR]

This paper describes the deployment of a platform to enable processing of currently uncharted high frequency, high fidelity, synchronous data from medical devices. Such a platform would support the next generation of informatics solutions for neonatal intensive care. We present Artemis, a platform for real-time enactment of clinical knowledge as it relates to multidimensional data analysis and clinical research. Through specific deployment examples at two different neonatal intensive care units, we demonstrate that Artemis supports: 1) instantiation of clinical rules; 2) multidimensional analysis; 3) distribution of services for critical care via cloud computing; and 4) accomplishing 1 through 3 using current technology without a negative impact on patient care. [ABSTRACT FROM AUTHOR]

Clinical decision support systems (CDSS) are the new generation clinical support tools that ‘make it easy to do it right’. Despite promising results, these systems are not common practice, although experts agree that the necessary revolution in health care will depend on its implementation. To accelerate adoption a strategy is handed for structured development and validation of CDSS' content (clinical rules). The first results show that the proposed strategy is easily applicable for creating specific and reliable rules, generating relevant recommendations. [ABSTRACT FROM AUTHOR]