Clinical Decision Support System for Point of Care Use

Objectives: The objective of this research was to design a clinical decision support system (CDSS) that supports heterogeneous clinical decision problems and runs on multiple computing platforms. Meeting this objective required a novel design to create an extendable and easy to maintain clinical CDSS for point of care support. The proposed solution was evaluated in a proof of concept implementation.

Methods: Based on our earlier research with the design of a mobile CDSS for emergency triage we used ontology-driven design to represent essential components of a CDSS. Models of clinical decision problems were derived from the ontology and they were processed into executable applications during runtime. This allowed scaling applications’ functionality to the capabilities of computing platforms. A prototype of the system was implemented using the extended client-server architecture and Web services to distribute the functions of the system and to make it operational in limited connectivity conditions.

Results: The proposed design provided a common framework that facilitated development of diversified clinical applications running seamlessly on a variety of computing platforms. It was prototyped for two clinical decision problems and settings (triage of acute pain in the emergency department and postoperative management of radical pros-tatectomy on the hospital ward) and implemented on two computing platforms – desktop and handheld computers.

Conclusions: The requirement of the CDSS heterogeneity was satisfied with ontology-driven design. Processing of application models described with the help of ontological models allowed having a complex system running on multiple computing platforms with different capabilities. Finally, separation of models and runtime components contributed to improved extensibility and maintainability of the system.

Heterogeneous Ice Nucleation by Soufriere Hills Volcanic Ash Immersed in Water Droplets

Fine particles of ash emitted during volcanic eruptions may sporadically influence cloud properties on a regional or global scale as well as influencing the dynamics of volcanic clouds and the subsequent dispersion of volcanic aerosol and gases. It has been shown that volcanic ash can trigger ice nucleation, but ash from relatively few volcanoes has been studied for its ice nucleating ability. In this study we quantify the efficiency with which ash from the Soufriere Hills volcano on Montserrat nucleates ice when immersed in supercooled water droplets. Using an ash sample from the 11^th February 2010 eruption, we report ice nucleating efficiencies from 246 to 265 K. This wide range of temperatures was achieved using two separate droplet freezing instruments, one employing nanolitre droplets, the other using microlitre droplets. Soufriere Hills volcanic ash was significantly more efficient than all other ash samples that have been previously examined. At present the reasons for these differences are not understood, but may be related to mineralogy, amorphous content and surface chemistry.