From adverse drug event detection to prevention. A novel clinical decision support framework for medication safety.

BACKGROUND: Errors related to medication seriously affect patient safety and the quality of healthcare. It has been widely argued that various types of such errors may be prevented by introducing Clinical Decision Support Systems (CDSSs) at the point of care. OBJECTIVES: Although significant research has been conducted in the field, still medication safety is a crucial issue, while few research outcomes are mature enough to be considered for use in actual clinical settings. In this paper, we present a clinical decision support framework targeting medication safety with major focus on adverse drug event (ADE) prevention. METHODS: The novelty of the framework lies in its design that approaches the problem holistically, i.e., starting from knowledge discovery to provide reliable numbers about ADEs per hospital or medical unit to describe their consequences and probable causes, and next employing the acquired knowledge for decision support services development and deployment. Major design features of the framework's services are: a) their adaptation to the context of care (i.e. patient characteristics, place of care, and significance of ADEs), and b) their straightforward integration in the healthcare information technologies (IT) infrastructure thanks to the adoption of a service-oriented architecture (SOA) and relevant standards. RESULTS: Our results illustrate the successful interoperability of the framework with two commercially available IT products, i.e., a Computerized Physician Order Entry (CPOE) and an Electronic Health Record (EHR) system, respectively, along with a Web prototype that is independent of existing healthcare IT products. The conducted clinical validation with domain experts and test cases illustrates that the impact of the framework is expected to be major, with respect to patient safety, and towards introducing the CDSS functionality in practical use. CONCLUSIONS: This study illustrates an important potential for the applicability of the presented framework in delivering contextualized decision support services at the point of care and for making a substantial contribution towards ADE prevention. Nonetheless, further research is required in order to quantitatively and thoroughly assess its impact in medication safety.

A pervasive health system integrating patient monitoring, status logging and social sharing.

In this paper, we present the design and development of a pervasive health system enabling self-management of chronic patients during their everyday activities. The proposed system integrates patient health monitoring, status logging for capturing various problems or symptoms met, and social sharing of the recorded information within the patients community, aiming to facilitate disease management. A prototype is implemented on a mobile device illustrating the feasibility and applicability of the presented work by adopting unobtrusive vital signs monitoring through a wearable multi-sensing device, a service oriented architecture for handling communication issues, and popular micro-blogging services. Furthermore, a study has been conducted with 16 hypertensive patients, in order to investigate the user acceptance, the usefulness, and the virtue of the proposed system. The results show that the system is welcome by the chronic patients who are especially willing to share healthcare information, and easy to learn and use, while its features have been overall regarded by the patients as helpful for their disease management and treatment.