WAP-based personalized healthcare systems

In this paper a prototype system for personalized healthcare delivery is presented. The system involves monitoring and education services, designed specifically for people suffering from chronic diseases such as diabetes mellitus. Adaptation to every patient’s special requirements was kept in mind, in order to achieve personalization of the service provided. The technological platform adopted for implementing the service is the Wireless Application Protocol (WAP™), an emerging technology between the two most dynamically evolving communication mediums, the Internet and wireless communication networks. The fundamental idea behind this innovative system lies in the fact that by delivering customized to the special patients’ needs healthcare systems, a more flexible and efficient way of dealing with some kind of diseases may be provided. More precisely, adopting monitoring facilities by following a condition report process in a regular time base, healthcare delivery may become more prosperous. In the long term, clinical patterns useful for better diagnosis results may be extracted, by applying data-mining techniques on the data collected by the service. Thus, embodying such types of system in the demanding healthcare delivery domain can promise continuity of care, advanced quality of services, increased patient satisfaction and a more effective approach to disease management.

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.