When a disaster exceeds the capacity of the affected country to cope with its own resources, the provision of external rescue and health services is required, and the deployment of relief units requested. Recently, the cost of international relief and the belief that such deployment is cost-effective has been questioned by the international community; unfortunately, there is still little informed debate and few detailed data are available. This paper presents the results of a comparative review on the cost-effectiveness analysis (CEA) of search and rescue (SAR) and Emergency Medical Team (EMT) deployment. The aim of this work is to provide an overview of the topic, highlight the criteria used to assess the effectiveness, and identify gaps in existing literature. The results show that both deployments are highly expensive, and their success is strongly related to the time they need to be operational; SAR deployments are characterized by limited outcomes in terms of lives saved, and EMTs by insufficient data and lack of detailed assessment. This research highlights that the criteria used to assess the effectiveness need to be explored further, considering different purposes, lengths of stay, and different activities performed, especially for any comparison. This study concludes that data reporting should be mandatory for humanitarian response agencies.

Summary

The discipline of evidence-based prescribing is relatively new to nurses and other non-medical prescribers. The introduction of clinical governance, which emphasises accountability, quality and efficiency, means that it is no longer acceptable to base clinical decisions on personal opinion. Prescribing itself is just one stage in making a rational treatment decision, which requires a fully structured approach. This article will highlight some of the considerations that the prescriber has to take into account, including: the efficacy and cost-effectiveness of treatment options, how to check the evidence, the benefits or harms of a treatment and, the patient's own involvement in the treatment plan.

In this study we present a review of the emerging field of meta-knowledge components as practised over the past decade among a variety of practitioners. We use the artificially defined term “meta-knowledge” to encompass all those different but overlapping notions used by the artificial intelligence and software engineering communities to represent reusable modelling frameworks: ontologies, problem-solving methods, patterns and experience factories and bases, to name but a few. We then elaborate on how meta-knowledge is deployed in the context of system's design to improve its reliability by consistency-checking, enhance its reuse potential and manage its knowledge-sharing. We speculate on its usefulness and explore technologies for supporting deployment of meta-knowledge. We argue that, despite the different approaches being followed in systems design by divergent communities, meta-knowledge is present in all cases, in a tacit or explicit form, and its utilisation depends on pragmatic aspects which we try to identify and critically review on criteria of effectiveness.