Evaluation of quality of life related to nutritional status

The way in which the quality of life related to health (HRQoL) is affected by the nutritional status of the patient is a subject of constant interest and permanent debate. The purpose of the present paper is to review those studies that relate HRQoL to nutritional status and examine the tools (questionnaires) that they use to investigate this relationship. A critical review of published studies was carried out via an investigation of the following databases: MEDLINE (via PubMed); EMBASE; The Cochrane Library; Cumulative Index to Nursing and Allied Health Literature (CINAHL); Institute for Scientific Information (ISI) Web of Science; Latin American and Caribbean Health Sciences Literature (LILACS); Spanish Health Sciences Bibliographic Index (IBECS). The search was carried out from the earliest date possible until July 2007.The medical subject heading terms used were ‘quality of life’, ‘nutritional status’ and ‘questionnaires’. The articles had to contain at least one questionnaire that evaluated quality of life. Twenty-eight documents fulfilling the inclusion criteria were accepted, although none of them used a specific questionnaire to evaluate HRQoL related to nutritional status. However, some of them used a combination of generic questionnaires with the intention of evaluating the same. Only three studies selectively addressed the relationship between nutritional status and quality of life, this evaluation being performed not by means of specific questionnaires but by statistical analysis of data obtained via validated questionnaires.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

In this work, we analyze the effect of incorporating life cycle inventory (LCI) uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear programming (MILP) coupled with a two-step transformation scenario generation algorithm with the unique feature of providing scenarios where the LCI random variables are correlated and each one of them has the desired lognormal marginal distribution. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study of a petrochemical supply chain. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact, and moreover the correlation among environmental burdens provides more realistic scenarios for the decision making process.

Making it easy to do the right thing in healthcare: Advancing improvement science education through accredited pan European higher education modules

Background: Numerous international policy drivers espouse the need to improve healthcare. The application of Improvement Science has the potential to restore the balance of healthcare and transform it to a more person-centred and quality improvement focussed system. However there is currently no accredited Improvement Science education offered routinely to healthcare students. This means that there are a huge number of healthcare professionals who do not have the conceptual or experiential skills to apply Improvement Science in everyday practise. Methods: This article describes how seven European Higher Education Institutions (HEIs) worked together to develop four evidence informed accredited inter-professional Improvement Science modules for under and postgraduate healthcare students. It outlines the way in which a Policy Delphi, a narrative literature review, a review of the competency and capability requirements for healthcare professionals to practise Improvement Science, and a mapping of current Improvement Science education informed the content of the modules. Results: A contemporary consensus definition of Healthcare Improvement Science was developed. The four Improvement Science modules that have been designed are outlined. A framework to evaluate the impact modules have in practise has been developed and piloted. Conclusion: The authors argue that there is a clear need to advance healthcare Improvement Science education through incorporating evidence based accredited modules into healthcare professional education. They suggest that if Improvement Science education, that incorporates work based learning, becomes a staple part of the curricula in inter-professional education then it has real promise to improve the delivery, quality and design of healthcare.