Re-admission to intensive care: Identification of risk factors

Background and Purpose. The re-admission of patients to intensive care is associated with increased morbidity, mortality, loss of morale for patients and family, and increased health costs. The aim of the present study was to identify factors which place patients at a higher risk of re-admission to intensive care. Method. A prospective study of patients who were re-admitted to a 22-bed tertiary level intensive care facility within a 12-month period. Data were kept on every patient re-admitted to intensive care, including standard demographic data, initial admission diagnosis, co-morbidities, re-admission diagnosis, mobility on discharge, secretions, airway, chest X-ray, PaCO2, PaO2, PaO2/FiO2and time of discharge. Subjects included 74 patients who had been re-admitted to intensive care in a 12-month period and a comparison group of patients who were not re-admitted to intensive care. A cross-tabs procedure was initially used to estimate maximum likelihood. Significant factors with an value of 65 years (p

Assessing the quality of risk factor survey data: lessons from the WHO MONICA Project

Background and purpose Survey data quality is a combination of the representativeness of the sample, the accuracy and precision of measurements, data processing and management with several subcomponents in each. The purpose of this paper is to show how, in the final risk factor surveys of the WHO MONICA Project, information on data quality were obtained, quantified, and used in the analysis. Methods and results In the WHO MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) Project, the information about the data quality components was documented in retrospective quality assessment reports. On the basis of the documented information and the survey data, the quality of each data component was assessed and summarized using quality scores. The quality scores were used in sensitivity testing of the results both by excluding populations with low quality scores and by weighting the data by its quality scores. Conclusions Detailed documentation of all survey procedures with standardized protocols, training, and quality control are steps towards optimizing data quality. Quantifying data quality is a further step. Methods used in the WHO MONICA Project could be adopted to improve quality in other health surveys.

Selection and application of risk management tools and techniques for build-operate-transfer projects

Construction projects are risky. However, the characteristics of the risk highly depend on the type of procurement being adopted for managing the project. A build-operate-transfer (BOT) project is recognized as one of the most risky project schemes. There are instances of project failure where a BOT scheme was employed. Ineffective rts are increasingly being managed using various risk management tools and techniques. However, application of those tools depends on the nature of the project, organization's policy, project management strategy, risk attitude of the project team members, and availability of the resources. Understanding of the contents and contexts of BOT projects, together with a thorough understanding of risk management tools and techniques, helps select processes of risk management for effective project implementation in a BOT scheme. This paper studies application of risk management tools and techniques in BOT projects through reviews of relevant literatures and develops a model for selecting risk management process for BOT projects. The application to BOT projects is considered from the viewpoints of the major project participants. Discussion is also made with regard to political risks. This study would contribute to the establishment of a framework for systematic risk management in BOT projects.