Social impact assessment of a sewerage project in Barbados

This report investigates why a nationally important and internationally funded infrastructural project within the Caribbean island of Barbados — The South Coast Sewerage Project — spurned a substantial level of negative socio-economic externalities. Primary and secondary research evaluated the presence or effectiveness of social impact assessment as a mitigation tool. The mitigation measures suggested within the appraisal report appear to have been considered by the Project Execution Unit (PEU) of Government of Barbados. The primary obstacle seems to have been the implementation of the mitigation process by the contractor. This highlights the need to foster an interconnected and symbiotic relationship between appraisal and implementation, if an initiative is to be conducted efficiently and effectively. Additionally, the South Coast Sewerage Project exemplifies the importance of establishing and sustaining a monitoring/control mechanism as an integral part of project construction.

Managing healthcare quality in project management framework

Healthcare professionals routinely deploy various quality management tools and techniques in order to improve performance of healthcare delivery. However, they are characterised by fragmented approach i.e., they are not linked with the strategic intent of the organisation. This study introduces a holistic quality improvement method, which integrates all quality improvement projects with the strategic intent of the healthcare organisations. It first identifies a healthcare system and its environment. The Strengths, Weaknesses, Opportunities and Threats (SWOT) of the system are then derived with the involvement of the concerned stakeholders. This leads to developing the strategies in order to satisfy customers in line with the organisation's competitive position. These strategies help identify a few projects, the implementation of which ensures achievement of desired quality. The projects are then prioritised with the involvement of the concerned stakeholders and implemented in order to improve the system performance. The effectiveness of the method has been demonstrated using a case study of an intensive care unit at the Eric Williams Medical Sciences Complex Hospital in Trinidad. Copyright © 2007 Inderscience Enterprises Ltd.

Data envelopment analysis model for the appraisal and relative performance evaluation of nurses at an intensive care unit

The appraisal and relative performance evaluation of nurses are very important and beneficial for both nurses and employers in an era of clinical governance, increased accountability and high standards of health care services. They enhance and consolidate the knowledge and practical skills of nurses by identification of training and career development plans as well as improvement in health care quality services, increase in job satisfaction and use of cost-effective resources. In this paper, a data envelopment analysis (DEA) model is proposed for the appraisal and relative performance evaluation of nurses. The model is validated on thirty-two nurses working at an Intensive Care Unit (ICU) at one of the most recognized hospitals in Lebanon. The DEA was able to classify nurses into efficient and inefficient ones. The set of efficient nurses was used to establish an internal best practice benchmark to project career development plans for improving the performance of other inefficient nurses. The DEA result confirmed the ranking of some nurses and highlighted injustice in other cases that were produced by the currently practiced appraisal system. Further, the DEA model is shown to be an effective talent management and motivational tool as it can provide clear managerial plans related to promoting, training and development activities from the perspective of nurses, hence increasing their satisfaction, motivation and acceptance of appraisal results. Due to such features, the model is currently being considered for implementation at ICU. Finally, the ratio of the number DEA units to the number of input/output measures is revisited with new suggested values on its upper and lower limits depending on the type of DEA models and the desired number of efficient units from a managerial perspective.