834 resultados para Hospital performance improvement
Resumo:
In general, the performance of construction projects, including their sustainability performance, does not meet optimal expectations. One aspect of this is the performance of the participants who are independent and make a significance impact on overall project outcomes. Of these participants, the client is traditionally the owner of the project, the architect or engineer is engaged as the lead designer and a contractor is selected to construct the facilities. Generally, the performance of the participants is gauged by considering three main factors, namely, time, cost and quality. As the level of satisfaction is a subjective issue, it is rarely used in the performance evaluation of construction work. Recently, various approaches to the measurement of satisfaction have been made in an attempt to determine the performance of construction project outcomes - for instance, client satisfaction, customer satisfaction, contractor satisfaction, occupant satisfaction and home buyer satisfaction. These not only identify the performance of the construction project but are also used to improve and maintain relationships. In addition, these assessments are necessary for the continuous improvement and enhanced cooperation of participants. The measurement of satisfaction levels primarily involves expectations and perceptions. An expectation can be regarded as a comparative standard of different needs, motives and beliefs, while a perception is a subjective interpretation that is influenced by moods, experiences and values. This suggests that the disparity between perceptions and expectations may possibly be used to represent different levels of satisfaction. However, this concept is rather new and in need of further investigation. This chapter examines the methods commonly practised in measuring satisfaction levels today and the advantages of promoting these methods. The results provide a preliminary review of the advantages of satisfaction measurement in the construction industry and recommendations are made concerning the most appropriate methods to use in identifying the performance of project outcomes.
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Purpose – The purpose of this paper is to examine the role of three strategies - organisational, business and information system – in post implementation of technological innovations. The findings reported in the paper are that improvements in operational performance can only be achieved by aligning technological innovation effectiveness with operational effectiveness. Design/methodology/approach – A combination of qualitative and quantitative methods was used to apply a two-stage methodological approach. Unstructured and semi structured interviews, based on the findings of the literature, were used to identify key factors used in the survey instrument design. Confirmatory factor analysis (CFA) was used to examine structural relationships between the set of observed variables and the set of continuous latent variables. Findings – Initial findings suggest that organisations looking for improvements in operational performance through adoption of technological innovations need to align with operational strategies of the firm. Impact of operational effectiveness and technological innovation effectiveness are related directly and significantly to improved operational performance. Perception of increase of operational effectiveness is positively and significantly correlated with improved operational performance. The findings suggest that technological innovation effectiveness is also positively correlated with improved operational performance. However, the study found that there is no direct influence of strategiesorganisational, business and information systems (IS) - on improvement of operational performance. Improved operational performance is the result of interactions between the implementation of strategies and related outcomes of both technological innovation and operational effectiveness. Practical implications – Some organisations are using technological innovations such as enterprise information systems to innovate through improvements in operational performance. However, they often focus strategically only on effectiveness of technological innovation or on operational effectiveness. Such a focus will be detrimental in the long-term of the enterprise. This research demonstrated that it is not possible to achieve maximum returns through technological innovations as dimensions of operational effectiveness need to be aligned with technological innovations to improve their operational performance. Originality/value – No single technological innovation implementation can deliver a sustained competitive advantage; rather, an advantage is obtained through the capacity of an organisation to exploit technological innovations’ functionality on a continuous basis. To achieve sustainable results, technology strategy must be aligned with organisational and operational strategies. This research proposes the key performance objectives and dimensions that organisations should focus to achieve a strategic alignment. Research limitations/implications – The principal limitation of this study is that the findings are based on investigation of small sample size. There is a need to explore the appropriateness of influence of scale prior to generalizing the results of this study.
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Advances in data mining have provided techniques for automatically discovering underlying knowledge and extracting useful information from large volumes of data. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large complex databases. Application of data mining to manufacturing is relatively limited mainly because of complexity of manufacturing data. Growing self organizing map (GSOM) algorithm has been proven to be an efficient algorithm to analyze unsupervised DNA data. However, it produced unsatisfactory clustering when used on some large manufacturing data. In this paper a data mining methodology has been proposed using a GSOM tool which was developed using a modified GSOM algorithm. The proposed method is used to generate clusters for good and faulty products from a manufacturing dataset. The clustering quality (CQ) measure proposed in the paper is used to evaluate the performance of the cluster maps. The paper also proposed an automatic identification of variables to find the most probable causative factor(s) that discriminate between good and faulty product by quickly examining the historical manufacturing data. The proposed method offers the manufacturers to smoothen the production flow and improve the quality of the products. Simulation results on small and large manufacturing data show the effectiveness of the proposed method.
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This paper presents the results of a pilot study examining the factors that impact most on the effective implementation of, and improvement to, Quality Mangement Sytems (QMSs) amongst Indonesian construction companies. Nine critical factors were identified from an extensive literature review, and a survey was conducted of 23 respondents from three specific groups (Quality Managers, Project Managers, and Site Engineers) undertaking work in the Indonesian infrastructure construction sector. The data has been analyzed initially using simple descriptive techniques. This study reveals that different groups within the sector have different opinions of the factors regardless of the degree of importance of each factor. However, the evaluation of construction project success and the incentive schemes for high performance staff, are the two factors that were considered very important by most of the respondents in all three groups. In terms of their assessment of tools for measuring contractor’s performance, additional QMS guidelines, techniques related to QMS practice provided by the Government, and benchmarking, a clear majority in each group regarded their usefulness as ‘of some importance’.
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Purpose: One strategy to minimize bacteria-associated adverse responses such as microbial keratitis, contact lens–induced acute red eye (CLARE), and contact lens induced peripheral ulcers (CLPUs) that occur with contact lens wear is the development of an antimicrobial or antiadhesive contact lens. Cationic peptides represent a novel approach for the development of antimicrobial lenses.---------- Methods: A novel cationic peptide, melimine, was covalently incorporated into silicone hydrogel lenses. Confirmation tests to determine the presence of peptide and anti-microbial activity were performed. Cationic lenses were then tested for their ability to prevent CLPU in the Staphylococcus aureus rabbit model and CLARE in the Pseudomonas aeruginosa guinea pig model. ---------- Results: In the rabbit model of CLPU, melimine-coated lenses resulted in significant reductions in ocular symptom scores and in the extent of corneal infiltration (P < 0.05). Evaluation of the performance of melimine lenses in the CLARE model showed significant improvement in all ocular response parameters measured, including the percentage of eyes with corneal infiltrates, compared with those observed in the eyes fitted with the control lens (P ≤ 0.05). ---------- Conclusions: Cationic coating of contact lenses with the peptide melimine may represent a novel method of prevention of bacterial growth on contact lenses and consequently result in reduction of the incidence and severity of adverse responses due to Gram-positive and -negative bacteria during lens wear.
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The traditional searching method for model-order selection in linear regression is a nested full-parameters-set searching procedure over the desired orders, which we call full-model order selection. On the other hand, a method for model-selection searches for the best sub-model within each order. In this paper, we propose using the model-selection searching method for model-order selection, which we call partial-model order selection. We show by simulations that the proposed searching method gives better accuracies than the traditional one, especially for low signal-to-noise ratios over a wide range of model-order selection criteria (both information theoretic based and bootstrap-based). Also, we show that for some models the performance of the bootstrap-based criterion improves significantly by using the proposed partial-model selection searching method. Index Terms— Model order estimation, model selection, information theoretic criteria, bootstrap 1. INTRODUCTION Several model-order selection criteria can be applied to find the optimal order. Some of the more commonly used information theoretic-based procedures include Akaike’s information criterion (AIC) [1], corrected Akaike (AICc) [2], minimum description length (MDL) [3], normalized maximum likelihood (NML) [4], Hannan-Quinn criterion (HQC) [5], conditional model-order estimation (CME) [6], and the efficient detection criterion (EDC) [7]. From a practical point of view, it is difficult to decide which model order selection criterion to use. Many of them perform reasonably well when the signal-to-noise ratio (SNR) is high. The discrepancies in their performance, however, become more evident when the SNR is low. In those situations, the performance of the given technique is not only determined by the model structure (say a polynomial trend versus a Fourier series) but, more importantly, by the relative values of the parameters within the model. This makes the comparison between the model-order selection algorithms difficult as within the same model with a given order one could find an example for which one of the methods performs favourably well or fails [6, 8]. Our aim is to improve the performance of the model order selection criteria in cases where the SNR is low by considering a model-selection searching procedure that takes into account not only the full-model order search but also a partial model order search within the given model order. Understandably, the improvement in the performance of the model order estimation is at the expense of additional computational complexity.
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The unique characteristics of the construction industry - such as the fragmentation of its processes, varied scope of works and diversity of its participants - are contributory factors to poor project performance. Several issues are unresolved due to the lack of a comprehensive technique to measure project outcomes including: inefficient decision making, insufficient communication, uncertain site conditions, a continuously changing environment, inharmonious working relationships, mismatched objectives within the project team and a blame culture. One approach to overcoming these problems appears to be to measure performance by gauging contractor satisfaction (Co-S) levels, but this has not been widely investigated as yet. Additionally, the key Co-S dimensions at the project level are still not fully identified. ----- ----- This paper concerns a study of satisfaction dimensions, primarily by a postal questionnaire survey of construction contractors registered by the Malaysian Construction Industry Development Board (CIDB). Eight satisfaction dimensions are identified that are significantly and substantially relate to these contractors - comprising: project cost performance, schedule performance, product performance, design satisfaction, site safety, project profitability, business performance and relationships between participants. -Each of these dimensions is accorded different priority levels of satisfaction by different contractors. ----- ----- The output of this study will be useful in raising the awareness and understanding of project teams regarding contractors’ needs, mutual objectives and open communication to help to deliver a successful project.
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Numerous tools and techniques have been developed to eliminate or reduce waste and carry out Lean concepts in the manufacturing environment. However, in practice, manufacturers encounter difficulties to clearly identify the weaknesses of the existing processes in order to address them by implementing Lean tools. Moreover, selection and implementation of appropriate Lean strategies to address the problems identified is a challenging task. According best of authors‟ knowledge, there is no method available to quantitatively evaluate the cost and benefits of implementing a Lean strategy to address the weaknesses in the manufacturing process. Therefore, benefits of Lean approaches cannot be clearly established. The authors developed a methodology to quantitatively measure the performances of a manufacturing system in detecting the causes of inefficiencies and to select appropriate Lean strategies to address the problems identified. The proposed methodology demonstrates that the Lean strategies should be implemented based on the contexts of the organization and identified problem in order to achieve maximum cost benefits. Finally, a case study has been presented to demonstrate how the procedure developed works in practical situation.
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Purpose The purpose of this paper is to explore the process, and analyse the implementation of constructability improvement and innovation result during the planning and design for sea water intake structure of fertilizer plant project. Design/methodology/approach The research methodology approach is case study method at project level. This constructability improvement process was investigated by using constructability implementation check lists, direct observation, documented lesson learned analysis and key personnel interviews. Findings The case study shows that the implementation of constructability during planning and design stage for this sea water intake structure has increased the project performance as well as improved the schedule by 5 months (14.21%) and reduced the project cost by 15.35%. Research limitations/implications This case study was limited to three (3) previous sea water intake projects as references and one (1) of new method sea water intake structure at fertilizer plant project. Practical implications A constructability improvement check list using theory and lesson learned for the specific construction project was documented. Originality/value The findings support the relevant study of constructability and provide specific lesson learned for three (3) previous project and one (1) of the new innovation method of the construction project and documented by the company.
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Older adults, especially those acutely ill, are vulnerable to developing malnutrition due to a range of risk factors. The high prevalence and extensive consequences of malnutrition in hospitalised older adults have been reported extensively. However, there are few well-designed longitudinal studies that report the independent relationship between malnutrition and clinical outcomes after adjustment for a wide range of covariates. Acutely ill older adults are exceptionally prone to nutritional decline during hospitalisation, but few reports have studied this change and impact on clinical outcomes. In the rapidly ageing Singapore population, all this evidence is lacking, and the characteristics associated with the risk of malnutrition are also not well-documented. Despite the evidence on malnutrition prevalence, it is often under-recognised and under-treated. It is therefore crucial that validated nutrition screening and assessment tools are used for early identification of malnutrition. Although many nutrition screening and assessment tools are available, there is no universally accepted method for defining malnutrition risk and nutritional status. Most existing tools have been validated amongst Caucasians using various approaches, but they are rarely reported in the Asian elderly and none has been validated in Singapore. Due to the multiethnicity, cultural, and language differences in Singapore older adults, the results from non-Asian validation studies may not be applicable. Therefore it is important to identify validated population and setting specific nutrition screening and assessment methods to accurately detect and diagnose malnutrition in Singapore. The aims of this study are therefore to: i) characterise hospitalised elderly in a Singapore acute hospital; ii) describe the extent and impact of admission malnutrition; iii) identify and evaluate suitable methods for nutritional screening and assessment; and iv) examine changes in nutritional status during admission and their impact on clinical outcomes. A total of 281 participants, with a mean (+SD) age of 81.3 (+7.6) years, were recruited from three geriatric wards in Tan Tock Seng Hospital over a period of eight months. They were predominantly Chinese (83%) and community-dwellers (97%). They were screened within 72 hours of admission by a single dietetic technician using four nutrition screening tools [Tan Tock Seng Hospital Nutrition Screening Tool (TTSH NST), Nutritional Risk Screening 2002 (NRS 2002), Mini Nutritional Assessment-Short Form (MNA-SF), and Short Nutritional Assessment Questionnaire (SNAQ©)] that were administered in no particular order. The total scores were not computed during the screening process so that the dietetic technician was blinded to the results of all the tools. Nutritional status was assessed by a single dietitian, who was blinded to the screening results, using four malnutrition assessment methods [Subjective Global Assessment (SGA), Mini Nutritional Assessment (MNA), body mass index (BMI), and corrected arm muscle area (CAMA)]. The SGA rating was completed prior to computation of the total MNA score to minimise bias. Participants were reassessed for weight, arm anthropometry (mid-arm circumference, triceps skinfold thickness), and SGA rating at discharge from the ward. The nutritional assessment tools and indices were validated against clinical outcomes (length of stay (LOS) >11days, discharge to higher level care, 3-month readmission, 6-month mortality, and 6-month Modified Barthel Index) using multivariate logistic regression. The covariates included age, gender, race, dementia (defined using DSM IV criteria), depression (defined using a single question “Do you often feel sad or depressed?”), severity of illness (defined using a modified version of the Severity of Illness Index), comorbidities (defined using Charlson Comorbidity Index, number of prescribed drugs and admission functional status (measured using Modified Barthel Index; MBI). The nutrition screening tools were validated against the SGA, which was found to be the most appropriate nutritional assessment tool from this study (refer section 5.6) Prevalence of malnutrition on admission was 35% (defined by SGA), and it was significantly associated with characteristics such as swallowing impairment (malnourished vs well-nourished: 20% vs 5%), poor appetite (77% vs 24%), dementia (44% vs 28%), depression (34% vs 22%), and poor functional status (MBI 48.3+29.8 vs 65.1+25.4). The SGA had the highest completion rate (100%) and was predictive of the highest number of clinical outcomes: LOS >11days (OR 2.11, 95% CI [1.17- 3.83]), 3-month readmission (OR 1.90, 95% CI [1.05-3.42]) and 6-month mortality (OR 3.04, 95% CI [1.28-7.18]), independent of a comprehensive range of covariates including functional status, disease severity and cognitive function. SGA is therefore the most appropriate nutritional assessment tool for defining malnutrition. The TTSH NST was identified as the most suitable nutritional screening tool with the best diagnostic performance against the SGA (AUC 0.865, sensitivity 84%, specificity 79%). Overall, 44% of participants experienced weight loss during hospitalisation, and 27% had weight loss >1% per week over median LOS 9 days (range 2-50). Wellnourished (45%) and malnourished (43%) participants were equally prone to experiencing decline in nutritional status (defined by weight loss >1% per week). Those with reduced nutritional status were more likely to be discharged to higher level care (adjusted OR 2.46, 95% CI [1.27-4.70]). This study is the first to characterise malnourished hospitalised older adults in Singapore. It is also one of the very few studies to (a) evaluate the association of admission malnutrition with clinical outcomes in a multivariate model; (b) determine the change in their nutritional status during admission; and (c) evaluate the validity of nutritional screening and assessment tools amongst hospitalised older adults in an Asian population. Results clearly highlight that admission malnutrition and deterioration in nutritional status are prevalent and are associated with adverse clinical outcomes in hospitalised older adults. With older adults being vulnerable to risks and consequences of malnutrition, it is important that they are systematically screened so timely and appropriate intervention can be provided. The findings highlighted in this thesis provide an evidence base for, and confirm the validity of the current nutrition screening and assessment tools used among hospitalised older adults in Singapore. As the older adults may have developed malnutrition prior to hospital admission, or experienced clinically significant weight loss of >1% per week of hospitalisation, screening of the elderly should be initiated in the community and continuous nutritional monitoring should extend beyond hospitalisation.
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In 2001, the Malaysian Code on Corporate Governance (MCCG) became an integral part of the Bursa Malaysia Listing Rules, which requires all listed firms to disclose the extent of compliance with the MCCG. Our panel analysis of 440 firms from 1999 to 2002 finds that corporate governance reform in Malaysia has been successful, with a significant improvement in governance practices. The relationship between ownership by the Employees Provident Fund (EPF) and corporate governance has strengthened during the period subsequent to the reform, in line with the lead role taken by the EPF in establishing the Minority Shareholders Watchdog Group. The implementation of MCCG has had a substantial effect on shareholders' wealth, increasing stock prices by an average of about 4.8%. Although there is no evidence that politically connected firms perform better, political connections do have a significantly negative effect on corporate governance, which is mitigated by institutional ownership.
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Dealing with product yield and quality in manufacturing industries is getting more difficult due to the increasing volume and complexity of data and quicker time to market expectations. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large databases. Growing self-organizing map (GSOM) is established as an efficient unsupervised datamining algorithm. In this study some modifications to the original GSOM are proposed for manufacturing yield improvement by clustering. These modifications include introduction of a clustering quality measure to evaluate the performance of the programme in separating good and faulty products and a filtering index to reduce noise from the dataset. Results show that the proposed method is able to effectively differentiate good and faulty products. It will help engineers construct the knowledge base to predict product quality automatically from collected data and provide insights for yield improvement.
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The uncertain and dynamic nature of International Construction Joint Venture (ICJV) performance is evolved with many critical factors which lead to make partner relationships more complex in respect of making decisions to maintain a cohesive environment. Addressing to the fact, a generic system dynamics performance model for ICJV is developed by integrating a number variables as to get an overall impact on performance of ICJV and to make effective decisions based on that. In order to formulate and validate the model both structurally and behaviourally, both qualitative and quantitative data are gathered by conducting intensive interviews from two ICJVs in Thailand. After conducting intensive simulations of model, three major problems are identified related to negative value gap, low productivity in construction and high rate of ineffective information sharing of both ICJVs. Several policies are suggested and integrated application of these policies provides a maximum improvement to performance of the ICJV.