970 resultados para quality indices


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Background, aim, and scope Urban motor vehicle fleets are a major source of particulate matter pollution, especially of ultrafine particles (diameters < 0.1 µm), and exposure to particulate matter has known serious health effects. A considerable body of literature is available on vehicle particle emission factors derived using a wide range of different measurement methods for different particle sizes, conducted in different parts of the world. Therefore the choice as to which are the most suitable particle emission factors to use in transport modelling and health impact assessments presented as a very difficult task. The aim of this study was to derive a comprehensive set of tailpipe particle emission factors for different vehicle and road type combinations, covering the full size range of particles emitted, which are suitable for modelling urban fleet emissions. Materials and methods A large body of data available in the international literature on particle emission factors for motor vehicles derived from measurement studies was compiled and subjected to advanced statistical analysis, to determine the most suitable emission factors to use in modelling urban fleet emissions. Results This analysis resulted in the development of five statistical models which explained 86%, 93%, 87%, 65% and 47% of the variation in published emission factors for particle number, particle volume, PM1, PM2.5 and PM10 respectively. A sixth model for total particle mass was proposed but no significant explanatory variables were identified in the analysis. From the outputs of these statistical models, the most suitable particle emission factors were selected. This selection was based on examination of the statistical robustness of the statistical model outputs, including consideration of conservative average particle emission factors with the lowest standard errors, narrowest 95% confidence intervals and largest sample sizes, and the explanatory model variables, which were Vehicle Type (all particle metrics), Instrumentation (particle number and PM2.5), Road Type (PM10) and Size Range Measured and Speed Limit on the Road (particle volume). Discussion A multiplicity of factors need to be considered in determining emission factors that are suitable for modelling motor vehicle emissions, and this study derived a set of average emission factors suitable for quantifying motor vehicle tailpipe particle emissions in developed countries. Conclusions The comprehensive set of tailpipe particle emission factors presented in this study for different vehicle and road type combinations enable the full size range of particles generated by fleets to be quantified, including ultrafine particles (measured in terms of particle number). These emission factors have particular application for regions which may have a lack of funding to undertake measurements, or insufficient measurement data upon which to derive emission factors for their region. Recommendations and perspectives In urban areas motor vehicles continue to be a major source of particulate matter pollution and of ultrafine particles. It is critical that in order to manage this major pollution source methods are available to quantify the full size range of particles emitted for traffic modelling and health impact assessments.

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This article explores the quality of accounting information in listed family firms. The authors exploit the features of the Italian equitymarket characterizd by high ownership concentration across all tpes of firms to disentangle the effects of family ownership from other major block holders on the quality of accounting information. The findings document that family firms convey financial information of higher quality compared to the nonfamily peers. Furthermore the authors provide evidence that the determinants of accounting quality differ across family and nonfamily firms.

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While Information services function’s (ISF) service quality is not a new concept and has received considerable attention for over two decades, cross-cultural research of ISF’s service quality is not very mature. The author argues that the relationship between cultural dimensions and the ISF’s service quality dimensions may provide useful insights for how organisations should deal with different cultural groups. This paper will show that ISF’s service quality dimensions vary from one culture to another. The study adopts Hofstede’s (1980, 1991) typology of cultures and the “zones of tolerance” (ZOT) service quality measure reported by Kettinger & Lee (2005) as the primary commencing theory-base. In this paper, the author hypothesised and tested the influences of culture on users’ service quality perceptions and found strong empirical support for the study’s hypotheses. The results of this study indicate that as a result of their cultural characteristics, users vary in both their overall service quality perceptions and their perceptions on each of the four dimensions of ZOT service quality.

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Australia is leading the way in establishing a national system (the Palliative Care Outcomes Collaboration – PCOC) to measure the outcomes and quality of specialist palliative care services and to benchmark services across the country. This article reports on analysis of data collected routinely at point-of-care on 5939 patients treated by the first fifty one services that voluntarily joined PCOC. By March 2009, 111 services have agreed to join PCOC, representing more than 70% of services and more than 80% of specialist palliative care patients nationally. All states and territories are involved in this unique process that has involved extensive consultation and infrastructure and close collaboration between health services and researchers. The challenges of dealing with wide variation in outcomes and practice and the progress achieved to date are described. PCOC is aiming to improve understanding of the reasons for variations in clinical outcomes between specialist palliative care patients and differences in service outcomes as a critical step in an ongoing process to improve both service quality and patient outcomes. What is known about the topic? Governments internationally are grappling with how best to provide care for people with life limiting illnesses and how best to measure the outcomes and quality of that care. There is little international evidence on how to measure the quality and outcomes of palliative care on a routine basis. What does this paper add? The Palliative Care Outcomes Collaboration (PCOC) is the first effort internationally to measure the outcomes and quality of specialist palliative care services and to benchmark services on a national basis through an independent third party. What are the implications for practitioners? If outcomes and quality are to be measured on a consistent national basis, standard clinical assessment tools that are used as part of everyday clinical practice are necessary.

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Background: Loneliness and low mood are associated with significant negative health outcomes including poor sleep, but the strength of the evidence underlying these associations varies. There is strong evidence that poor sleep quality and low mood are linked, but only emerging evidence that loneliness and poor sleep are associated. Aims: To independently replicate the finding that loneliness and poor subjective sleep quality are associated and to extend past research by investigating lifestyle regularity as a possible mediator of relationships, since lifestyle regularity has been linked to loneliness and poor sleep. Methods: Using a cross-sectional design, 97 adults completed standardized measures of loneliness, lifestyle regularity, subjective sleep quality and mood. Results: Loneliness was a significant predictor of sleep quality. Lifestyle regularity was not a predictor of, nor associated with, mood, sleep quality or loneliness. Conclusions: This study provides an important independent replication of the association between poor sleep and loneliness. However, the mechanism underlying this link remains unclear. A theoretically plausible mechanism for this link, lifestyle regularity, does not explain the relationship between loneliness and poor sleep. The nexus between loneliness and poor sleep is unlikely to be broken by altering the social rhythm of patients who present with poor sleep and loneliness.

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Aim Australian residential aged care does not have a system of quality assessment related to clinical outcomes, or comprehensive quality benchmarking. The Residential Care Quality Assessment was developed to fill this gap; and this paper discusses the process by which preliminary benchmarks representing high and low quality were developed for it. Methods Data were collected from all residents (n = 498) of nine facilities. Numerator–denominator analysis of clinical outcomes occurred at a facility-level, with rank-ordered results circulated to an expert panel. The panel identified threshold scores to indicate excellent and questionable care quality, and refined these through Delphi process. Results Clinical outcomes varied both within and between facilities; agreed thresholds for excellent and poor outcomes were finalised after three Delphi rounds. Conclusion Use of the Residential Care Quality Assessment provides a concrete means of monitoring care quality and allows benchmarking across facilities; its regular use could contribute to improved care outcomes within residential aged care in Australia.

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Process modeling is a central element in any approach to Business Process Management (BPM). However, what hinders both practitioners and academics is the lack of support for assessing the quality of process models – let alone realizing high quality process models. Existing frameworks are highly conceptual or too general. At the same time, various techniques, tools, and research results are available that cover fragments of the issue at hand. This chapter presents the SIQ framework that on the one hand integrates concepts and guidelines from existing ones and on the other links these concepts to current research in the BPM domain. Three different types of quality are distinguished and for each of these levels concrete metrics, available tools, and guidelines will be provided. While the basis of the SIQ framework is thought to be rather robust, its external pointers can be updated with newer insights as they emerge.

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Goals: Few studies have repeatedly evaluated quality of life and potentially relevant factors in patients with benign primary brain tumor. The purpose of this study was to explore the relationship between the experience of the symptom distress, functional status, depression, and quality of life prior to surgery (T1) and 1 month post-discharge (T2). ---------- Patients and methods: This was a prospective cohort study including 58 patients with benign primary brain tumor in one teaching hospital in the Taipei area of Taiwan. The research instruments included the M.D. Anderson Symptom Inventory, the Functional Independence Measure scale, the Hospital Depression Scale, and the Functional Assessment of Cancer Therapy-Brain.---------- Results: Symptom distress (T1: r=−0.90, p<0.01; T2: r=−0.52, p<0.01), functional status (T1: r=0.56, p<0.01), and depression (T1: r=−0.71, p<0.01) demonstrated a significant relationship with patients' quality of life. Multivariate analysis identified symptom distress (explained 80.2%, Rinc 2=0.802, p=0.001) and depression (explained 5.2%, Rinc 2=0.052, p<0.001) continued to have a significant independent influence on quality of life prior to surgery (T1) after controlling for key demographic and medical variables. Furthermore, only symptom distress (explained 27.1%, Rinc 2=0.271, p=0.001) continued to have a significant independent influence on quality of life at 1 month after discharge (T2).---------- Conclusions: The study highlights the potential importance of a patient's symptom distress on quality of life prior to and following surgery. Health professionals should inquire about symptom distress over time. Specific interventions for symptoms may improve the symptom impact on quality of life. Additional studies should evaluate symptom distress on longer-term quality of life of patients with benign brain tumor.

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Internet and Web services have been used in both teaching and learning and are gaining popularity in today’s world. E-Learning is becoming popular and considered the latest advance in technology based learning. Despite the potential advantages for learning in a small country like Bhutan, there is lack of eServices at the Paro College of Education. This study investigated students’ attitudes towards online communities and frequency of access to the Internet, and how students locate and use different sources of information in their project tasks. Since improvement was at the heart of this research, an action research approach was used. Based on the idea of purposeful sampling, a semi-structured interview and observations were used as data collection instruments. 10 randomly selected students (5 girls and 5 boys) participated in this research as the controlled group. The study findings indicated that there is a lack of educational information technology services, such as e-learning at the college. Internet connection being very slow was the main barrier to learning using e-learning or accessing Internet resources. There is a strong relationship between the quality of written task and the source of the information, and between Web searching and learning. The source of information used in assignments and project work is limited to books in the library which are often outdated and of poor quality. Project tasks submitted by most of the students were of poor quality.

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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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Background: Clinical practice and clinical research has made a concerted effort to move beyond the use of clinical indicators alone and embrace patient focused care through the use of patient reported outcomes such as healthrelated quality of life. However, unless patients give consistent consideration to the health states that give meaning to measurement scales used to evaluate these constructs, longitudinal comparison of these measures may be invalid. This study aimed to investigate whether patients give consideration to a standard health state rating scale (EQ-VAS) and whether consideration of good and poor health state descriptors immediately changes their selfreport. Methods: A randomised crossover trial was implemented amongst hospitalised older adults (n = 151). Patients were asked to consider descriptions of extremely good (Description-A) and poor (Description-B) health states. The EQ-VAS was administered as a self-report at baseline, after the first descriptors (A or B), then again after the remaining descriptors (B or A respectively). At baseline patients were also asked if they had considered either EQVAS anchors. Results: Overall 106/151 (70%) participants changed their self-evaluation by ≥5 points on the 100 point VAS, with a mean (SD) change of +4.5 (12) points (p < 0.001). A total of 74/151 (49%) participants did not consider the best health VAS anchor, of the 77 who did 59 (77%) thought the good health descriptors were more extreme (better) then they had previously considered. Similarly 85/151 (66%) participants did not consider the worst health anchor of the 66 who did 63 (95%) thought the poor health descriptors were more extreme (worse) then they had previously considered. Conclusions: Health state self-reports may not be well considered. An immediate significant shift in response can be elicited by exposure to a mere description of an extreme health state despite no actual change in underlying health state occurring. Caution should be exercised in research and clinical settings when interpreting subjective patient reported outcomes that are dependent on brief anchors for meaning. Trial Registration: Australian and New Zealand Clinical Trials Registry (#ACTRN12607000606482) http://www.anzctr. org.au

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Background: Assessments of change in subjective patient reported outcomes such as health-related quality of life (HRQoL) are a key component of many clinical and research evaluations. However, conventional longitudinal evaluation of change may not agree with patient perceived change if patients' understanding of the subjective construct under evaluation changes over time (response shift) or if patients' have inaccurate recollection (recall bias). This study examined whether older adults' perception of change is in agreement with conventional longitudinal evaluation of change in their HRQoL over the duration of their hospital stay. It also investigated this level of agreement after adjusting patient perceived change for recall bias that patients may have experienced. Methods: A prospective longitudinal cohort design nested within a larger randomised controlled trial was implemented. 103 hospitalised older adults participated in this investigation at a tertiary hospital facility. The EQ-5D utility and Visual Analogue Scale (VAS) scores were used to evaluate HRQoL. Participants completed EQ-5D reports as soon as they were medically stable (within three days of admission) then again immediately prior to discharge. Three methods of change score calculation were used (conventional change, patient perceived change and patient perceived change adjusted for recall bias). Agreement was primarily investigated using intraclass correlation coefficients (ICC) and limits of agreement. Results: Overall 101 (98%) participants completed both admission and discharge assessments. The mean (SD) age was 73.3 (11.2). The median (IQR) length of stay was 38 (20-60) days. For agreement between conventional longitudinal change and patient perceived change: ICCs were 0.34 and 0.40 for EQ-5D utility and VAS respectively. For agreement between conventional longitudinal change and patient perceived change adjusted for recall bias: ICCs were 0.98 and 0.90 respectively. Discrepancy between conventional longitudinal change and patient perceived change was considered clinically meaningful for 84 (83.2%) of participants, after adjusting for recall bias this reduced to 8 (7.9%). Conclusions: Agreement between conventional change and patient perceived change was not strong. A large proportion of this disagreement could be attributed to recall bias. To overcome the invalidating effect of response shift (on conventional change) and recall bias (on patient perceived change) a method of adjusting patient perceived change for recall bias has been described.

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Objective: To identify agreement levels between conventional longitudinal evaluation of change (post–pre) and patient-perceived change (post–then test) in health-related quality of life. Design: A prospective cohort investigation with two assessment points (baseline and six-month follow-up) was implemented. Setting: Community rehabilitation setting. Subjects: Frail older adults accessing community-based rehabilitation services. Intervention: Nil as part of this investigation. Main measures: Conventional longitudinal change in health-related quality of life was considered the difference between standard EQ-5D assessments completed at baseline and follow-up. To evaluate patient-perceived change a ‘then test’ was also completed at the follow-up assessment. This required participants to report (from their current perspective) how they believe their health-related quality of life was at baseline (using the EQ-5D). Patient-perceived change was considered the difference between ‘then test’ and standard follow-up EQ-5D assessments. Results: The mean (SD) age of participants was 78.8 (7.3). Of the 70 participants 62 (89%) of data sets were complete and included in analysis. Agreement between conventional (post–pre) and patient-perceived (post–then test) change was low to moderate (EQ-5D utility intraclass correlation coefficient (ICC)¼0.41, EQ-5D visual analogue scale (VAS) ICC¼0.21). Neither approach inferred greater change than the other (utility P¼0.925, VAS P¼0.506). Mean (95% confidence interval (CI)) conventional change in EQ-5D utility and VAS were 0.140 (0.045,0.236) and 8.8 (3.3,14.3) respectively, while patient-perceived change was 0.147 (0.055,0.238) and 6.4 (1.7,11.1) respectively. Conclusions: Substantial disagreement exists between conventional longitudinal evaluation of change in health-related quality of life and patient-perceived change in health-related quality of life (as measured using a then test) within individuals.

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The purpose of this research is to report preliminary empirical evidence regarding the association between common physical performance measures and health-related quality of life (HRQoL) of hospitalized older adults recovering from illness and injury. Frequently, these patients do not return to premorbid levels of independence and physical ability. Rehabilitation for this population often focuses on improving physical functioning and mobility with the intention of maximizing their HRQoL for discharge and thereafter. For this reason, longitudinal use of physical performance measures as an indicator of improvement in physical functioning (and thus HRQoL) is common. Although this is a logical approach, there have been mixed results from previous investigations into the association between common measures of physical function and HRQoL amongst other adult patient populations.1,2 There has been no previous investigation reporting the association between HRQoL and a variety of common physical performance measures in hospitalized older adults.