648 resultados para quality indicator
em Queensland University of Technology - ePrints Archive
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In their paper Lindberg and Ludvigsen (2012) have correctly identified the lack of evidence-based nurse-sensitive indicators measuring the quality of haemodialysis nursing care. The authors suggest that the intradialytic ultrafiltration rate (UFR) (total fluid removed divided by the total time in a single dialysis treatment, measured in litres per hour) may be one such indicator. Importantly it is best practice to minimise high UFRs as they are associated with higher risk of cardiovascular events and vascular access complications (Curatola et al., 2011). However, this does not justify UFR to qualify as a nurse-sensitive indicator of quality in the haemodialysis context. The aim of this response is to voice our concerns over the proposal to use haemodialysis treatment UFR as a haemodialysis nurse-sensitive quality indicator...
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To undertake exploratory benchmarking of a set of clinical indicators of quality care in residential care in Australia, data were collected from 107 residents within four medium-sized facilities (40–80 beds) in Brisbane, Australia. The proportion of residents in each sample facility with a particular clinical problem was compared with US Minimum Data Set quality indicator thresholds. Results demonstrated variability within and between clinical indicators, suggesting breadth of assessment using various clinical indicators of quality is an important factor when monitoring quality of care. More comprehensive and objective measures of quality of care would be of great assistance in determining and monitoring the effectiveness of residential aged care provision in Australia, particularly as demands for accountability by consumers and their families increase. What is known about the topic? The key to quality improvement is effective quality assessment, and one means of evaluating quality of care is through clinical outcomes. The Minimum Data Set quality indicators have been credited with improving quality in United States nursing homes. What does this paper add? The Clinical Care Indicators Tool was used to collect data on clinical outcomes, enabling comparison of data from a small Australian sample with American quality benchmarks to illustrate the utility of providing guidelines for interpretation. What are the implications for practitioners? Collecting and comparing clinical outcome data would enable practitioners to better understand the quality of care being provided and whether practices required review. The Clinical Care Indicator Tool could provide a comprehensive and systematic means of doing this, thus filling a gap in quality monitoring within Australian residential aged care.
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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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Background: In response to the need for more comprehensive quality assessment within Australian residential aged care facilities, the Clinical Care Indicator (CCI) Tool was developed to collect outcome data as a means of making inferences about quality. A national trial of its effectiveness and a Brisbane-based trial of its use within the quality improvement context determined the CCI Tool represented a potentially valuable addition to the Australian aged care system. This document describes the next phase in the CCI Tool.s development; the aims of which were to establish validity and reliability of the CCI Tool, and to develop quality indicator thresholds (benchmarks) for use in Australia. The CCI Tool is now known as the ResCareQA (Residential Care Quality Assessment). Methods: The study aims were achieved through a combination of quantitative data analysis, and expert panel consultations using modified Delphi process. The expert panel consisted of experienced aged care clinicians, managers, and academics; they were initially consulted to determine face and content validity of the ResCareQA, and later to develop thresholds of quality. To analyse its psychometric properties, ResCareQA forms were completed for all residents (N=498) of nine aged care facilities throughout Queensland. Kappa statistics were used to assess inter-rater and test-retest reliability, and Cronbach.s alpha coefficient calculated to determine internal consistency. For concurrent validity, equivalent items on the ResCareQA and the Resident Classification Scales (RCS) were compared using Spearman.s rank order correlations, while discriminative validity was assessed using known-groups technique, comparing ResCareQA results between groups with differing care needs, as well as between male and female residents. Rank-ordered facility results for each clinical care indicator (CCI) were circulated to the panel; upper and lower thresholds for each CCI were nominated by panel members and refined through a Delphi process. These thresholds indicate excellent care at one extreme and questionable care at the other. Results: Minor modifications were made to the assessment, and it was renamed the ResCareQA. Agreement on its content was reached after two Delphi rounds; the final version contains 24 questions across four domains, enabling generation of 36 CCIs. Both test-retest and inter-rater reliability were sound with median kappa values of 0.74 (test-retest) and 0.91 (inter-rater); internal consistency was not as strong, with a Chronbach.s alpha of 0.46. Because the ResCareQA does not provide a single combined score, comparisons for concurrent validity were made with the RCS on an item by item basis, with most resultant correlations being quite low. Discriminative validity analyses, however, revealed highly significant differences in total number of CCIs between high care and low care groups (t199=10.77, p=0.000), while the differences between male and female residents were not significant (t414=0.56, p=0.58). Clinical outcomes varied both within and between facilities; agreed upper and lower thresholds were finalised after three Delphi rounds. Conclusions: The ResCareQA provides a comprehensive, easily administered means of monitoring quality in residential aged care facilities that can be reliably used on multiple occasions. The relatively modest internal consistency score was likely due to the multi-factorial nature of quality, and the absence of an aggregate result for the assessment. Measurement of concurrent validity proved difficult in the absence of a gold standard, but the sound discriminative validity results suggest that the ResCareQA has acceptable validity and could be confidently used as an indication of care quality within Australian residential aged care facilities. The thresholds, while preliminary due to small sample size, enable users to make judgements about quality within and between facilities. Thus it is recommended the ResCareQA be adopted for wider use.
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Objectives The objective of this study was to develop process quality indicators (PQIs) to support the improvement of care services for older people with cognitive impairment in emergency departments (ED). Methods A structured research approach was taken for the development of PQIs for the care of older people with cognitive impairment in EDs, including combining available evidence with expert opinion (phase 1), a field study (phase 2), and formal voting (phase 3). A systematic review of the literature identified ED processes targeting the specific care needs of older people with cognitive impairment. Existing relevant PQIs were also included. By integrating the scientific evidence and clinical expertise, new PQIs were drafted and, along with the existing PQIs, extensively discussed by an advisory panel. These indicators were field tested in eight hospitals using a cohort of older persons aged 70 years and older. After analysis of the field study data (indicator prevalence, variability across sites), in a second meeting, the advisory panel further defined the PQIs. The advisory panel formally voted for selection of those PQIs that were most appropriate for care evaluation. Results In addition to seven previously published PQIs relevant to the care of older persons, 15 new indicators were created. These 22 PQIs were then field tested. PQIs designed specifically for the older ED population with cognitive impairment were only scored for patients with identified cognitive impairment. Following formal voting, a total of 11 PQIs were included in the set. These PQIs targeted cognitive screening, delirium screening, delirium risk assessment, evaluation of acute change in mental status, delirium etiology, proxy notification, collateral history, involvement of a nominated support person, pain assessment, postdischarge follow-up, and ED length of stay. Conclusions This article presents a set of PQIs for the evaluation of the care for older people with cognitive impairment in EDs. The variation in indicator triggering across different ED sites suggests that there are opportunities for quality improvement in care for this vulnerable group. Applied PQIs will identify an emergency services' implementation of care strategies for cognitively impaired older ED patients. Awareness of the PQI triggers at an ED level enables implementation of targeted interventions to improve any suboptimal processes of care. Further validation and utility of the indicators in a wider population is now indicated.
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Objectives The purpose of this study was to identify the structural quality of care domains and to establish a set of structural quality indicators (SQIs) for the assessment of care of older people with cognitive impairment in emergency departments (EDs). Methods A structured approach to SQI development was undertaken including: 1) a comprehensive search of peer-reviewed and gray literature focusing on identification of evidence-based interventions targeting structure of care of older patients with cognitive impairment and existing SQIs; 2) a consultative process engaging experts in the care of older people and epidemiologic methods (i.e., advisory panel) leading to development of a draft set of SQIs; 3) field testing of drafted SQIs in eight EDs, leading to refinement of the SQI set, and; 4) an independent voting process among the panelists for SQI inclusion in a final set, using preestablished inclusion and exclusion criteria. Results At the conclusion of the process, five SQIs targeting the management of older ED patients with cognitive impairment were developed: 1) the ED has a policy outlining the management of older people with cognitive impairment during the ED episode of care; 2) the ED has a policy outlining issues relevant to carers of older people with cognitive impairment, encompassing the need to include the (family) carer in the ED episode of care; 3) the ED has a policy outlining the assessment and management of behavioral symptoms, with specific reference to older people with cognitive impairment; 4) the ED has a policy outlining delirium prevention strategies, including the assessment of patients' delirium risk factors, and; 5) the ED has a policy outlining pain assessment and management for older people with cognitive impairment. Conclusions This article presents a set of SQIs for the evaluation of performance in caring for older people with cognitive impairment in EDs.
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Purpose The purpose of this research is to examine the concept of “potential quality” – that is, a company's tangible search qualities (such as the physical servicescape and virtual servicescape) – within the context of the real‐estate industry in the USA. Design/methodology/approach This qualitative study collects data by conducting personal in‐depth interviews with 34 respondents who had been recent buyers or renters of property. The data are then coded and themed to identify quality dimensions relevant to this industry. Findings The results indicate that a buyer's perception of the overall service quality of real‐estate service consists of two components: the interaction with a realtor (process quality); and the virtual servicescape, especially the firm's website design and content (potential quality). The study concludes that existing scales (such as SERVQUAL and RESERV) fail to capture the tangible component of service quality sufficiently in the real‐estate industry. Research limitations/implications The study uses data from only one industry (real estate) and from only one demographic segment (professionals in higher education). Practical implications Service providers of intangible, high‐contact services must appreciate the importance of the virtual servicescape as a surrogate quality indicator that can help to reduce information asymmetries and consumers' uncertainty with regard to initiating a business relationship. Real estate firms need to pay attention to the training of agents and the design and content of their e‐service systems. Originality/value This study integrates potential quality, process quality, and outcome quality in a comprehensive proposed model. In particular, the study identifies “potential quality” as a combination of the attributes of the virtual service environment and the physical service environment.
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Until now health impact assessment and environmental impact assessment are two different issues, often not addressed together. Both issues have to be dealt with for sustainable building. The aim of this paper is to link healthy and sustainable housing in life cycle assessment. Two strategies are studied: clean air as a functional unity and health as a quality indicator. The strategies are illustrated with an example on the basis of Eco-Quantum, which is a Dutch whole-building assessment tool. It turns out that both strategies do not conflict with the LCA methodology. The LCA methodology has to be refined for this purpose.
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A low-cost test bed was made from a modified heavy vehicle (HV) brake tester. By rotating a test HV’s wheel on an eccentric roller, a known vibration was imparted to the wheel under test. A control case for dampers in good condition was compared with two test cases of ineffective shock absorbers. Measurement of the forces at the bearings of the roller provided an indication of the HV wheel-forces. Where the level of serviceability of the shock absorbers varied, differences in wheel load provided a quality indicator corresponding to a change of damper characteristic. Conclusions regarding the levels of damper maintenance beyond which HV suspensions cause road damage and dynamic wheel forces at the threshold of tyre wear at which HV shock absorbers are normally replaced are presented.
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The paper provides an assessment of the performance of commercial Real Time Kinematic (RTK) systems over longer than recommended inter-station distances. The experiments were set up to test and analyse solutions from the i-MAX, MAX and VRS systems being operated with three triangle shaped network cells, each having an average inter-station distance of 69km, 118km and 166km. The performance characteristics appraised included initialization success rate, initialization time, RTK position accuracy and availability, ambiguity resolution risk and RTK integrity risk in order to provide a wider perspective of the performance of the testing systems. ----- ----- The results showed that the performances of all network RTK solutions assessed were affected by the increase in the inter-station distances to similar degrees. The MAX solution achieved the highest initialization success rate of 96.6% on average, albeit with a longer initialisation time. Two VRS approaches achieved lower initialization success rate of 80% over the large triangle. In terms of RTK positioning accuracy after successful initialisation, the results indicated a good agreement between the actual error growth in both horizontal and vertical components and the accuracy specified in the RMS and part per million (ppm) values by the manufacturers. ----- ----- Additionally, the VRS approaches performed better than the MAX and i-MAX when being tested under the standard triangle network with a mean inter-station distance of 69km. However as the inter-station distance increases, the network RTK software may fail to generate VRS correction and then may turn to operate in the nearest single-base RTK (or RAW) mode. The position uncertainty reached beyond 2 meters occasionally, showing that the RTK rover software was using an incorrect ambiguity fixed solution to estimate the rover position rather than automatically dropping back to using an ambiguity float solution. Results identified that the risk of incorrectly resolving ambiguities reached 18%, 20%, 13% and 25% for i-MAX, MAX, Leica VRS and Trimble VRS respectively when operating over the large triangle network. Additionally, the Coordinate Quality indicator values given by the Leica GX1230 GG rover receiver tended to be over-optimistic and not functioning well with the identification of incorrectly fixed integer ambiguity solutions. In summary, this independent assessment has identified some problems and failures that can occur in all of the systems tested, especially when being pushed beyond the recommended limits. While such failures are expected, they can offer useful insights into where users should be wary and how manufacturers might improve their products. The results also demonstrate that integrity monitoring of RTK solutions is indeed necessary for precision applications, thus deserving serious attention from researchers and system providers.
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The study aimed to evaluate the suitability of Escherichia coli, enterococci and C. perfringens to assess the microbiological quality of roof harvested rainwater, and to assess whether the concentrations of these faecal indicators can be used to predict the presence or absence of specific zoonotic bacterial or protozoan pathogens. From a total of 100 samples tested, respectively 58%, 83% and 46% of samples were found to be positive for E. coli, enterococci and C. perfringens spores, as determined by traditional culture based methods. Additionally, in the samples tested, 7%, 19%, 1%, 8%, 17%, and 15% were PCR positive for A. hydrophila lip, C. coli ceuE, C. jejuni mapA, L. pneumophila mip, Salmonella invA, and G. lamblia β-giardin genes. However, none of the samples was positive for E. coli O157 LPS, VT1, VT2 and C. parvum COWP genes. The presence or absence of these potential pathogens did not correlate with any of the faecal indicator bacterial concentrations as determined by a binary logistic regression model. The roof-harvested rainwater samples tested in this study appear to be of poor microbiological quality and no significant correlation was found between the concentration of faecal indicators and pathogenic microorganisms. The use of faecal indicator bacteria raises questions regarding their reliability in assessing the microbiological quality of water and particularly their poor correlation with pathogenic microorganisms. The presence of one or more zoonotic pathogens suggests that the microbiological analysis of water should be performed, and appropriate treatment measures should be undertaken especially in tanks where the water is used for drinking.
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Microbial pollution in water periodically affects human health in Australia, particularly in times of drought and flood. There is an increasing need for the control of waterborn microbial pathogens. Methods, allowing the determination of the origin of faecal contamination in water, are generally referred to as Microbial Source Tracking (MST). Various approaches have been evaluated as indicatorsof microbial pathogens in water samples, including detection of different microorganisms and various host-specific markers. However, until today there have been no universal MST methods that could reliably determine the source (human or animal) of faecal contamination. Therefore, the use of multiple approaches is frequently advised. MST is currently recognised as a research tool, rather than something to be included in routine practices. The main focus of this research was to develop novel and universally applicable methods to meet the demands for MST methods in routine testing of water samples. Escherichia coli was chosen initially as the object organism for our studies as, historically and globally, it is the standard indicator of microbial contamination in water. In this thesis, three approaches are described: single nucleotide polymorphism (SNP) genotyping, clustered regularly interspaced short palindromic repeats (CRISPR) screening using high resolution melt analysis (HRMA) methods and phage detection development based on CRISPR types. The advantage of the combination SNP genotyping and CRISPR genes has been discussed in this study. For the first time, a highly discriminatory single nucleotide polymorphism interrogation of E. coli population was applied to identify the host-specific cluster. Six human and one animal-specific SNP profile were revealed. SNP genotyping was successfully applied in the field investigations of the Coomera watershed, South-East Queensland, Australia. Four human profiles [11], [29], [32] and [45] and animal specific SNP profile [7] were detected in water. Two human-specific profiles [29] and [11] were found to be prevalent in the samples over a time period of years. The rainfall (24 and 72 hours), tide height and time, general land use (rural, suburban), seasons, distance from the river mouth and salinity show a lack of relashionship with the diversity of SNP profiles present in the Coomera watershed (p values > 0.05). Nevertheless, SNP genotyping method is able to identify and distinquish between human- and non-human specific E. coli isolates in water sources within one day. In some samples, only mixed profiles were detected. To further investigate host-specificity in these mixed profiles CRISPR screening protocol was developed, to be used on the set of E. coli, previously analysed for SNP profiles. CRISPR loci, which are the pattern of previous DNA coliphages attacks, were considered to be a promising tool for detecting host-specific markers in E. coli. Spacers in CRISPR loci could also reveal the dynamics of virulence in E. coli as well in other pathogens in water. Despite the fact that host-specificity was not observed in the set of E. coli analysed, CRISPR alleles were shown to be useful in detection of the geographical site of sources. HRMA allows determination of ‘different’ and ‘same’ CRISPR alleles and can be introduced in water monitoring as a cost-effective and rapid method. Overall, we show that the identified human specific SNP profiles [11], [29], [32] and [45] can be useful as marker genotypes globally for identification of human faecal contamination in water. Developed in the current study, the SNP typing approach can be used in water monitoring laboratories as an inexpensive, high-throughput and easy adapted protocol. The unique approach based on E. coli spacers for the search for unknown phage was developed to examine the host-specifity in phage sequences. Preliminary experiments on the recombinant plasmids showed the possibility of using this method for recovering phage sequences. Future studies will determine the host-specificity of DNA phage genotyping as soon as first reliable sequences can be acquired. No doubt, only implication of multiple approaches in MST will allow identification of the character of microbial contamination with higher confidence and readability.
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The quality of office indoor environments is considered to consist of those factors that impact the occupants according to their health and well-being and (by consequence) their productivity. Indoor Environment Quality (IEQ) can be characterized by four indicators: • Indoor air quality indicators • Thermal comfort indicators • Lighting indicators • Noise indicators. Within each indicator, there are specific metrics that can be utilized in determining an acceptable quality of an indoor environment based on existing knowledge and best practice. Examples of these metrics are: indoor air levels of pollutants or odorants; operative temperature and its control; radiant asymmetry; task lighting; glare; ambient noise. The way in which these metrics impact occupants is not fully understood, especially when multiple metrics may interact in their impacts. It can be estimated that the potential cost of lost productivity from poor IEQ may be much in excess of other operating costs of a building. However, the relative productivity impacts of each of the four indicators is largely unknown. The CRC Project ‘Regenerating Construction to Enhance Sustainability’ has a focus on IEQ impacts before and after building refurbishment. This paper provides an overview of IEQ impacts and criteria and the implementation of a CRC project that is currently researching these factors during the refurbishment of a Melbourne office building. IEQ measurements and their impacts will be reported in a future paper
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The quality of office indoor environments is considered to consist of those factors that impact occupants according to their health and well-being and (by consequence) their productivity. Indoor Environment Quality (IEQ) can be characterized by four indicators: • Indoor air quality indicators • Thermal comfort indicators • Lighting indicators • Noise indicators. Within each indicator, there are specific metrics that can be utilized in determining an acceptable quality of an indoor environment based on existing knowledge and best practice. Examples of these metrics are: indoor air levels of pollutants or odorants; operative temperature and its control; radiant asymmetry; task lighting; glare; ambient noise. The way in which these metrics impact occupants is not fully understood, especially when multiple metrics may interact in their impacts. While the potential cost of lost productivity from poor IEQ has been estimated to exceed building operation costs, the level of impact and the relative significance of the above four indicators are largely unknown. However, they are key factors in the sustainable operation or refurbishment of office buildings. This paper presents a methodology for assessing indoor environment quality (IEQ) in office buildings, and indicators with related metrics for high performance and occupant comfort. These are intended for integration into the specification of sustainable office buildings as key factors to ensure a high degree of occupant habitability, without this being impaired by other sustainability factors. The assessment methodology was applied in a case study on IEQ in Australia’s first ‘six star’ sustainable office building, Council House 2 (CH2), located in the centre of Melbourne. The CH2 building was designed and built with specific focus on sustainability and the provision of a high quality indoor environment for occupants. Actual IEQ performance was assessed in this study by field assessment after construction and occupancy. For comparison, the methodology was applied to a 30 year old conventional building adjacent to CH2 which housed the same or similar occupants and activities. The impact of IEQ on occupant productivity will be reported in a separate future paper
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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.