972 resultados para Quality tools


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This research document is motivated by the need for a systemic, efficient quality improvement methodology at universities. There exists no methodology designed for a total quality management (TQM) program in a university. The main objective of this study is to develop a TQM Methodology that enables a university to efficiently develop an integral total quality improvement (TQM) Plan. ^ Current research focuses on the need of improving the quality of universities, the study of the perceived best quality universities, and the measurement of the quality of universities through rankings. There is no evidence of research on how to plan for an integral quality improvement initiative for the university as a whole, which is the main contribution of this study. ^ This research is built on various reference TQM models and criteria provided by ISO 9000, Baldrige and Six Sigma; and educational accreditation criteria found in ABET and SACS. The TQM methodology is proposed by following a seven-step metamethodology. The proposed methodology guides the user to develop a TQM plan in five sequential phases: initiation, assessment, analysis, preparation and acceptance. Each phase defines for the user its purpose, key activities, input requirements, controls, deliverables, and tools to use. The application of quality concepts in education and higher education is particular; since there are unique factors in education which ought to be considered. These factors shape the quality dimensions in a university and are the main inputs to the methodology. ^ The proposed TQM Methodology is used to guide the user to collect and transform appropriate inputs to a holistic TQM Plan, ready to be implemented by the university. Different input data will lead to a unique TQM plan for the specific university at the time. It may not necessarily transform the university into a world-class institution, but aims to strive for stakeholder-oriented improvements, leading to a better alignment with its mission and total quality advancement. ^ The proposed TQM methodology is validated in three steps. First, it is verified by going through a test activity as part of the meta-methodology. Secondly, the methodology is applied to a case university to develop a TQM plan. Lastly, the methodology and the TQM plan both are verified by an expert group consisting of TQM specialists and university administrators. The proposed TQM methodology is applicable to any university at all levels of advancement, regardless of changes in its long-term vision and short-term needs. It helps to assure the quality of a TQM plan, while making the process more systemic, efficient, and cost effective. This research establishes a framework with a solid foundation for extending the proposed TQM methodology into other industries. ^

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In the early 1980s many hotels in the United States adopted quality assurance as a business strategy. By the late 1980s independent and chain hotels realized that total quality management (TQM) was a more powerful process and they began utilizing many of its components. For over 10 years, hotels have flirted with a variety of tools, processes, and theories to improve service to the guest

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X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

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This dissertation contributes to the rapidly growing empirical research area in the field of operations management. It contains two essays, tackling two different sets of operations management questions which are motivated by and built on field data sets from two very different industries --- air cargo logistics and retailing.

The first essay, based on the data set obtained from a world leading third-party logistics company, develops a novel and general Bayesian hierarchical learning framework for estimating customers' spillover learning, that is, customers' learning about the quality of a service (or product) from their previous experiences with similar yet not identical services. We then apply our model to the data set to study how customers' experiences from shipping on a particular route affect their future decisions about shipping not only on that route, but also on other routes serviced by the same logistics company. We find that customers indeed borrow experiences from similar but different services to update their quality beliefs that determine future purchase decisions. Also, service quality beliefs have a significant impact on their future purchasing decisions. Moreover, customers are risk averse; they are averse to not only experience variability but also belief uncertainty (i.e., customer's uncertainty about their beliefs). Finally, belief uncertainty affects customers' utilities more compared to experience variability.

The second essay is based on a data set obtained from a large Chinese supermarket chain, which contains sales as well as both wholesale and retail prices of un-packaged perishable vegetables. Recognizing the special characteristics of this particularly product category, we develop a structural estimation model in a discrete-continuous choice model framework. Building on this framework, we then study an optimization model for joint pricing and inventory management strategies of multiple products, which aims at improving the company's profit from direct sales and at the same time reducing food waste and thus improving social welfare.

Collectively, the studies in this dissertation provide useful modeling ideas, decision tools, insights, and guidance for firms to utilize vast sales and operations data to devise more effective business strategies.

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Increases in the rate and extent of lakeshore development along inland lakes in Ontario are adversely impacting water quality. Despite growing awareness, there is a lack of knowledge about the land use policies and tools in place to protect inland lakes in rural Ontario. This research evaluated official plans for water quality protection policies for inland lakes in the County of Renfrew, Ontario to address this gap. The findings suggest that municipalities implicitly link water quality to land use planning policy and fail to incorporate innovative methods to protect water quality.

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This thesis presents details of the design and development of novel tools and instruments for scanning tunneling microscopy (STM), and may be considered as a repository for several years' worth of development work. The author presents design goals and implementations for two microscopes. First, a novel Pan-type STM was built that could be operated in an ambient environment as a liquid-phase STM. Unique features of this microscope include a unibody frame, for increased microscope rigidity, a novel slider component with large Z-range, a unique wiring scheme and damping mechanism, and a removable liquid cell. The microscope exhibits a high level of mechanical isolation at the tunnel junction, and operates excellently as an ambient tool. Experiments in liquid are on-going. Simultaneously, the author worked on designs for a novel low temperature, ultra-high vacuum (LT-UHV) instrument, and these are presented as well. A novel stick-slip vertical coarse approach motor was designed and built. To gauge the performance of the motor, an in situ motion sensing apparatus was implemented, which could measure the step size of the motor to high precision. A new driving circuit for stick-slip inertial motors is also presented, that o ffers improved performance over our previous driving circuit, at a fraction of the cost. The circuit was shown to increase step size performance by 25%. Finally, a horizontal sample stage was implemented in this microscope. The build of this UHV instrument is currently being fi nalized. In conjunction with the above design projects, the author was involved in a collaborative project characterizing N-heterocyclic carbene (NHC) self-assembled monolayers (SAMs) on Au(111) films. STM was used to characterize Au substrate quality, for both commercial substrates and those manufactured via a unique atomic layer deposition (ALD) process by collaborators. Ambient and UHV STM was then also used to characterize the NHC/Au(111) films themselves, and several key properties of these films are discussed. During this study, the author discovered an unexpected surface contaminant, and details of this are also presented. Finally, two models are presented for the nature of the NHC-Au(111) surface interaction based on the observed film properties, and some preliminary theoretical work by collaborators is presented.

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The volume of Audiovisual Translation (AVT) is increasing to meet the rising demand for data that needs to be accessible around the world. Machine Translation (MT) is one of the most innovative technologies to be deployed in the field of translation, but it is still too early to predict how it can support the creativity and productivity of professional translators in the future. Currently, MT is more widely used in (non-AV) text translation than in AVT. In this article, we discuss MT technology and demonstrate why its use in AVT scenarios is particularly challenging. We also present some potentially useful methods and tools for measuring MT quality that have been developed primarily for text translation. The ultimate objective is to bridge the gap between the tech-savvy AVT community, on the one hand, and researchers and developers in the field of high-quality MT, on the other.

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Rotational moulding is a method to produce hollow plastic articles. Heating is normally carried out by placing the mould into a hot air oven where the plastic material in the mould is heated. The most common cooling media are water and forced air. Due to the inefficient nature of conventional hot air ovens most of the energy supplied by the oven does not go to heat the plastic and as a consequence the procedure has very long cycle times. Direct oil heating is an effective alternative in order to achieve better energy efficiency and cycle times. This research work has combined this technology with new innovative design of mould, applying the advantages of electroforming and rapid prototyping. Complex cavity geometries are manufactured by electroforming from a rapid prototyping mandrel. The approach involves conformal heating and cooling channels , where the oil flows into a parallel channel to the electroformed cavity (nickel or copper). Because of this the mould enables high temperature uniformity with direct heating and cooling of the electroformed shell, Uniform heating and cooling is important not only for good quality parts but also for good uniform wall thickness distribution in the rotationally moulded part. The experimental work with the manufactured prototype mould has enabled analysis of the thermal uniformity in the cavity, under different temperatures. Copyright © 2008 by ASME.

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Les procédures appliquées avant l’abattage des animaux influencent directement la qualité de la viande en modulant l’état physiologique des porcs; ainsi, l’augmentation de la température corporelle, les taux élevés de lactate sanguin et l’épuisement des réserves de glycogène entre autres, occasionnent la majorité des baisses de qualité. L’objectif de cette thèse était de valider des outils indicateurs de stress porcin pour les fermes et les abattoirs. Ceux-ci seraient appliqués à la surveillance du bien-être animal et à la prédiction de variation de qualité de la viande porcine au niveau commercial. Premierement, les résultats de la thèse ont permis de conclure qu’un des outils développés (analyseur portatif de lactate) mesure la variation du niveau de lactate sanguin associé à l’état physiologique des porcs dans la phase péri-mortem et aide à expliquer la variation de la qualité de la viande chez le porc à l’abattoir, en particulier dans les muscles du jambon. Deuxièmement, les résultats des audits du bien-être animal appliqués de la ferme à l’abattoir ont démontré que la qualité du système d’élevage à la ferme d’origine et les compétences du chauffeur de camion sont d’importants critères affectant la réponse comportementale des porcs à la manipulation avant l’abattage. Ces résultats ont également démontré que les conditions de logement à la ferme (la faible densité et l’enrichissement dans les enclos), le comportement des porcs en période pré-abattage (glissade), ainsi que les interventions du manipulateur (utilisation du bâton électrique) dans la zone d’étourdissement de l’abattoir affectent négativement la variation de la qualité de la viande. L’application des protocoles d’audits dans la filière porcine a également démontré que le respect des critères de bien-être animal fixés par un outil de vérification est primordiale et permet de contrôler les conditions de bien-être des porcs à chaque étape de la période pré-abattage, de produire une viande de qualité supérieure et de réduire les pertes. Les audits de bien-être animal sont donc un outil qui apporte des resultats très pertinents pour aider a éviter les variations de la qualité de la viande chez le porc. Troisièmement, la thermographie infrarouge s’est avéré être une technique prometteuse permettant d’évaluer la variation de température corporelle de l’animal pendant et après un stress physique, en particulier lorsque cette mesure est prise derrière les oreilles. En conclusion, les outils validés à travers cette thèse représentent des méthodologies non invasives et potentiellement complémentaires à d’autres approches d’évaluation de l’état physiologique et du bien-être animal par rapport au stress, permettant de réduire les pertes de qualité de viande (par exemple en utilisation conjointe avec le niveau de lactate sanguin et les indicateurs de stress comportemental, entre autres).

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The complexity of issues surrounding continence management, have been investigated by a UK multi-disciplinary research team working under the project title Tackling Ageing Continence through Theory Tools and Technology (TACT3). The team comprising engineers, chemists, health researchers, designers and social anthropologists is funded by the New Dynamics of Ageing Programme, ‘a seven year multidisciplinary research initiative with the ultimate aim of improving quality of life of older people. The programme is a unique collaboration between five UK Research Councils , and is the largest and most ambitious research programme on ageing ever mounted in the UK’ (www.newdynamics.group.shef.ac.uk). The TACT3 project comprises four work packages that are individually managed by members of the research team. One work package focuses solely on knowledge transfer of the research outputs and the management of the overall project. Another work package, entitled ‘Challenging Environmental Barriers’ has focused on the barriers in the built environment that prevent older people with continence concerns from participating in wider social life, namely access to publicly available toilet facilities. We also have a work package entitled ‘Improving Continence Interventions and Services’ which is exploring patient, carer and service providers experiences in receiving and delivering National Health Service (NHS) continence management treatments. The fourth workpackage ‘Developing Assistive Technologies’ has worked with users to develop devices that promote confidence, improve health and therefore may facilitate greater social interaction for older people with continence management concerns.

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Thesis (Master's)--University of Washington, 2016-08

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Nervous system disorders are associated with cognitive and motor deficits, and are responsible for the highest disability rates and global burden of disease. Their recovery paths are vulnerable and dependent on the effective combination of plastic brain tissue properties, with complex, lengthy and expensive neurorehabilitation programs. This work explores two lines of research, envisioning sustainable solutions to improve treatment of cognitive and motor deficits. Both projects were developed in parallel and shared a new sensible approach, where low-cost technologies were integrated with common clinical operative procedures. The aim was to achieve more intensive treatments under specialized monitoring, improve clinical decision-making and increase access to healthcare. The first project (articles I – III) concerned the development and evaluation of a web-based cognitive training platform (COGWEB), suitable for intensive use, either at home or at institutions, and across a wide spectrum of ages and diseases that impair cognitive functioning. It was tested for usability in a memory clinic setting and implemented in a collaborative network, comprising 41 centers and 60 professionals. An adherence and intensity study revealed a compliance of 82.8% at six months and an average of six hours/week of continued online cognitive training activities. The second project (articles IV – VI) was designed to create and validate an intelligent rehabilitation device to administer proprioceptive stimuli on the hemiparetic side of stroke patients while performing ambulatory movement characterization (SWORD). Targeted vibratory stimulation was found to be well tolerated and an automatic motor characterization system retrieved results comparable to the first items of the Wolf Motor Function Test. The global system was tested in a randomized placebo controlled trial to assess its impact on a common motor rehabilitation task in a relevant clinical environment (early post-stroke). The number of correct movements on a hand-to-mouth task was increased by an average of 7.2/minute while the probability to perform an error decreased from 1:3 to 1:9. Neurorehabilitation and neuroplasticity are shifting to more neuroscience driven approaches. Simultaneously, their final utility for patients and society is largely dependent on the development of more effective technologies that facilitate the dissemination of knowledge produced during the process. The results attained through this work represent a step forward in that direction. Their impact on the quality of rehabilitation services and public health is discussed according to clinical, technological and organizational perspectives. Such a process of thinking and oriented speculation has led to the debate of subsequent hypotheses, already being explored in novel research paths.

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The machining of hardened steel is becoming increasingly important in manufacturing processes. Machined parts made with hardened steel are often subjected to high service demands, which require great resistance and quality. The machining of this material submits the tools to high mechanical and thermal loads, which increases the tool wear and affects the surface integrity of the part. In that context, this work presents a study of drilling of AISI P20 steel with carbide tools, analyzing the effects on the process caused by the reduction of cutting fluid supply and its relation with the tool wear and the surface integrity of the piece. The major problem observed in the tests was a difficulty for chips to flow through the drill flute, compromising their expulsion from the hole. After a careful analysis, a different machining strategy was adopted to solve the problem

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BACKGROUND: The identification of patients' health needs is pivotal in optimising the quality of health care, increasing patient satisfaction and directing resource allocation. Health needs are complex and not so easily evaluated as health-related quality of life (HRQL), which is becoming increasingly accepted as a means of providing a more global, patient-orientated assessment of the outcome of health care interventions than the simple medical model. The potential of HRQL as a surrogate measure of healthcare needs has not been evaluated. OBJECTIVES AND METHOD: A generic (Short Form-12; SF-12) and a disease-specific questionnaire (Seattle Angina Questionnaire; SAQ) were tested for their potential to predict health needs in patients with acute coronary disease. A wide range of healthcare needs were determined using a questionnaire specifically developed for this purpose. RESULTS: With the exception of information needs, healthcare needs were highly correlated with health-related quality of life. Patients with limited enjoyment of personal interests, weak financial situation, greater dependency on others to access health services, and dissatisfaction with accommodation reported poorer HRQL (SF-12: p < 0.001; SAQ: p < 0.01). Difficulties with mobility, aids to daily living and activities requiring assistance from someone else were strongly associated with both generic and disease-specific questionnaires (SF-12: r = 0.46-0.55, p < 0.01; SAQ: r = 0.53-0.65, p < 0.001). Variables relating to quality of care and health services were more highly correlated with SAQ components (r = 0.33-0.59) than with SF-12 (r = 0.07-0.33). Overall, the disease-specific Seattle Angina Questionnaire was superior to the generic Short Form-12 in detecting healthcare needs in patients with coronary disease. Receiver-operator curves supported the sensitivity of HRQL tools in detecting health needs. CONCLUSION: Healthcare needs are complex and developing suitable questionnaires to measure these is difficult and time-consuming. Without a satisfactory means of measuring these needs, the extent to which disease impacts on health will continue to be underestimated. Further investigation on larger populations is warranted but HRQL tools appear to be a reasonable proxy for healthcare needs, as they identify the majority of needs in patients with coronary disease, an observation not previously reported in this patient group

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OBJECTIVES: To assess satisfaction of survivors of coronary artery diseases (CAD) with healthcare services and to determine whether specific components of standard health-related quality of life (HRQL) assessment tools might identify areas of satisfaction and dissatisfaction. METHOD: A specific tool developed to provide a comprehensive assessment of healthcare needs was administered concomitantly with generic and specific HRQL instruments, on 242 patients with CAD, admitted to an acute coronary unit during a single year. RESULTS: 92.5% of patients confirmed their trust in and satisfaction with the care given by their General Practitioner; even so, one third experienced difficulty getting an appointment and a quarter wanted more time for each consultation or prompt referral to a specialist when needed. Around a third expressed dissatisfaction with advice from the practice nurse or hospital consultant. Overall 54% were highly satisfied with services, 33% moderately satisfied and 13% dissatisfied.Cronbach's alpha was 0.87; the corrected total-item correlation ranged between 0.55-0.75, with trivial 'floor' score and low 'ceiling' effect. Several domains in all three HRQL tools correlated with items relating to satisfaction. The Seattle Angina Questionnaire Treatment Score correlated significantly with all satisfaction items and with the global satisfaction score. CONCLUSION: Cardiac patients' demanded better services and advice from, and more time with, health professionals and easier surgery access. The satisfaction tool showed acceptable psychometric properties. In this patient group, disease-specific HRQL tools seem more appropriate than generic tools for surveys of patient satisfaction