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This is the registration of a scoping review protocol titled, "Quality indicators to monitor, evaluate and improve the quality of rehabilitation care for older people: Scoping Review Protocol". There are no prior registrations. This scoping review aims to systematically identify and synthesis the evidence of existing international and national used quality indicators (QIs) and associated tools to measure QIs in the rehabilitation care of older people.

International audience; Dental caries management requires individualized follow-up and prophylaxis based on patients’ caries risk (PCR). In large pre-doctoral clinics, the use of institutional quality measures (QMs) is essential to control the quality of patient follow-up and to evaluate the need for improvement measures. The aim of this retrospective study was to evaluate the suitability of reusing student activity data for the development of QMs of caries risk. Two approaches for predicting PCR using student activity data were evaluated and compared. The first approach used the procedure codes recommended by the Dental Quality Alliance and the second used these same codes along with three educational codes. The sensitivity, specificity, overall accuracy of the two approaches were evaluated. A Receiver Operating Characteristic (ROC) curve analysis was carried out, and the areas under the ROC curve of the two approaches were compared using Delong’s test. A two-tailed P value ≤0.05 was considered statistically significant. While the two approaches were able to correctly predict PCR, the approach using both procedure and educational codes showed better predictive performance. The reuse of student activity data is an easy and robust method for the development of QMs of caries risk that can help improve monitoring and quality of patient care.

ObjectiveTo develop and test a new quality measure assessing timeliness of follow-up mental health care for youth presenting to the emergency department (ED) with suicidal ideation or self-harm.MethodsBased on a conceptual framework, evidence review, and a modified Delphi process, we developed a quality measure assessing whether youth 5 to 17 years old evaluated for suicidal ideation or self-harm in the ED and discharged to home had a follow-up mental health care visit within 7 days. The measure was tested in 4 geographically dispersed states (California, Pennsylvania, South Carolina, Tennessee) using Medicaid administrative data. We examined measure feasibility of implementation, variation, reliability, and validity. To test validity, adjusted regression models examined associations between quality measure scores and subsequent all-cause and same-cause hospital readmissions/ED return visits.ResultsOverall, there were 16,486 eligible ED visits between September 1, 2014 and July 31, 2016; 53.5% of eligible ED visits had an associated mental health care follow-up visit within 7 days. Measure scores varied by state, ranging from 26.3% to 66.5%, and by youth characteristics: visits by youth who were non-White, male, and living in an urban area were significantly less likely to be associated with a follow-up visit within 7 days. Better quality measure performance was not associated with decreased reutilization.ConclusionsThis new ED quality measure may be useful for monitoring and improving the quality of care for this vulnerable population; however, future work is needed to establish the measure's predictive validity using more prevalent outcomes such as recurrence of suicidal ideation or deliberate self-harm.

The performances of the automatic speaker verification (ASV) systems degrade due to the reduction in the amount of speech used for enrollment and verification. Combining multiple systems based on different features and classifiers considerably reduces speaker verification error rate with short utterances. This work attempts to incorporate supplementary information during the system combination process. We use quality of the estimated model parameters as supplementary information. We introduce a class of novel quality measures formulated using the zero-order sufficient statistics used during the i-vector extraction process. We have used the proposed quality measures as side information for combining ASV systems based on Gaussian mixture model-universal background model (GMM-UBM) and i-vector. The proposed methods demonstrate considerable improvement in speaker recognition performance on NIST SRE corpora, especially in short duration conditions. We have also observed improvement over existing systems based on different duration-based quality measures., Comment: Accepted for publication in Digital Signal Processing: A Review Journal

Objective The study was done to evaluate levels of missing and invalid values in the Michigan (MI) National Emergency Medical Services Information System (NEMSIS) (MI-EMSIS) and explore possible causes to inform improvement in data reporting and prehospital care quality. Methods We used a mixed-methods approach to study trends in data reporting. The proportion of missing or invalid values for 18 key reported variables in the MI-EMSIS (2010–2015) dataset was assessed overall, then stratified by EMS agency, software platform, and Medical Control Authorities (MCA)—regional EMS oversight entities in MI. We also conducted 4 focus groups and 10 key-informant interviews with EMS participants to understand the root causes of data missingness in MI-EMSIS. Results Only five variables of the 18 studied exhibited less than 10% missingness, and there was apparent variation in the rate of missingness across all stratifying variables under study. No consistent trends over time regarding the levels of missing or invalid values from 2010 to 2015 were identified. Qualitative findings indicated possible causes for this missingness including data-mapping issues, unclear variable definitions, and lack of infrastructure or training for data collection. Conclusions The adoption of electronic data collection in the prehospital setting can only support quality improvement if its entry is complete. The data suggest that there are many EMS agencies and MCAs with very high levels of missingness, and they do not appear to be improving over time, demonstrating a need for investment in efforts in improving data collection and reporting.

Classification is one of the main problems of machine learning, and assessing the quality of classification is one of the most topical tasks, all the more difficult as it depends on many factors. Many different measures have been proposed to assess the quality of the classification, often depending on the application of a specific classifier. However, in most cases, these measures are focused on binary classification, and for the problem of many decision classes, they are significantly simplified. Due to the increasing scope of classification applications, there is a growing need to select a classifier appropriate to the situation, including more complex data sets with multiple decision classes. This paper aims to propose a new measure of classifier quality assessment (called the preference-driven measure, abbreviated p-d), regardless of the number of classes, with the possibility of establishing the relative importance of each class. Furthermore, we propose a solution in which the classifier’s assessment can be adapted to the analyzed problem using a vector of preferences. To visualize the operation of the proposed measure, we present it first on an example involving two decision classes and then test its operation on real, multi-class data sets. Additionally, in this case, we demonstrate how to adjust the assessment to the user’s preferences. The results obtained allow us to confirm that the use of a preference-driven measure indicates that other classifiers are better to use according to preferences, particularly as opposed to the classical measures of classification quality assessment.

The European Colonoscopy Quality Investigation (ECQI) Group aims to raise awareness for improvement in colonoscopy standards across Europe. We analyzed data collected on a sample of procedures conducted across Europe to evaluate the achievement of the European Society of Gastrointestinal Endoscopy (ESGE) mean withdrawal time (WT) target. We also investigated factors associated with WT, in the hope of establishing areas that could lead to a quality improvement. Methods: 6445 form completions from 12 countries between 2 June 2016 and 30 April 2018 were considered for this analysis. We performed an exploratory analysis looking at WT according to the ESGE definition. Stepwise multivariable logistic regression analysis was conducted to determine the most influential associated factors after adjusting for the other pre-specified variables. Results: In 1150 qualifying colonoscopies, the mean WT was 7.8 min. Stepwise analysis, including 587 procedures where all inputs were known, found that the variables most associated with mean WT were a previous total colonoscopy in the last five years (p = 0.0011) and the time of day the colonoscopy was performed (p = 0.0192). The main factor associated with a WT < 6 min was the time of day that a colonoscopy was performed. Use of sedation was the main factor associated with a higher propor-tion of WT > 10 min, along with a previous colonoscopy. Conclusions: On average, the sample of European practice captured by the ECQI survey met the minimum standard set by the ESGE. How-ever, there was variation and potential for improvement. publishedVersion

In this note a new procedure to represent the quality measure for triangles is proposed. The triangles are identified by their three angles and are represented in a bounded domain, called angle representation region, according to the area co-ordinates, which are common and well known by finite element users. The developed representation can also be used in order to visualize the characteristics of any quality measure. This new procedure is extended to graphically represent triangular meshes in the angle representation region.

Visual quality evaluation is one of the challenging basic problems in image processing. It also plays a central role in the shaping, implementation, optimization, and testing of many methods. The existing image quality assessment methods focused on images corrupted by common degradation types while little attention was paid to color quantization. This in spite there is a wide range of applications requiring color quantization assessment being used as a preprocessing step when color-based tasks are more efficiently accomplished on a reduced number of colors. In this paper, we propose and carry-out a quantitative performance evaluation of nine well-known and commonly used full-reference image quality assessment measures. The evaluation is done by using two publicly available and subjectively rated image quality databases for color quantization degradation and by considering suitable combinations or subparts of them. The results indicate the quality measures that have closer performances in terms of their correlation to the subjective human rating and show that the evaluation of the statistical performance of the quality measures for color quantization is significantly impacted by the selected image quality database while maintaining a similar trend on each database. The detected strong similarity both on individual databases and on databases obtained by integration provides the ability to validate the integration process and to consider the quantitative performance evaluation on each database as an indicator for performance on the other databases. The experimental results are useful to address the choice of suitable quality measures for color quantization and to improve their future employment., Comment: Preprint

The use of quality measures to adjust health care payments and to rank providers is growing rapidly, but there are many problems with the quality measures that are currently being used. This article discusses some of these problems and then lays out some principles and procedures that should be used in the development and combination of quality measures. Many of the problems with existing quality measures would have been avoided had these principles been applied as they were developed.

Equivalent mutants are usually seen as an inconvenience in mutation analysis.We claim that equivalent mutants can be useful to detect and remove static anomalies.A process for detecting static anomalies is proposed.The process is based on mutation, equivalence checking, and quality measurement.The process is applicable to different kinds of software artifacts. Context: In mutation analysis, a mutant of a software artifact, either a program or a model, is said equivalent if it leaves the artifact meaning unchanged. Equivalent mutants are usually seen as an inconvenience and they reduce the applicability of mutation analysis.Objective: Instead, we here claim that equivalent mutants can be useful to define, detect, and remove static anomalies, i.e., deficiencies of given qualities: If an equivalent mutant has a better quality value than the original artifact, then an anomaly has been found and removed.Method: We present a process for detecting static anomalies based on mutation, equivalence checking, and quality measurement.Results: Our proposal and the originating technique are applicable to different kinds of software artifacts. We present anomalies and conduct several experiments in different contexts, at specification, design, and implementation level.Conclusion: We claim that in mutation analysis a new research direction should be followed, in which equivalent mutants and operators generating them are welcome.

In automotive industry, market demands shorter life cycles and individualized products. For manual assembly, this trend leads to more frequent planning of an ever increasing number of process variants. In order to ensure planning quality, virtual verification of manual production is crucial for efficient process optimization. However, virtual verification is not established in practice because available simulation tools require prohibitive manual modeling effort for human motions of acceptable quality. For automating the modeling process, data driven motion synthesis approaches are promising candidates that –however– require high quality input data for acceptable synthesis results. Therefore, objective motion capture data quality measures for data driven human motion synthesis are sought. This work proposes and tests a principal component analysis (PCA) and a Shannon entropy based quality measure. Both measures evaluate post-processed data and thus consider motion capture hardware in combination with a post-processing tool chain. The measures are tested for selectivity and validity using two low cost and two high cost motion capture systems. They differ in selectivity for high and low cost motion capture systems. Both measures correctly predict motion synthesis quality in tests with treadmill walking. Therefore, they can be employed for testing if a motion capture system is suitable for data driven motion synthesis that relies on PCA for input dimension reduction. Further research on robustness of the measures against motion variation is proposed.

Background: Triclustering has shown to be a valuable tool for the analysis of microarray data since its appearance as an improvement of classical clustering and biclustering techniques. The standard for validation of triclustering is based on three different measures: correlation, graphic similarity of the patterns and functional annotations for the genes extracted from the Gene Ontology project (GO). Results: We propose TRIQ, a single evaluation measure that combines the three measures previously described: correlation, graphic validation and functional annotation, providing a single value as result of the validation of a tricluster solution and therefore simplifying the steps inherent to research of comparison and selection of solutions. TRIQ has been applied to three datasets already studied and evaluated with single measures based on correlation, graphic similarity and GO terms. Triclusters have been extracted from this three datasets using two different algorithms: TriGen and OPTricluster. Conclusions: TRIQ has successfully provided the same results as a the three single evaluation measures. Furthermore, we have applied TRIQ to results from another algorithm, OPTRicluster, and we have shown how TRIQ has been a valid tool to compare results from different algorithms in a quantitative straightforward manner. Therefore, it appears as a valid measure to represent and summarize the quality of tricluster solutions. It is also feasible for evaluation of non biological triclusters, due to the parametrization of each component of TRIQ. Ministerio de Ciencia y Tecnología TIN2014-55894-C2-1-R

ObjectiveTo develop a longlist of healthcare quality indicators for the care of hospitalised adults of all ages with (or at risk of) low physical activity during the hospital stay.DesignA modified RAND/UCLA Appropriateness Method Delphi study.Setting and participantsParticipants were physical therapists, nurses and managers working in Dutch university medical centres.MethodsThe current study consisted of three phases. Phase I was a systematic literature search for quality indicators and relevant domains. Phase II was a survey among healthcare professionals to collect additional data. Phase III consisted of three consensus rounds. In round 1, experts rated the relevance of the potential indicators online (Delphi). The second round was a face-to-face expert panel meeting managed by an experienced moderator. Acceptability, feasibility and validity of the quality indicators were discussed by the panel members. In round 3, the panel members rated the relevance of the potential indicators that were still under discussion.ResultsThe search retrieved 1556 studies of which 53 studies were assessed full text. Data from 17 studies were included in a first draft longlist of indicators. Eighteen nurses and one physical therapist responded to the survey and added data for a second draft of the longlist. Experts constructed the final longlist of 23 indicators in three consensus rounds. Seven domains were identified: ‘Policy’, ‘Attitude and education’, ‘Equipment and support’, ‘Evaluation’, ‘Information’, ‘Patient-tailored physical activity plan’ and ‘Outcome measure’.Conclusion and implicationsThe healthcare quality indicators developed in this study could help to grade, monitor and improve healthcare for hospitalised adults of all ages with (or at risk of) low physical activity during the hospital stay. Future research will focus on the psychometric quality of the indicators and selection of key performance indicators.

Methodologies for defining standard quality indicators are important to assess service quality in public transport. The article proposes a method to integrate EU service quality standards in the transport planning process. It also investigates the effects of a set of large-scale transport policies in Campania region, Italy, in terms of service quality and ridership variations. Results of 10 years-long transport policies (€3,115 million invested) shows an impressive increase in both service quality and ridership. The article also compares perceived and measured service quality indicators for a new high quality metro line. Results point to new perspectives in modelling users’ travel behavior and related quality measures.

Three-dimensional (3D) videos are becoming popular not only in commercial cinemas but also home entertainment systems, such as TVs, DVDs, Blu-ray and games. Because of the radical development of 3DTV technologies, the broadcasting of high-definition 3D videos is in great demand which is growing rapidly in the mass consumer market. In spite of increasing consumer interest, poor quality, cross-talk or side effects and visual quality degradation due to packet loss during transmission has hampered the advancement of 3D visualization. Determining the impacts of transmission losses and assessing the quality of distorted 3D videos are crucial for the design and arrangement of advanced immersive media distribution platforms, a topic which is at the centre of this work. The impacts of network errors and their concealment in 2D videos ensured that error-resilient video transmission was widely discussed in the past. However, the scenario is different for 3D videos as distortions in one or both views are perceived quite differently and create detrimental effects which lead to binocular rivalry. This strongly degrades the Quality of Experience (QoE) as it produces visual discomfort which can cause visual fatigue, eye strain, headaches and nausea. Since the Human Visual System (HVS) is more sensitive to 3D perceptions, the impacts of transmission errors, such as delays or packet losses, need to be carefully analyzed, with proper error concealment methods and their effects on a viewer’s perception needing to be defined. In this dissertation, the main focus is ensuring error-resilient video communication and increasing the opportunity to more effectively fuse 3D video content in order to improve the overall QoE of users. A key contribution of this work is the decision to assess the success of all proposed techniques using formal subjective testing. The first effort to address these challenges was to review state-of-the-art 3D error concealment strategies and propose a low-complexity frame-loss concealment method for a video decoder. Subjective testing of common 3D video sequences demonstrated the proposed methods’ efficiency for stereoscopic video error concealment in terms of visual comfort and video quality. Various statistical comparisons with previously proposed methods were performed to define this technique’s significance in terms of its full frame-loss concealment and feasibility for real-time video transmission applications. Binocular rivalry is a visual phenomenon that has been the subject of intensive investigations of stereo visual perception for many years. The next part of this study is to attempt to quantify the detrimental effects of binocular rivalry. Existing approaches, in which one or more frames or macroblocks are lost in one or both views because of packet losses during transmission, were applied for error concealment. Then, standard numbers of subjects were engaged in subjective testing on common error concealed 3D video sequences. The evaluations provided by these subjects were then combined and analyzed using a standard student t-test which allowed the impact of binocular rivalry to be compared with that of monocular viewing. Finally, based on the criteria of the human visual system (HVS) and the impact of binocular rivalry, novel Quality Assessment (QA) metrics for quantifying the perceived quality of transmitted and degraded stereoscopic videos were proposed. The extracted features were accumulated according to the binocular suppression theory, with the disparity index modelled by taking into account the similar features of stereo videos and edge masking employed to quantify the suppression of binocular vision and impairments due to packet losses in the network. Based on the evidence obtained by subjective evaluations, the psychovisual effect of binocular rivalry was integrated to improve the overall QA and the robustness of our approach to reflect human visual sensitivity in terms of stereo vision. This kind of distortion measure or impairment metric is useful for enabling an improved QA of a stereo video without the need for formal subjective evaluation tests.

This paper proposes a new criterion, called absolute transparency, to design control schemes applied to bilateral teleoperation of mobile robots with time-varying delay. The absolute transparency measures how and how fast the human operator and the remote system interact with each other through a teleoperation system. The absolute transparency of different control schemes is analyzed and tested through teleoperation experiments where a human operator drives a mobile robot and receives both visual and force feedback.

Participant d’un mouvement de rationalisation des organisations hospitalières, les démarches qualité s’attachent à donner une nouvelle place à cet acteur particulier qu’est le patient. Dans cet article nous cherchons à déceler les différentes figures du patient convoquées (usager, client, participant, expert), comment elles sont configurées par leurs articulations avec l’organisation de soins de santé. Les démarches qualité poussent les organisations de soins de santé à s’ouvrir vers cet acteur : à se déplier – se laisser questionner par (et pour) le patient – et à s’y (re)plier – se renfermer, y envelopper le patient. Nous faisons l’hypothèse que l’étude des figures textualisées du patient est une clé pour comprendre les mouvements de pli et de dépli à travers lesquels le patient et l’organisation sont reconfigurés ; les figures du patient poussent ainsi l’organisation à s’« espacer » différemment (Vasquez, 2009). Comment maintenir dès lors l’organisation à travers ces multiples reconfigurations (successives et simultanées) ? As part of the rationalization of healthcare organizations, total quality management seeks to give greater importance to one actor, namely the patient. In this paper, we seek to identify the various representations of the patient (user, customer, member, expert) and how they are configured in relation to the healthcare organization. Quality measures are forcing healthcare organizations to open up to this actor by unfolding themselves on behalf of and for the benefit of the patient and to then fold themselves up again, delimit their boundaries, and wrap up the patient. We propose that the study of the patient’s textualized representations is key to understanding the folding and unfolding processes through which the patient and the organization are reconfigured. We argue that the representations of the patient configure the organization in many different ways (Vasquez 2009). The key issue is how to maintain the organization through its multiple successive and concurrent reconfigurations.

Publication à la conférence Discovery Science 2016; International audience; From a molecule to the brain perception, olfaction is a complex phenomenon that remains to be fully understood in neuroscience. A challenge is to establish comprehensive rules between the physicochem-ical properties of the molecules (e.g., weight, atom counts) and specific and small subsets of olfactory qualities (e.g., fruity, woody). This problem is particularly difficult as the current knowledge states that molecular properties only account for 30% of the identity of an odor: predictive models are found lacking in providing universal rules. However, descriptive approaches enable to elicit local hypotheses, validated by domain experts, to understand the olfactory percept. Based on a new quality measure tailored for multi-labeled data with skewed distributions, our approach extracts the top-k unredundant subgroups interpreted as descriptive rules description → {subset of labels}. Our experiments on benchmark and olfaction datasets demonstrate the capabilities of our approach with direct applications for the perfume and flavor industries.

The quality of pan-sharpened image is usually quantified separately by various spectral and spatial quality measures mostly originating from image processing. This quantity and diversity of quality measures makes it quite difficult to rank different image fusion methods. A new Joint Quality Measure (JQM) is proposed which is based on the combination of two Structural SIMilarity (SSIM) indices (one for spectral quality and another one for spatial quality) allowing comparison of different methods using a sole measure. Quality assessment of four fusion methods: Component Substitution (CS), General Fusion Filtering (GFF), variant of GFF and ATWT (one of ARSIS implementations) is performed for IKONOS and WorldView-2 satellite optical remote sensing data. Experiments and results showed the superiority of the proposed JQM when compared with already known joint measure - Quality with No Reference (QNR) index. Moreover, the results are fully supported by a visual analysis of imagery.

In this paper, blind image separation is performed, exploiting the property of sparseness to represent images. A new sparse representation called forward difference method is proposed. It is known that most of the independent component analysis (ICA) basis functions, extracted from images are sparse and gives unreliable sparseness measure. In the proposed method, the image mixture is first transformed to sparse images. These images are divided into blocks and for each block the sparseness measure ε0 norm is applied. The block having the most sparseness is considered to determine the separation matrix. The efficiency of the proposed method is compared with other sparse representation functions.&nbsp

A Hierarchical Clustering Based Approach in Aspect Mining Clustering is a division of data into groups of similar objects. Aspect mining is a process that tries to identify crosscutting concerns in existing software systems. The goal is to refactor the existing systems to use aspect oriented programming, in order to make them easier to maintain and to evolve. The aim of this paper is to present a new hierarchical clustering based approach in aspect mining. For this purpose we propose HAC algorithm (Hierarchical Agglomerative Clustering in aspect mining). Clustering is used in order to identify crosscutting concerns. We evaluate the obtained results from the aspect mining point of view, based on two quality measures that we have previously introduced and a newly defined one. The proposed approach is compared with other similar existing approaches in aspect mining and two case studies are also reported.

Using our multi-user model, a community of users provides feedback in a pay-as-you-go fashion to the ontology matching process by validating the mappings found by automatic methods, with the following advantages over having a single user: the effort required from each user is reduced, user errors are corrected, and consensus is reached. We propose strategies that dynamically determine the order in which the candidate mappings are presented to the users for validation. These strategies are based on mapping quality measures that we define. Further, we use a propagation method to leverage the validation of one mapping to other mappings. We use an extension of the AgreementMaker ontology matching system and the Ontology Alignment Evaluation Initiative (OAEI) Benchmarks track to evaluate our approach. Our results show how Fmeasure and robustness vary as a function of the number of user validations. We consider different user error and revalidation rates (the latter measures the number of times that the same mapping is validated). Our results highlight complex trade-offs and point to the benefits of dynamically adjusting the revalidation rate.

We present a technique to extend Jacobian-based distortion (quality) measures for planar triangles to high-order isoparametric elements of any interpolation degree on CAD parameterized surfaces. The resulting distortion (quality) measures are expressed in terms of the parametric coordinates of the nodes. These extended distortion (quality) measures can be used to check the quality and validity of a high-order surface mesh. We also apply them to simultaneously smooth and untangle high-order surface meshes by minimizing the extended distortion measure. The minimization is performed in terms of the parametric coordinates of the nodes. Thus, the nodes always lie on the surface. Finally, we include several examples to illustrate the application of the proposed technique