3 research outputs found

    Ranking of Fuzzy Similar Faces Using Relevance Matrix and Aggregation Operators

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    AbstractIn perception based imaging, Sketching With Words (SWW) is a well-established methodology in which the objects of computation are fuzzy geometric objects (f-objects).The problem of facial imaging of criminal on the basis of onlooker statement is not lack of method and measures but the modeling of onlooker(s) mind set. Because the onlooker has to give statements about different human face parts like forehead, eyes, nose, and chin etc.The concept of fuzzy similarity (f-similarity) and proper aggregation of components of face may provide more flexibility to onlooker(s). In proposed work onlooker(s) statement is recorded. Thereafter it is compared with existing statements. The f-similarity with different faces in database is estimated by using ‘as many as possible’ linguistic quantifier. Three types of constraints over size of parts of face ‘small’, ‘medium’, and ‘large’ are considered. Possibilistic constraints with linguistic hedges and negation operator like ‘very long’, ‘not long’, ‘not very long’ etc. are used. Moreover we have generated ranking of alike faces in decreasing order by using the concepts of f-similarity and relevance matrix

    Feedback preferences of patients, professionals and health insurers in integrated head and neck cancer care

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    Background: Audit and feedback on professional practice and health care outcomes are the most often used interventions to change behaviour of professionals and improve quality of health care. However, limited information is available regarding preferred feedback for patients, professionals and health insurers. Objective: Investigate the (differences in) preferences of receiving feedback between stakeholders, using the Dutch Head and Neck Audit as an example. Methods: A total of 37 patients, medical specialists, allied health professionals and health insurers were interviewed using semi-structured interviews. Questions focussed on: “Why,” “On what aspects” and “How” do you prefer to receive feedback on professional practice and health care outcomes?. Results: All stakeholders mentioned that feedback can improve health care by creating awareness, enabling self-reflection and reflection on peers or colleagues, and by benchmarking to others. Patients prefer feedback on the actual professional practice that matches the health care received, whereas medical specialists and health insurers are interested mainly in health care outcomes. All stakeholders largely prefer a bar graph. Patients prefer a pie chart for patient-reported outcomes and experiences, while Kaplan-Meier survival curves are preferred by medical specialists. Feedback should be simple with firstly an overview, and 1-4 times a year sent by e-mail. Finally, patients and health professionals are cautious with regard to transparency of audit data. Conclusions: This exploratory study shows how feedback preferences differ between stakeholders. Therefore, tailored reports are recommended. Using this information, effects of audit and feedback can be improved by adapting the feedback format and contents to the preferences of stakeholders

    Variation in Integrated Head and Neck Cancer Care: Impact of Patient and Hospital Characteristics

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    Background: Monitoring and effectively improving oncologic integrated care requires dashboard information based on quality registrations. The dashboard includes evidence-based quality indicators (QIs) that measure quality of care. This study aimed to assess the quality of current integrated head and neck cancer care with QIs, the variation between Dutch hospitals, and the influence of patient and hospital characteristics. Methods: Previously, 39 QIs were developed with input from medical specialists, allied health professionals, and patients’ perspectives. QI scores were calculated with data from 1,667 curatively treated patients in 8 hospitals. QIs with a sample size of >400 patients were included to calculate reliable QI scores. We used multilevel analysis to explain the variation. Results: Current care varied from 29% for the QI about a case manager being present to discuss the treatment plan to 100% for the QI about the availability of a treatment plan. Variation between hospitals was small for the QI about patients discussed in multidisciplinary team meetings (adherence: 95%, range 88%–98%), but large for the QI about malnutrition screening (adherence: 50%, range 2%–100%). Higher QI scores were associated with lower performance status, advanced tumor stage, and tumor in the oral cavity or oropharynx at the patient level, and with more curatively treated patients (volume) at hospital level. Conclusions: Although the quality registration was only recently launched, it already visualizes hospital variation in current care. Four determinants were found to be influential: tumor stage, performance status, tumor site, and volume. More data are needed to assure stable results for use in quality improvement
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