114 resultados para Datasets in health


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PURPOSE: To develop a consensus opinion regarding capturing diagnosis-timing in coded hospital data. METHODS: As part of the World Health Organization International Classification of Diseases-11th Revision initiative, the Quality and Safety Topic Advisory Group is charged with enhancing the capture of quality and patient safety information in morbidity data sets. One such feature is a diagnosis-timing flag. The Group has undertaken a narrative literature review, scanned national experiences focusing on countries currently using timing flags, and held a series of meetings to derive formal recommendations regarding diagnosis-timing reporting. RESULTS: The completeness of diagnosis-timing reporting continues to improve with experience and use; studies indicate that it enhances risk-adjustment and may have a substantial impact on hospital performance estimates, especially for conditions/procedures that involve acutely ill patients. However, studies suggest that its reliability varies, is better for surgical than medical patients (kappa in hip fracture patients of 0.7-1.0 versus kappa in pneumonia of 0.2-0.6) and is dependent on coder training and setting. It may allow simpler and more precise specification of quality indicators. CONCLUSIONS: As the evidence indicates that a diagnosis-timing flag improves the ability of routinely collected, coded hospital data to support outcomes research and the development of quality and safety indicators, the Group recommends that a classification of 'arising after admission' (yes/no), with permitted designations of 'unknown or clinically undetermined', will facilitate coding while providing flexibility when there is uncertainty. Clear coding standards and guidelines with ongoing coder education will be necessary to ensure reliability of the diagnosis-timing flag.

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PURPOSE OF REVIEW: Current computational neuroanatomy based on MRI focuses on morphological measures of the brain. We present recent methodological developments in quantitative MRI (qMRI) that provide standardized measures of the brain, which go beyond morphology. We show how biophysical modelling of qMRI data can provide quantitative histological measures of brain tissue, leading to the emerging field of in-vivo histology using MRI (hMRI). RECENT FINDINGS: qMRI has greatly improved the sensitivity and specificity of computational neuroanatomy studies. qMRI metrics can also be used as direct indicators of the mechanisms driving observed morphological findings. For hMRI, biophysical models of the MRI signal are being developed to directly access histological information such as cortical myelination, axonal diameters or axonal g-ratio in white matter. Emerging results indicate promising prospects for the combined study of brain microstructure and function. SUMMARY: Non-invasive brain tissue characterization using qMRI or hMRI has significant implications for both research and clinics. Both approaches improve comparability across sites and time points, facilitating multicentre/longitudinal studies and standardized diagnostics. hMRI is expected to shed new light on the relationship between brain microstructure, function and behaviour, both in health and disease, and become an indispensable addition to computational neuroanatomy.

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With qualitative methods being increasingly used in health science fields, numerous grids proposing criteria to evaluate the quality of this type of research have been produced. Expert evaluators deem that there is a lack of consensual tools to evaluate qualitative research. Based on the review of 133 quality criteria grids for qualitative research in health sciences, the authors present the results of a computerized lexicometric analysis, which confirms the variety of intra- and inter-grid constructions, including within the same field. This variety is linked to the authors' paradigmatic references underlying the criteria proposed. These references seem to be built intuitively, reflecting internal representations of qualitative research, thus making the grids and their criteria hard to compare. Consequently, the consensus on the definitions and the number of criteria becomes problematic. The paradigmatic and theoretical references of the grids should be specified so that users could better assess their contributions and limitations.

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In the context of lay mobilization in health-related areas, this article addresses the role and activities of patients' associations in connection with organ donation, on the basis of interviews carried out with thirty members of transplant patients' associations in the French-speaking part of Switzerland. First, we describe the three main categories of activities conducted by these associations. While self-help and public awareness activities are predominant, policy-oriented actions are marginal. Then, we examine the factors likely to explain why these associations have a limited capacity to be active, especially in the public sphere. Such a lack of social visibility is all the more important in the current political context, characterized by the implementation of a national action plan designed to improve organ donation.

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BACKGROUND: Patient-centered care (PCC) has been recognized as a marker of quality in health service delivery. In policy documents, PCC is often used interchangeably with other models of care. There is a wide literature about PCC, but there is a lack of evidence about which model is the most appropriate for maternity services specifically. AIM: We sought to identify and critically appraise the literature to identify which definition of PCC is most relevant for maternity services. METHODS: The four-step approach used to identify definitions of PCC was to 1) search electronic databases using key terms (1995-2011), 2) cross-reference key papers, 3) search of specific journals, and 4) search the grey literature. Four papers and two books met our inclusion criteria. ANALYSIS: A four-criteria critical appraisal tool developed for the review was used to appraise the papers and books. MAIN RESULTS: From the six identified definitions, the Shaller's definition met the majority of the four criteria outlined and seems to be the most relevant to maternity services because it includes physiologic conditions as well as pathology, psychological aspects, a nonmedical approach to care, the greater involvement of family and friends, and strategies to implement PCC. CONCLUSION: This review highlights Shaller's definitions of PCC as the one that would be the most inclusive of all women using maternity services. Future research should concentrate on evaluating programs that support PCC in maternity services, and testing/validating this model of care.

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OBJECTIVE: To review and update the conceptual framework, indicator content and research priorities of the Organisation for Economic Cooperation and Development's (OECD) Health Care Quality Indicators (HCQI) project, after a decade of collaborative work. DESIGN: A structured assessment was carried out using a modified Delphi approach, followed by a consensus meeting, to assess the suite of HCQI for international comparisons, agree on revisions to the original framework and set priorities for research and development. SETTING: International group of countries participating to OECD projects. PARTICIPANTS: Members of the OECD HCQI expert group. RESULTS: A reference matrix, based on a revised performance framework, was used to map and assess all seventy HCQI routinely calculated by the OECD expert group. A total of 21 indicators were agreed to be excluded, due to the following concerns: (i) relevance, (ii) international comparability, particularly where heterogeneous coding practices might induce bias, (iii) feasibility, when the number of countries able to report was limited and the added value did not justify sustained effort and (iv) actionability, for indicators that were unlikely to improve on the basis of targeted policy interventions. CONCLUSIONS: The revised OECD framework for HCQI represents a new milestone of a long-standing international collaboration among a group of countries committed to building common ground for performance measurement. The expert group believes that the continuation of this work is paramount to provide decision makers with a validated toolbox to directly act on quality improvement strategies.

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Introduction. If we are to promote more patient-centred approaches in care delivery, we have to better characterize the situations in which being patient-centred is difficult to achieve. Data from professionals in health and social care are important because they are the people charged with operationalizing patient-centred care (PCC) in their daily practice. However, empirical accounts from frontline care providers are still lacking, and it is important to gather experiences not only from doctors but also from the other care providers. Indeed, experiences from different professions can help inform our understanding of patient care, which is expected to be both patient-centred and collaborative. Methods. This study was based on the following research question: What factors make the provision of PCC difficult to achieve? Sample and setting. A purposeful sampling technique was used, allowing for a series of choices about the participants and their professional affiliation. Because patient-centredness is the focus, 3 professions appeared to be of special interest: general internists, nurses and social workers. The study was undertaken in the General Internal Medicine Division of a teaching hospital located in a North American context. Data Collection. To answer the research question, a methodological approach based on a theory called phenomenology was chosen. Accordingly, semi-structured interviews were used since they generate understanding of the meanings different individuals have of their lived world. Interviews with 8 physicians, 10 nurses and 10 social workers were eventually conducted. Data analysis. An inductive thematic analysis was employed to make sense of the interview data. Results. The thematic analysis allowed identifying various types of challenges to PCC. Although most of the challenges were perceived by all three groups of professionals, they were perceived to a different degree across the professions, which likely reflected the scope of practice of each profession. The challenges and their distribution across the professions are illustrated in Table 1. Examples of challenges are provided in Table 2. Discussion. There is a tension between what is supposed to be done - what stands in the philosophy of patient -centredness - and what is currently done - the real life with all the challenges to PCC. According to some participants' accounts, PCC clearly risks becoming a mere illusion for health care professionals on which too great pressures are imposed.

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The World Health Organization (WHO) plans to submit the 11th revision of the International Classification of Diseases (ICD) to the World Health Assembly in 2018. The WHO is working toward a revised classification system that has an enhanced ability to capture health concepts in a manner that reflects current scientific evidence and that is compatible with contemporary information systems. In this paper, we present recommendations made to the WHO by the ICD revision's Quality and Safety Topic Advisory Group (Q&S TAG) for a new conceptual approach to capturing healthcare-related harms and injuries in ICD-coded data. The Q&S TAG has grouped causes of healthcare-related harm and injuries into four categories that relate to the source of the event: (a) medications and substances, (b) procedures, (c) devices and (d) other aspects of care. Under the proposed multiple coding approach, one of these sources of harm must be coded as part of a cluster of three codes to depict, respectively, a healthcare activity as a 'source' of harm, a 'mode or mechanism' of harm and a consequence of the event summarized by these codes (i.e. injury or harm). Use of this framework depends on the implementation of a new and potentially powerful code-clustering mechanism in ICD-11. This new framework for coding healthcare-related harm has great potential to improve the clinical detail of adverse event descriptions, and the overall quality of coded health data.