Basics of qualitative research: Grounded theory procedures and techniques

Acute kidney injury (AKI) is a complex disorder for which currently there is no accepted definition. Having a uniform standard for diagnosing and classifying AKI would enhance our ability to manage these patients. Future clinical and translational research in AKI will require collaborative networks of investigators drawn from various disciplines, dissemination of information via multidisciplinary joint conferences and publications, and improved translation of knowledge from pre-clinical research. We describe an initiative to develop uniform standards for defining and classifying AKI and to establish a forum for multidisciplinary interaction to improve care for patients with or at risk for AKI. Members representing key societies in critical care and nephrology along with additional experts in adult and pediatric AKI participated in a two day conference in Amsterdam, The Netherlands, in September 2005 and were assigned to one of three workgroups. Each group's discussions formed the basis for draft recommendations that were later refined and improved during discussion with the larger group. Dissenting opinions were also noted. The final draft recommendations were circulated to all participants and subsequently agreed upon as the consensus recommendations for this report. Participating societies endorsed the recommendations and agreed to help disseminate the results. The term AKI is proposed to represent the entire spectrum of acute renal failure. Diagnostic criteria for AKI are proposed based on acute alterations in serum creatinine or urine output. A staging system for AKI which reflects quantitative changes in serum creatinine and urine output has been developed. We describe the formation of a multidisciplinary collaborative network focused on AKI. We have proposed uniform standards for diagnosing and classifying AKI which will need to be validated in future studies. The Acute Kidney Injury Network offers a mechanism for proceeding with efforts to improve patient outcomes.

Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury

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Modern Applied Statistics With S

Truth and method

1. Type 1 diabetes (due to b-cell destruction, usually leading to absolute insulin deficiency) 2. Type 2 diabetes (due to a progressive insulin secretory defect on the background of insulin resistance) 3. Gestational diabetes mellitus (GDM) (diabetes diagnosed in the second or third trimester of pregnancy that is not clearly overt diabetes) 4. Specific types of diabetes due to other causes, e.g., monogenic diabetes syndromes (such as neonatal diabetes and maturity-onset diabetes of the young [MODY]), diseases of the exocrine pancreas (such as cystic fibrosis), and drugor chemical-induced diabetes (such as in the treatment of HIV/AIDS or after organ transplantation)

Classification and diagnosis of diabetes

A systematic review of pharmacological and non-pharmacological interventions for improving diabetes outcomes in people with severe mental illness

INTRODUCTION: Health systems responsiveness is a key objective of any health system, yet it is the least studied of all objectives particularly in low-income and middle-income countries. Research on health systems responsiveness highlights its multiple elements, for example, dignity and confidentiality. Little is known, however, about underlying theories of health systems responsiveness, and the mechanisms through which responsiveness works. This realist synthesis contributes to bridging these two knowledge gaps. METHODS AND ANALYSIS: In this realist synthesis, we will use a four-step process, comprising: mapping of theoretical bases, formulation of programme theories, theory refinement and testing of programme theories using literature and empirical data from Ghana and Vietnam. We will include theoretical and conceptual pieces, reviews, empirical studies and grey literature, alongside the primary data. We will explore responsiveness as entailing external and internal interactions within health systems. The search strategy will be purposive and iterative, with continuous screening and refinement of theories. Data extraction will be combined with quality appraisal, using appropriate tools. Each fragment of evidence will be appraised as it is being extracted, for its relevance to the emerging programme theories and methodological rigour. The extracted data pertaining to contexts, mechanisms and outcomes will be synthesised to identify patterns and contradictions. Results will be reported using narrative explanations, following established guidance on realist syntheses. ETHICS AND DISSEMINATION: Ethics approvals for the wider RESPONSE (Improving health systems responsiveness to neglected health needs of vulnerable groups in Ghana and Vietnam) study, of which this review is one part, were obtained from the ethics committees of the following institutions: London School of Hygiene and Tropical Medicine (ref: 22981), University of Leeds, School of Medicine (ref: MREC19-051), Ghana Health Service (ref: GHS-ERC 012/03/20) and Hanoi University of Public Health (ref: 020-149/DD-YTCC).We will disseminate results through academic papers, conference presentations and stakeholder workshops in Ghana and Vietnam. PROSPERO REGISTRATION NUMBER: CRD42020200353. Full record: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020200353.

https://bmjopen.bmj.com/content/bmjopen/11/6/e046992.full.pdf

Protocol for a realist synthesis of health systems responsiveness in low-income and middle-income countries.

In this chapter we will introduce you to the key mechanisms for summarizing the uncertainty in the outputs from cost effectiveness models; how to construct them and their strengths and weaknesses. Focus lies on probabilistic sensitivity analysis (PSA). Use of PSA ensures that the estimate of the Incremental Cost Effectiveness Ratio (ICER), and by extension the Net Benefit, is unbiased if the model is non-linear. PSA also enables us to characterise the uncertainty in the inputs to the model and thereby quantify the resulting uncertainty in the model outputs.

Outputs from Probabilistic Sensitivity Analysis


Purpose
This study aims to examine the extent to which “What Works” reviews in youth justice enable understanding of the features of effectiveness (what works, for whom, in what circumstances and why?) specified in the Effects–Mechanisms–Moderators–Implementation–Economic cost (EMMIE) framework.


Design/methodology/approach
The EMMIE framework examined findings within a sample of “What Works” style reviews of preventative youth justice intervention effectiveness.


Findings
“What Works” style reviews of evaluations of preventative youth justice interventions often omit the requisite details required to examine all of the necessary elements of effectiveness contained within the EMMIE framework. While effectiveness measures were typically provided, the dominant evaluation evidence-base struggles to consider moderators of effect, mechanisms of change, implementation differences and cost-effectiveness. Therefore, “What Works” samples cannot facilitate sufficient understanding of “what works for whom, in what circumstances and why?”. The authors argue that Realist Synthesis can fill this gap and shed light on the contexts that shape the mechanisms through which youth justice interventions work.


Originality/value
The authors extended the approach adopted by an earlier review of effectiveness reviews (Tompson et al., 2020), considering more recent reviews of the effectiveness of preventative interventions using the EMMIE framework. Unlike previous reviews, the authors prioritised the utility of the EMMIE framework for assessing the factors affecting the effectiveness of preventative interventions in youth justice.


https://figshare.com/articles/journal_contribution/Searching_for_context_a_review_of_what_works_reviews_of_interventions_to_prevent_youth_offending_using_the_EMMIE_Framework/21303402/1/files/37801038.pdf

Searching for context: a review of “what works” reviews of interventions to prevent youth offending using the EMMIE Framework

When we construct a decision model for cost effectiveness analysis, we are representing the flow of patients through a clinical pathway As patients flow through a pathway, represented by health states in our model, they will experience clinical events Clinical events are measured in real life by conducting clinical research or audit and are reported as health outcomes It is these health outcomes that are represented in our model by effectiveness parameters In this chapter we consider how these parameters can be incorporated into a model in a manner that captures the uncertainty in estimated effectiveness

Judy Wright

Papers

A systematic review of pharmacological and non-pharmacological interventions for improving diabetes outcomes in people with severe mental illness

Protocol for a realist synthesis of health systems responsiveness in low-income and middle-income countries.

Outputs from Probabilistic Sensitivity Analysis

Searching for context: a review of “what works” reviews of interventions to prevent youth offending using the EMMIE Framework

Probability Distributions for Effectiveness Parameters