Genomic epidemiology of third-generation cephalosporin-resistant Escherichia coli from Argentinian pig and dairy farms reveals animal-specific patterns of co-resistance and resistance mechanisms.

Control measures are being introduced globally to reduce the prevalence of antibiotic resistance (ABR) in bacteria on farms. However, little is known about the current prevalence and molecular ecology of ABR in bacterial species with the potential to be key opportunistic human pathogens, such as Escherichia coli, on South American farms. Working with 30 dairy cattle farms and 40 pig farms across two provinces in central-eastern Argentina, we report a comprehensive genomic analysis of third-generation cephalosporin-resistant (3GC-R) E. coli, which were recovered from 34.8% (cattle) and 47.8% (pigs) of samples from fecally contaminated sites. Phylogenetic analysis revealed substantial diversity suggestive of long-term horizontal and vertical transmission of 3GC-R mechanisms. CTX-M-15 and CTX-M-2 were more often produced by isolates from dairy farms, while CTX-M-8 and CMY-2 and co-carriage of amoxicillin/clavulanate resistance and florfenicol resistance were more common in isolates from pig farms. This suggests different selective pressures for antibiotic use in these two animal types. We identified the ß-lactamase gene blaROB, which has previously only been reported in the family Pasteurellaceae, in 3GC-R E. coli. blaROB was found alongside a novel florfenicol resistance gene, ydhC, also mobilized from a pig pathogen as part of a new composite transposon. As the first comprehensive genomic survey of 3GC-R E. coli in Argentina, these data set a baseline from which to measure the effects of interventions aimed at reducing on-farm ABR and provide an opportunity to investigate the zoonotic transmission of resistant bacteria in this region. IMPORTANCE: Little is known about the ecology of critically important antibiotic resistance among bacteria with the potential to be opportunistic human pathogens (e.g., Escherichia coli) on South American farms. By studying 70 pig and dairy cattle farms in central-eastern Argentina, we identified that third-generation cephalosporin resistance (3GC-R) in E. coli was mediated by mechanisms seen more often in certain species and that 3GC-R pig E. coli were more likely to be co-resistant to florfenicol and amoxicillin/clavulanate. This suggests that on-farm antibiotic usage is key to selecting the types of E. coli present on these farms. 3GC-R E. coli and 3GC-R plasmids were diverse, suggestive of long-term circulation in this region. We identified the de novo mobilization of the resistance gene blaROB from pig pathogens into E. coli on a novel mobile genetic element, which shows the importance of surveying poorly studied regions for antibiotic resistance that might impact human health.

Steering by their own lights: Why regulators across Europe use different indicators to measure healthcare quality.

Despite widespread faith that quality indicators are key to healthcare improvement and regulation, surprisingly little is known about what is actually measured in different countries, nor how, nor why. To address that gap, this article compares the official indicator sets--comprising some 1100 quality measures-- used by statutory hospital regulators in England, Germany, France, and the Netherlands. The findings demonstrate that those countries' regulators strike very different balances in: the dimensions of quality they assess (e.g. between safety, effectiveness, and patient-centredness); the hospital activities they target (e.g. between clinical and non-clinical activities and management); and the 'Donabedian' measurement style of their indicators (between structure, process and outcome indicators). We argue that these contrasts reflect: i) how the distinctive problems facing each country's healthcare system create different 'demand-side' pressures on what national indicator sets measure; and ii) how the configuration of national healthcare systems and governance traditions create 'supply-side' constraints on the kinds of data that regulators can use for indicator construction. Our analysis suggests fundamental differences in the meaning of quality and its measurement across countries that are likely to impede international efforts to benchmark quality and identify best practice.

Intelligent Monitoring? Assessing the ability of the Care Quality Commission's statistical surveillance tool to predict quality and prioritise NHS hospital inspections.

BACKGROUND: The Care Quality Commission (CQC) is responsible for ensuring the quality of the health and social care delivered by more than 30 000 registered providers in England. With only limited resources for conducting on-site inspections, the CQC has used statistical surveillance tools to help it identify which providers it should prioritise for inspection. In the face of planned funding cuts, the CQC plans to put more reliance on statistical surveillance tools to assess risks to quality and prioritise inspections accordingly. OBJECTIVE: To evaluate the ability of the CQC's latest surveillance tool, Intelligent Monitoring (IM), to predict the quality of care provided by National Health Service (NHS) hospital trusts so that those at greatest risk of providing poor-quality care can be identified and targeted for inspection. METHODS: The predictive ability of the IM tool is evaluated through regression analyses and χ2 testing of the relationship between the quantitative risk score generated by the IM tool and the subsequent quality rating awarded following detailed on-site inspection by large expert teams of inspectors. RESULTS: First, the continuous risk scores generated by the CQC's IM statistical surveillance tool cannot predict inspection-based quality ratings of NHS hospital trusts (OR 0.38 (0.14 to 1.05) for Outstanding/Good, OR 0.94 (0.80 to -1.10) for Good/Requires improvement, and OR 0.90 (0.76 to 1.07) for Requires improvement/Inadequate). Second, the risk scores cannot be used more simply to distinguish the trusts performing poorly-those subsequently rated either 'Requires improvement' or 'Inadequate'-from the trusts performing well-those subsequently rated either 'Good' or 'Outstanding' (OR 1.07 (0.91 to 1.26)). Classifying CQC's risk bandings 1-3 as high risk and 4-6 as low risk, 11 of the high risk trusts were performing well and 43 of the low risk trusts were performing poorly, resulting in an overall accuracy rate of 47.6%. Third, the risk scores cannot be used even more simply to distinguish the worst performing trusts-those subsequently rated 'Inadequate'-from the remaining, better performing trusts (OR 1.11 (0.94 to 1.32)). Classifying CQC's risk banding 1 as high risk and 2-6 as low risk, the highest overall accuracy rate of 72.8% was achieved, but still only 6 of the 13 Inadequate trusts were correctly classified as being high risk. CONCLUSIONS: Since the IM statistical surveillance tool cannot predict the outcome of NHS hospital trust inspections, it cannot be used for prioritisation. A new approach to inspection planning is therefore required.

Accounting for failure: risk-based regulation and the problems of ensuring healthcare quality in the NHS.

In this paper, we examine why risk-based policy instruments have failed to improve the proportionality, effectiveness, and legitimacy of healthcare quality regulation in the National Health Service (NHS) in England. Rather than trying to prevent all possible harms, risk-based approaches promise to rationalise and manage the inevitable limits of what regulation can hope to achieve by focusing regulatory standard-setting and enforcement activity on the highest priority risks, as determined through formal assessments of their probability and consequences. As such, risk-based approaches have been enthusiastically adopted by healthcare quality regulators over the last decade. However, by drawing on historical policy analysis and in-depth interviews with 15 high-level UK informants in 2013-2015, we identify a series of practical problems in using risk-based policy instruments for defining, assessing, and ensuring compliance with healthcare quality standards. Based on our analysis, we go on to consider why, despite a succession of failures, healthcare regulators remain committed to developing and using risk-based approaches. We conclude by identifying several preconditions for successful risk-based regulation: goals must be clear and trade-offs between them amenable to agreement; regulators must be able to reliably assess the probability and consequences of adverse outcomes; regulators must have a range of enforcement tools that can be deployed in proportion to risk; and there must be political tolerance for adverse outcomes.

Flooding and the framing of risk in British broadsheets, 1985-2010.

Our analysis of 2707 news stories explores the framing of flooding in Britain over the past quarter century and the displacement of a once dominant understanding of flooding as an agricultural problem of land drainage by the contemporary concern for its urban impacts, particularly to homes and property. We document dramatic changes in the volume and variety of reporting about flooding since 2000 as the risks of flooding have become more salient, the informal 'Gentlemen's Agreement' between government and private insurers has broken down, and flood management subjected to greater public scrutiny. While the historic reliance on private insurance remains largely unchallenged, we show that other aspects of flood hazard management are now topics of active political debate to which the looming threat of climate change adds both urgency and exculpatory excuses for poor performance. We conclude by reflecting on the significance of the case for grand theories of neoliberalisation and governmentality.