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Background Delirium affects > 15% of hospitalised patients but is grossly underdetected, contributing to poor care. The 4 ‘A’s Test (4AT, www.the4AT.com ) is a short delirium assessment tool designed for routine use without special training. The primary objective was to assess the accuracy of the 4AT for delirium detection. The secondary objective was to compare the 4AT with another commonly used delirium assessment tool, the Confusion Assessment Method (CAM). Methods This was a prospective diagnostic test accuracy study set in emergency departments or acute medical wards involving acute medical patients aged ≥ 70. All those without acutely life-threatening illness or coma were eligible. Patients underwent (1) reference standard delirium assessment based on DSM-IV criteria and (2) were randomised to either the index test (4AT, scores 0–12; prespecified score of > 3 considered positive) or the comparator (CAM; scored positive or negative), in a random order, using computer-generated pseudo-random numbers, stratified by study site, with block allocation. Reference standard and 4AT or CAM assessments were performed by pairs of independent raters blinded to the results of the other assessment. Results Eight hundred forty-three individuals were randomised: 21 withdrew, 3 lost contact, 32 indeterminate diagnosis, 2 missing outcome, and 785 were included in the analysis. Mean age was 81.4 (SD 6.4) years. 12.1% (95/785) had delirium by reference standard assessment, 14.3% (56/392) by 4AT, and 4.7% (18/384) by CAM. The 4AT had an area under the receiver operating characteristic curve of 0.90 (95% CI 0.84–0.96). The 4AT had a sensitivity of 76% (95% CI 61–87%) and a specificity of 94% (95% CI 92–97%). The CAM had a sensitivity of 40% (95% CI 26–57%) and a specificity of 100% (95% CI 98–100%). Conclusions The 4AT is a short, pragmatic tool which can help improving detection rates of delirium in routine clinical care. Trial registration International standard randomised controlled trial number (ISRCTN) 53388093 . Date applied 30/05/2014; date assigned 02/06/2014.

The aim of diagnostic point-of-care testing is to minimise the time to obtain a test result, thereby allowing clinicians and patients to make a quick clinical decision. Because point-of-care tests are used in resource-limited settings, the benefits need to outweigh the costs. To optimise point-of-care testing in resource-limited settings, diagnostic tests need rigorous assessments focused on relevant clinical outcomes and operational costs, which differ from assessments of conventional diagnostic tests. We reviewed published studies on point-of-care testing in resource-limited settings, and found no clearly defined metric for the clinical usefulness of point-of-care testing. Therefore, we propose a framework for the assessment of point-of-care tests, and suggest and define the term test efficacy to describe the ability of a diagnostic test to support a clinical decision within its operational context. We also propose revised criteria for an ideal diagnostic point-of-care test in resource-limited settings. Through systematic assessments, comparisons between centralised testing and novel point-of-care technologies can be more formalised, and health officials can better establish which point-of-care technologies represent valuable additions to their clinical programmes.

Purpose This study aims to examine interactions between multiple management accounting routines in integrating a new management accounting routine into a routine cluster. Design/methodology/approach This study uses a theoretical framework based on routine clusters, including routine complementarities. The authors use an in-depth case study to explore interactions of a management accounting routine integrating into a routine cluster. Findings The findings show that complementarity between an existing and a new management accounting routine facilitates integration of the new routine into a routine cluster. They also suggest that when an ostensive understanding of a routine exists, the integration of the new management accounting routine is stronger, as the new and existing routines in the routine cluster are more closely intertwined. Originality/value To the best of the authors’ knowledge, this paper is among the first to explore the role of intertwinedness of a new management accounting routine and existing organizational routines in integrating a new management accounting routine into a routine cluster. The findings imply that future management accounting research may need to distinguish between different forms of complementarity.

Background Spillover of effect, whether positive or negative, from intervention to control group patients invalidates the Stable Unit Treatment Variable Assumption (SUTVA). SUTVA is critical to valid causal inference from randomized concurrent controlled trials (RCCT). Spillover of infection prevention is an important population level effect mediating herd immunity. This herd effect, being additional to any individual level effect, is subsumed within the overall effect size (ES) estimate derived by contrast-based techniques from RCCT’s. This herd effect would manifest only as increased dispersion among the control group infection incidence rates above background. Methods and results The objective here is to explore aspects of spillover and how this might be visualized and diagnosed. I use, for illustration, data from 190 RCCT’s abstracted in 13 Cochrane reviews of various antimicrobial versus non-antimicrobial based interventions to prevent pneumonia in ICU patients. Spillover has long been postulated in this context. Arm-based techniques enable three approaches to identify increased dispersion, not available from contrast-based techniques, which enable the diagnosis of spillover within antimicrobial versus non-antimicrobial based infection prevention RCCT’s. These three approaches are benchmarking the pneumonia incidence rates versus a clinically relevant range, comparing the dispersion in pneumonia incidence among the control versus the intervention groups and thirdly, visualizing the incidence dispersion within summary receiver operator characteristic (SROC) plots. By these criteria there is harmful spillover effects to concurrent control group patients. Conclusions Arm-based versus contrast-based techniques lead to contrary inferences from the aggregated RCCT’s of antimicrobial based interventions despite similar summary ES estimates. Moreover, the inferred relationship between underlying control group risk and ES is ‘flipped’.

Financial incentives and audit/feedback are widely used in primary care to influence clinician behaviour and increase quality of care. While observational data suggest a decline in quality when these interventions are stopped, their removal has not been evaluated in a randomised controlled trial (RCT), to our knowledge. This trial aimed to determine whether chlamydia testing in general practice is sustained when financial incentives and/or audit/feedback are removed. We undertook a 2 × 2 factorial cluster RCT in 60 general practices in 4 Australian states targeting 49,525 patients aged 16-29 years for annual chlamydia testing. Clinics were recruited between July 2014 and September 2015 and were followed for up to 2 years or until 31 December 2016. Clinics were eligible if they were in the intervention group of a previous cluster RCT where general practitioners (GPs) received financial incentives (AU$5-AU$8) for each chlamydia test and quarterly audit/feedback reports of their chlamydia testing rates. Clinics were randomised into 1 of 4 groups: incentives removed but audit/feedback retained (group A), audit/feedback removed but incentives retained (group B), both removed (group C), or both retained (group D). The primary outcome was the annual chlamydia testing rate among 16- to 29-year-old patients, where the numerator was the number who had at least 1 chlamydia test within 12 months and the denominator was the number who had at least 1 consultation during the same 12 months. We undertook a factorial analysis in which we investigated the effects of removal versus retention of incentives (groups A + C versus groups B + D) and the effects of removal versus retention of audit/feedback (group B + C versus groups A + D) separately. Of 60 clinics, 59 were randomised and 55 (91.7%) provided data (group A: 15 clinics, 11,196 patients; group B: 14, 11,944; group C: 13, 11,566; group D: 13, 14,819). Annual testing decreased from 20.2% to 11.7% (difference -8.8%; 95% CI -10.5% to -7.0%) in clinics with incentives removed and decreased from 20.6% to 14.3% (difference -7.1%; 95% CI -9.6% to -4.7%) where incentives were retained. The adjusted absolute difference in treatment effect was -0.9% (95% CI -3.5% to 1.7%; p = 0.2267). Annual testing decreased from 21.0% to 11.6% (difference -9.5%; 95% CI -11.7% to -7.4%) in clinics where audit/feedback was removed and decreased from 19.9% to 14.5% (difference -6.4%; 95% CI -8.6% to -4.2%) where audit/feedback was retained. The adjusted absolute difference in treatment effect was -2.6% (95% CI -5.4% to -0.1%; p = 0.0336). Study limitations included an unexpected reduction in testing across all groups impacting statistical power, loss of 4 clinics after randomisation, and inclusion of rural clinics only. Audit/feedback is more effective than financial incentives of AU$5-AU$8 per chlamydia test at sustaining GP chlamydia testing practices over time in Australian general practice. Australian New Zealand Clinical Trials Registry ACTRN12614000595617.

Author guidelines for journals could help to promote transparency, openness, and reproducibility Transparency, openness, and reproducibility are readily recognized as vital features of science ( 1 , 2 ). When asked, most scientists embrace these features as disciplinary norms and values ( 3 ). Therefore, one might expect that these valued features would be routine in daily practice. Yet, a growing body of evidence suggests that this is not the case ( 4 – 6 ).

Solving differential equations of fractional (i.e., non-integer) order in an accurate, reliable and efficient way is much more difficult than in the standard integer-order case; moreover, the majority of the computational tools do not provide built-in functions for this kind of problem. In this paper, we review two of the most effective families of numerical methods for fractional-order problems, and we discuss some of the major computational issues such as the efficient treatment of the persistent memory term and the solution of the nonlinear systems involved in implicit methods. We present therefore a set of MATLAB routines specifically devised for solving three families of fractional-order problems: fractional differential equations (FDEs) (also for the non-scalar case), multi-order systems (MOSs) of FDEs and multi-term FDEs (also for the non-scalar case); some examples are provided to illustrate the use of the routines.

PurposeBuilding on the routine dynamics literature, this paper aims to expand our philosophical, practical and infrastructural understanding of implementing lean production. The authors provide a process view on the interplay between lean operating routines and continuous improvement (CI) routines and the roles of different actors in initiating and establishing these routines.Design/methodology/approachUsing data from interviews, observations and document analysis, retrospective comparative analyses of three embedded case studies on lean implementations provide a process understanding of enacting and patterning lean operating and CI routines in manufacturing SMEs.FindingsIncorporating the “who” and “how” next to the “what” of practices and routines helps explain that rather than being implemented in isolation or even in conjunction with each other, sustainable lean practices and routines come about through team leader and employee enactment of the CI practices and routines. Neglecting these patterns aligned with unsustainable implementations.Research limitations/implicationsThe proposed process model provides a valuable way to integrate variance and process streams of literature to better understand lean production implementations.Practical implicationsThe process model helps manufacturing managers, policy makers, consultants and educators to reconsider their approach to implementing lean production or teaching how to do so.Originality/valueNuancing the existing lean implementation literature, the proposed process model shows that CI routines do not stem from implementing lean operating routines. Rather, the model highlights the importance of active engagement of actors at multiple organizational levels and strong connections between and across levels to change routines and work practices for implementing lean production.

Liquid chromatography–tandem mass spectrometry (LC–MS/MS) has been increasingly used in routine clinical laboratories during the last two decades. The high specificity, sensitivity, and multi-analyte potential make it an ideal alternative to immunoassays or conventional high-performance liquid chromatography (HPLC). It also provides higher throughput than gas chromatography–mass spectrometry (GC–MS). LC–MS/MS also offers higher flexibility than immunoassays because LC–MS/MS assays are typically developed in-house. In addition, abundant information can be obtained from a single LC–MS/MS run which can produce a large amount of quantitative or qualitative data. In this review, typical LC–MS/MS clinical applications are presented, personal experiences are shared, and strengths and weakness are discussed. It is foreseeable that LC–MS/MS will become a key instrument in routine clinical laboratories.