Errors associated with the preparation of aseptic products in UK hospital pharmacies: lessons from the national aseptic error reporting scheme

Background Pharmacy aseptic units prepare and supply injectables to minimise risks. The UK National Aseptic Error Reporting Scheme has been collecting data on pharmacy compounding errors, including near-misses, since 2003. Objectives The cumulative reports from January 2004 to December 2007, inclusive, were analysed. Methods The different variables of product types, error types, staff making and detecting errors, stage errors detected, perceived contributory factors, and potential or actual outcomes were presented by cross-tabulation of data. Results A total of 4691 reports were submitted against an estimated 958 532 items made, returning 0.49% as the overall error rate. Most of the errors were detected before reaching patients, with only 24 detected during or after administration. The highest number of reports related to adult cytotoxic preparations (40%) and the most frequently recorded error was a labelling error (34.2%). Errors were mostly detected at first check in assembly area (46.6%). Individual staff error contributed most (78.1%) to overall errors, while errors with paediatric parenteral nutrition appeared to be blamed on low staff levels more than other products were. The majority of errors (68.6%) had no potential patient outcomes attached, while it appeared that paediatric cytotoxic products and paediatric parenteral nutrition were associated with greater levels of perceived patient harm. Conclusions The majority of reports were related to near-misses, and this study highlights scope for examining current arrangements for checking and releasing products, certainly for paediatric cytotoxic and paediatric parenteral nutrition preparations within aseptic units, but in the context of resource and capacity constraints.

The automatic identification and prioritisation of criminal networks from police crime data

The identification of criminal networks is not a routine exploratory process within the current practice of the law enforcement authorities; rather it is triggered by specific evidence of criminal activity being investigated. A network is identified when a criminal comes to notice and any associates who could also be potentially implicated would need to be identified if only to be eliminated from the enquiries as suspects or witnesses as well as to prevent and/or detect crime. However, an identified network may not be the one causing most harm in a given area.. This paper identifies a methodology to identify all of the criminal networks that are present within a Law Enforcement Area, and, prioritises those that are causing most harm to the community. Each crime is allocated a score based on its crime type and how recently the crime was committed; the network score, which can be used as decision support to help prioritise it for law enforcement purposes, is the sum of the individual crime scores.

Video activity extraction and reporting with incremental unsupervised learning

The present work presents a new method for activity extraction and reporting from video based on the aggregation of fuzzy relations. Trajectory clustering is first employed mainly to discover the points of entry and exit of mobiles appearing in the scene. In a second step, proximity relations between resulting clusters of detected mobiles and contextual elements from the scene are modeled employing fuzzy relations. These can then be aggregated employing typical soft-computing algebra. A clustering algorithm based on the transitive closure calculation of the fuzzy relations allows building the structure of the scene and characterises the ongoing different activities of the scene. Discovered activity zones can be reported as activity maps with different granularities thanks to the analysis of the transitive closure matrix. Taking advantage of the soft relation properties, activity zones and related activities can be labeled in a more human-like language. We present results obtained on real videos corresponding to apron monitoring in the Toulouse airport in France.

Proposed best practice for statisticians in the reporting and publication of pharmaceutical industry-sponsored clinical trials

In this paper we set out what we consider to be a set of best practices for statisticians in the reporting of pharmaceutical industry-sponsored clinical trials. We make eight recommendations covering: author responsibilities and recognition; publication timing; conflicts of interest; freedom to act; full author access to data; trial registration and independent review. These recommendations are made in the context of the prominent role played by statisticians in the design, conduct, analysis and reporting of pharmaceutical sponsored trials and the perception of the reporting of these trials in the wider community.

The potential for bias in reporting of industry-sponsored clinical trials

Concerns about potentially misleading reporting of pharmaceutical industry research have surfaced many times. The potential for duality (and thereby conflict) of interest is only too clear when you consider the sums of money required for the discovery, development and commercialization of new medicines. As the ability of major, mid-size and small pharmaceutical companies to innovate has waned, as evidenced by the seemingly relentless decline in the numbers of new medicines approved by Food and Drug Administration and European Medicines Agency year-on-year, not only has the cost per new approved medicine risen: so too has the public and media concern about the extent to which the pharmaceutical industry is open and honest about the efficacy, safety and quality of the drugs we manufacture and sell. In 2005 an Editorial in Journal of the American Medical Association made clear that, so great was their concern about misleading reporting of industry-sponsored studies, henceforth no article would be published that was not also guaranteed by independent statistical analysis. We examine the precursors to this Editorial, as well as its immediate and lasting effects for statisticians, for the manner in which statistical analysis is carried out, and for the industry more generally.

Facilities management carbon footprints: an audit of critical elements of management and reporting

Concern for the environmental impact of organizations’ activities has led to the recognition and demand for organizations to manage and report on their carbon footprint. However, there is no limit as to the areas of carbon footprints required in such annual environmental reports. To deliver improvements in the quality of carbon footprint management and reporting, there is a need to identify the main elements of carbon footprint strategy that can be endorsed, supported and encouraged by facility managers. The study investigates carbon footprint elements managed and reported upon by facility manager in the UK. Drawing on a questionnaire survey of 256 facility managers in the UK, the key elements of carbon footprints identified in carbon footprint reports are examined. The findings indicate that the main elements are building energy consumption, waste disposal and water consumption. Business travel in terms of using public transport, air travel and company cars are also recognized as important targets and objectives for the carbon footprint strategy of several FM (facilities management) organizations.