Safer clinical systems : interim report, August 2010

Safer Clinical Systems is the Health Foundation’s new five year programme of work to test and demonstrate ways to improve healthcare systems and processes, to develop safer systems that improve patient safety. It builds on learning from the Safer Patients Initiative (SPI) and models of system improvement from both healthcare and other industries. Learning from the SPI highlighted the need to take a clinical systems approach to improving safety. SPI highlighted that many hospitals struggle to implement improvement in clinical areas due to inherent problems with support mechanisms. Clinical processes and systems, rather than individuals, are often the contributors to breakdown in patient safety. The Safer Clinical Systems programme aimed to measure the reliability of clinical processes, identify defects within those processes, and identify the systems that result in those defects. Methods to improve system reliability were then to be tested and re-developed in order to reduce the risk of harm being caused to patients. Such system-level awareness should lead to improvements in other patient care pathways. The relationship between system reliability and actual harm is challenging to identify and measure. Specific, well-defined, small-scale processes have been used in other programmes, and system reliability has been shown to have a direct causal relationship with harm (e.g. care bundle compliance in an intensive care unit can reduce the incidence of ventilator-associated pneumonia). However, it has become evident that harm can be caused by a variety of factors over time; when working in broader, more complex and dynamic systems, change in outcome can be difficult to attribute to specific improvements and difficulties are also associated with relating evidence to resulting harm. The overall aim of Phase 1 of the Safer Clinical Systems programme was to demonstrate proof-of-concept that using a systems-based approach could contribute to improved patient safety. In Phase 1, experienced NHS teams from four locations worked together with expert advisers to co-design the Safer Clinical Systems programme

Service Virtualisation of Internet-of-Things Devices: Techniques and Challenges

Service virtualization is an approach that uses virtualized environments to automatically test enterprise services in production-like conditions. Many techniques have been proposed to provide such a realistic environment for enterprise services. The Internet-of-Things (IoT) is an emerging field which connects a diverse set of devices over different transport layers, using a variety of protocols. Provisioning a virtual testbed of IoT devices can accelerate IoT application development by enabling automated testing without requiring a continuous connection to the physical devices. One solution is to expand existing enterprise service virtualization to IoT environments. There are various structural differences between the two environments that should be considered to implement appropriate service virtualization for IoT. This paper examines the structural differences between various IoT protocols and enterprise protocols and identifies key technical challenges that need to be addressed to implement service virtualization in IoT environments.Comment: 4 page

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Automated reliability assessment for spectroscopic redshift measurements

We present a new approach to automate the spectroscopic redshift reliability assessment based on machine learning (ML) and characteristics of the redshift probability density function (PDF). We propose to rephrase the spectroscopic redshift estimation into a Bayesian framework, in order to incorporate all sources of information and uncertainties related to the redshift estimation process, and produce a redshift posterior PDF that will be the starting-point for ML algorithms to provide an automated assessment of a redshift reliability. As a use case, public data from the VIMOS VLT Deep Survey is exploited to present and test this new methodology. We first tried to reproduce the existing reliability flags using supervised classification to describe different types of redshift PDFs, but due to the subjective definition of these flags, soon opted for a new homogeneous partitioning of the data into distinct clusters via unsupervised classification. After assessing the accuracy of the new clusters via resubstitution and test predictions, unlabelled data from preliminary mock simulations for the Euclid space mission are projected into this mapping to predict their redshift reliability labels.Comment: Submitted on 02 June 2017 (v1). Revised on 08 September 2017 (v2). Latest version 28 September 2017 (this version v3

Judging Innocence

This empirical study examines for the first time how the criminal justice system in the United States handled the cases of people who were subsequently found innocent through postconviction DNA testing. The data collected tell the story of this unique group of exonerees, starting with their criminal trials, moving through levels of direct appeals and habeas corpus review, and ending with their eventual exonerations. Beginning with the trials of these exonerees, this study examines the leading types of evidence supporting their wrongful convictions, which were erroneous eyewitness identifications, forensic evidence, informant testimony, and false confessions. Yet our system of criminal appeals and postconviction review poorly addressed factual deficiencies in these trials. Few exonerees brought claims regarding those facts or claims alleging their innocence. For those who did, hardly any claims were granted by courts. Far from recognizing innocence, courts often denied relief by finding errors to be harmless. Criminal appeals and postconviction proceedings brought before these exonerees proved their innocence using DNA testing yielded apparently high numbers of reversals 14% reversal rate. However, that reversal rate was indistinguishable from the background reversal rates of comparable rape and murder convictions. Our system may produce high rates of reversible errors during rape and murder trials. Finally, even after DNA testing was available, many exonerees had difficulty securing access to testing and ultimately receiving relief. These findings all demonstrate how our criminal system failed to effectively review unreliable factual evidence, and as a result, misjudged innocence