National Reporting and Learning System Research and Development

This report presents the findings of the NRLS Research and Development Programme conducted by the Patient Safety Translational Research Centre (PSTRC) and the Centre for Health Policy (CHP) at Imperial College London. It sets out the current state of affairs regarding patient safety incident reporting in the NHS, and specifies where the most pressing areas of concerns are, including thorough descriptions of the various incident reporting systems used in the NHS today. Furthermore it identifies areas for improvement in the overall landscape of incident reporting, and suggests how systems like the NRLS can capitalise on developments in technology. The main body of the report is then devoted to explaining the findings from the research programme. The research was divided into four domains, and the report details the new findings discovered about each of them: 1. Purpose of incident reporting in healthcare 2. User experience with reporting systems 3. Data quality and analysis 4. Effective feedback for learning Building on these findings, the report moves on to describe how they can be applied to the next generation of incident reporting. Specifically, it focuses on a prototype for a new incident reporting system that incorporates the improvement ideas generated by the research. Finally, the report concludes with a description of an evidence-based framework for evaluating incident reporting systems and an ‘Achievement Toolkit’ of ten recommendations for improvements to incident reporting systems

Dealing with abstraction: Case study generalisation as a method for eliciting design patterns

Developing a pattern language is a non-trivial problem. A critical requirement is a method to support pattern writers with abstraction, so as they can produce generalised patterns. In this paper, we address this issue by developing a structured process of generalisation. It is important that this process is initiated through engaging participants in identifying initial patterns, i.e. directly dealing with the 'cold-start' problem. We have found that short case study descriptions provide a productive 'way into' the process for participants. We reflect on a 1-year interdisciplinary pan-European research project involving the development of almost 30 cases and over 150 patterns. We provide example cases, detailing the process by which their associated patterns emerged. This was based on a foundation for generalisation from cases with common attributes. We discuss the merits of this approach and its implications for pattern development

Emerging Opportunities: Monitoring and Evaluation in a Tech-Enabled World

Various trends are impacting on the field of monitoring and evaluation in the area of international development. Resources have become ever more scarce while expectations for what development assistance should achieve are growing. The search for more efficient systems to measure impact is on. Country governments are also working to improve their own capacities for evaluation, and demand is rising from national and community-based organizations for meaningful participation in the evaluation process as well as for greater voice and more accountability from both aid and development agencies and government.These factors, in addition to greater competition for limited resources in the area of international development, are pushing donors, program participants and evaluators themselves to seek more rigorous – and at the same time flexible – systems to monitor and evaluate development and humanitarian interventions.However, many current approaches to M&E are unable to address the changing structure of development assistance and the increasingly complex environment in which it operates. Operational challenges (for example, limited time, insufficient resources and poor data quality) as well as methodological challenges that impact on the quality and timeliness of evaluation exercises have yet to be fully overcome

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

A systemic perspective on racism in football: the experience of the BRISWA project

The objective of this paper is to present the process for the development of a causal loop diagram that captures the relevant aspects of racism in football, through a holistic, top-down approach. To do so, a series of workshops/sessions has been organised with experts in the field and with the purpose of designing a tool that could be used to get better insights into how racism in football emerges and where are the potential areas where policymakers could use as leverage for effective counter-measures. The diagram demonstrated the multi-faceted nature of racism, the phenomena that might give rise to it and the elements that could serve as leverage in potential counter-measures. Some of the most interesting results include the following: the power structures of society and football should adapt to represent the actual demographic make-up of each country. Furthermore, policymakers should involve media more directly in every attempt to fight racism. Finally, racism in football is a mirror of racism in society. Hence, any attempt to combat racism in football should be interlinked with corresponding efforts to fight discrimination in society

Preventing Accidents and Building a Culture of Safety: Insights from a Simulation Model

Research has approached the topic of safety in organizations from a number of different perspectives. On the one hand, psychological research on safety climate gives evidence for a range of organizational factors that predict safety across organizations. On the other hand, organizational learning theorists view safety as a dynamic problem in which organizations must learn from mistakes. Here, we synthesize these two streams of research by incorporating key organizational factors from the safety climate literature into a dynamic simulation model that also includes the possibility for learning. Analysis of simulation results sheds insight into the nature of reliability and confirms the dangers of over-reliance on 'single loop learning' as a mechanism for controlling safety behaviors. Special emphasis is placed on strategies that managers might use to encourage learning and prevent erosion in safety behaviors over time.Work reported herein was supported, in part, by the Singapore Defence Science and Technology Agency (DSTA)

Mapping underground assets in the UK: Project Iceberg. Work Package 1, market research into current state of play and global case studies

Project Iceberg is an exploratory project undertaken by Future Cities Catapult, British Geological Survey (BGS) and Ordnance Survey (OS). The project aims to address the serious issue of the lack of information about the ground beneath our cities and the un-coordinated way in which the subsurface space is managed. Difficulties relating to data capture and sharing of information about subsurface features are well understood by some sectors and have been explored in previous research and industry reports, many of which are highlighted in this report. This study does not replicate past work, but rather reviews outcomes and explores the barriers to wider uptake of subsurface management systems within integrated city management. The long-term goal is to help increase the viability of land for development and de-risk future investment through better management of subsurface data. To help achieve this, our study aims to enable a means to discover and access relevant data about the ground’s physical condition and assets housed within it, in a way that is suitable for modern, data driven decision-making processes. The project considers both physical infrastructure i.e. underground utilities and natural ground conditions i.e. geological data and is divided into three different work packages: Work Package 1: Market research and analysis Work Package 2: Data operation systems and interoperability for a subsurface data platform Work Package 3: Identification of use cases for a subsurface data platform This report summarises the findings of work package 1 and identifies the following key findings and recommendations. There is substantial potential for commercialisation of data tools and data services using an integrated surface-subsurface data platform, which would support, for example, urban planning, redevelopment, infrastructure assessments and street works. Realising the full benefit of these opportunities relies on the sharing of data beyond statutory undertakers, albeit with suitable controls in place. Statutory undertakers do not necessarily have the national overview, capability or remit to develop an integrated platform. Stakeholders acknowledge that incomplete subsurface information means that land value is not being protected or worse, is being diminished and that organisations are incurring 6 indirect costs due to project delays and requirements for additional surveys. However, the direct costs of obtaining subsurface data and the indirect costs incurred because of incomplete access to subsurface data is largely unknown. Amendments to existing and introduction of new data standards (PAS 128 and PAS 256) make provision for more consistent and accurate data capture of buried utilities. Sharing of more accurate utility data will be facilitated and links to building information models and smart city standards will be more explicit. However, currently, storage of data and the integrity of data stores is not being addressed consistently at national level. There is a currently a lack of national standard that addresses commercial sensitivities and security risks concerning subsurface data sharing that can potentially guide “the right people getting access to the right and comprehensive set of data, at the right time without fear that parts of it have been redacted or manipulated” Investment in research and innovation to support the development of tools to identify the location of buried infrastructure has been successful and new systems are being brought to the market that will enable more accurate mapping of underground infrastructure. Precedents have been set for the sharing of underground utility data of national importance – exemplar projects, such as the VAULT and Greater Manchester Open Data Infrastructure Map (GMODIN), demonstrate successful collaboration across the utility sector to generate an integrated utility infrastructure map. Meanwhile adoption of AGS data formats by the ground investigation community has led to large-scale sharing of geotechnical data. National scale sharing of buried utility data has only been demonstrated in Scotland, largely driven by nationalised utilities. Upscaling of exemplar projects across the UK needs prioritising. The National Infrastructure Commission, Infrastructure Projects Authority and Digital Built Britain should take leadership of the development of an integrated data framework that combines surface and subsurface data. Future legislation and standards may be required to ensure the accurate and standardised capture and supply of buried infrastructure data. The benefits and business opportunities that may be delivered through an integrated data framework that embeds subsurface data are not sufficiently highlighted to stakeholders. Thus, the incentives and business drivers to collaborate on a subsurface data platform need to be better illustrated. Project Iceberg WP3 goes some way to addressing this but further work is needed

Applying systems thinking to unravel the mechanisms underlying orthostatic hypotension related fall risk

Orthostatic hypotension (OH) is an established and common cardiovascular risk factor for falls. An in-depth understanding of the various interacting pathophysiological pathways contributing to OH-related falls is essential to guide improvements in diagnostic and treatment opportunities. We applied systems thinking to multidisciplinary map out causal mechanisms and risk factors. For this, we used group model building (GMB) to develop a causal loop diagram (CLD). The GMB was based on the input of experts from multiple domains related to OH and falls and all proposed mechanisms were supported by scientific literature. Our CLD is a conceptual representation of factors involved in OH-related falls, and their interrelatedness. Network analysis and feedback loops were applied to analyze and interpret the CLD, and quantitatively summarize the function and relative importance of the variables. Our CLD contains 50 variables distributed over three intrinsic domains (cerebral, cardiovascular, and musculoskeletal), and an extrinsic domain (e.g., medications). Between the variables, 181 connections and 65 feedback loops were identified. Decreased cerebral blood flow, low blood pressure, impaired baroreflex activity, and physical inactivity were identified as key factors involved in OH-related falls, based on their high centralities. Our CLD reflects the multifactorial pathophysiology of OH-related falls. It enables us to identify key elements, suggesting their potential for new diagnostic and treatment approaches in fall prevention. The interactive online CLD renders it suitable for both research and educational purposes and this CLD is the first step in the development of a computational model for simulating the effects of risk factors on falls

Business Model Canvas to Create and Capture AI-enabled Public Value

The compatibility between the business model and AI-enabled value creation is paramount for the sustainability of organizations. The public sector lags the private sector in the race to AI readiness and adoption. Although the concept of the business model for the public sector has previously been discussed, we found a lack of evidence for the process of adaption of the business model as a value creation and capture tool from commercial motives to public value motives. This paper adapts the conventional business model canvas for the public sector as it pertains to the design and development of AI systems. Employing a design-science research approach, we postulate five design principles that public agencies must follow to design and deploy AI-enabled public services