A manifesto for a socio-technical approach to NHS and social care IT-enabled business change - to deliver effective high quality health and social care for all

80% of IT projects are known to fail. Adopting a socio-technical approach will help them to succeed in the future. The socio-technical proposition is simply that any work system comprises both a social system (including the staff, their working practices, job roles, culture and goals) and a technical system (the tools and technologies that support and enable work processes). These elements together form a single system comprising interacting parts. The technical and the social elements need to be jointly designed (or redesigned) so that they are congruent and support one another in delivering a better service. Focusing on one aspect alone is likely to be sub-optimal and wastes money (Clegg, 2008). Thus projects that just focus on the IT will almost always fail to deliver the full benefits

Ethics and Design in the Brazilian Context

Often driven by practical and immediate requirements, more and more people are incorporating technology into a variety of aspects of their lives, often without reflecting on the consequences of using them. On the other hand, studies on interactive system development that lead to behavioral change have been gaining ground on the agenda of large HCI conferences. This movement brings to the forefront the fundamental issues of ethics in design and technology use. A designer’s intentions, when directing certain actions or behaviors, are not always explicit or desired by the stakeholders affected by the use of the technology. Systems that induce an undesired purchase, or even those that use conditioning strategies to cause a behavioral change are examples of such intentions. The challenge proposed is therefore about the relationship between design and personal freedom in a way that these technology users do not become victims, either passively or submissively, of the effects of its use. This advance allows for the redefinition of the relationship between man and technology, and the application of new forms of designing and developing interactive systems that take into account the ethical aspects of this relationship

Müller glia activation in response to inherited retinal degeneration is highly varied and disease-specific

Despite different aetiologies, most inherited retinal disorders culminate in photoreceptor loss, which induces concomitant changes in the neural retina, one of the most striking being reactive gliosis by Müller cells. It is typically assumed that photoreceptor loss leads to an upregulation of glial fibrilliary acidic protein (Gfap) and other intermediate filament proteins, together with other gliosis-related changes, including loss of integrity of the outer limiting membrane (OLM) and deposition of proteoglycans. However, this is based on a mix of both injury-induced and genetic causes of photoreceptor loss. There are very few longitudinal studies of gliosis in the retina and none comparing these changes across models over time. Here, we present a comprehensive spatiotemporal assessment of features of gliosis in the degenerating murine retina that involves Müller glia. Specifically, we assessed Gfap, vimentin and chondroitin sulphate proteoglycan (CSPG) levels and outer limiting membrane (OLM) integrity over time in four murine models of inherited photoreceptor degeneration that encompass a range of disease severities (Crb1rd8/rd8, Prph2+/Δ307, Rho-/-, Pde6brd1/rd1). These features underwent very different changes, depending upon the disease-causing mutation, and that these changes are not correlated with disease severity. Intermediate filament expression did indeed increase with disease progression in Crb1rd8/rd8 and Prph2+/Δ307, but decreased in the Prph2+/Δ307 and Pde6brd1/rd1 models. CSPG deposition usually, but not always, followed the trends in intermediate filament expression. The OLM adherens junctions underwent significant remodelling in all models, but with differences in the composition of the resulting junctions; in Rho-/- mice, the adherens junctions maintained the typical rod-Müller glia interactions, while in the Pde6brd1/rd1 model they formed predominantly between Müller cells in late stage of degeneration. Together, these results show that gliosis and its associated processes are variable and disease-dependent

MS

thesisHealth information systems are networks of computers employed by health care enterprises to facilitate the delivery of their health care product. Computers originally entered the medical domain solely as tools aimed at the business functions of the hospital. Having demonstrated their utility in this area, computers were perceived by certain innovators to have usefulness in the clinical domain. As clinical computer applications were successfully developed and implemented, they have over time been merged together into systems offering multiple areas of functionality directly impacting the clinical aspects of health care delivery. Such health information systems have now assumed major importance in the provision of health care in a complex medical environment. Although the focus of substantial investment for development and implementation, relatively little work has been done to assess the value of such health information systems. The business information technology literature and the medical informatics literature each include only a small number of published reports examining the value question in an incomplete manner. No generally accepted valuation strategy has been developed for information systems in either the business or health care domains. Several valuation methods with potential applicability to health information systems have evolved: cost-effectiveness / cost- benefit analysis, return on investment, information economics, measurement systems, the Strassmann approach, the Japanese approach, and the strategic value approach. None of these valuation strategies is clearly superior; each has different strengths and weaknesses. A matrix comparing these strategies on the bases of explicitness and ease of implementation is proposed. Intermountain Health Care (IHC) has been instrumental in the development of health information systems and a leader in the application of such technology in clinical health care delivery. IHC's HELP system has played a seminal role as a catalyst to the development of the health information system industry. Although both historically and functionally important, detailed financial information regarding HELP'S origins and implementation no longer exists. Current IHC budget information demonstrates the major financial commitment underway within this health care enterprise totaling approximately $157 million over the last decade and with additional expenditures of$47 to $61 million projected annually through fiscal year 2004. The complex budgetary relationships between HELP and the other health information systems at LDS Hospital further obscure the magnitude of the information technology investment within this institution. Benefits of health information systems are potentially most substantial within the domain of clinical integration. IHC has not implemented any formal valuation strategy for its health information systems, but the ad hoc measurement systems valuation approach applied to date is practical, flexible, and the most appropriate of the available systems. Adequate valuation of health information systems cannot readily be achieved given the existing traditional hierarchical accounting structure; an alternative accounting framework patterned after a relational database is proposed

Advanced CO2 removal process control and monitor instrumentation development

A progam to evaluate, design and demonstrate major advances in control and monitor instrumentation was undertaken. A carbon dioxide removal process, one whose maturity level makes it a prime candidate for early flight demonstration was investigated. The instrumentation design incorporates features which are compatible with anticipated flight requirements. Current electronics technology and projected advances are included. In addition, the program established commonality of components for all advanced life support subsystems. It was concluded from the studies and design activities conducted under this program that the next generation of instrumentation will be greatly smaller than the prior one. Not only physical size but weight, power and heat rejection requirements were reduced in the range of 80 to 85% from the former level of research and development instrumentation. Using a microprocessor based computer, a standard computer bus structure and nonvolatile memory, improved fabrication techniques and aerospace packaging this instrumentation will greatly enhance overall reliability and total system availability

A3 thinking approach to support knowledge-driven design

Problem solving is a crucial skill in product development. Any lack of effective decision making at an early design stage will affect productivity and increase costs and the lead time for the other stages of the product development life cycle. This could be improved by the use of a simple and informative approach which allows the designers and engineers to make decisions in product design by providing useful knowledge. This paper presents a novel A3 thinking approach to problem solving in product design, and provides a new A3 template which is structured from a combination of customised elements (e.g. the 8 Disciplines approach) and reflection practice. This approach was validated using a case study in the Electromagnetic Compatibility (EMC) design issue for an automotive electrical sub-assembly product. The main advantage of the developed approach is to create and capture the useful knowledge in a simple manner. Moreover, the approach provides a reflection section allowing the designers to turn their experience of design problem solving into proper learning and to represent their understanding of the design solution. These will be systematically structured (e.g. as a design checklist) to be circulated and shared as a reference for future design projects. Thus, the recurrence of similar design problems will be prevented and will aid the designers in adopting the expected EMC test results

Deoxy technologies: a medical technology startup project: business plan for UK market

L26, O32DEOXY Technologies is a seed-stage medical technology project whose future core business will be based on an innovative Gene Expression profiling (GEP) nanotechnology, developed and patented at Harvard University. The project is located at Ludwig-Maximilian University (Germany) and its goal is to develop diagnostic tests for clinical market where price, speed and automation are competitive advantages. DEOXY Technologies intends to become a global and "lean" company focused on development and manufacturing of molecular tests (in vitro medical devices). This is a strategic analysis and a feasibility study for the breast cancer market. Breast cancer is the most frequent female cancer affecting 12% of women, worldwide and is seen as a paradigm of precision medicine success. The promoter identifies a clinical application for the GEP technology and proposes an alliance with an USA biomarker-focused company whose assets are complementary to the technology. The strategic analysis was based on a macroenvironmental analysis for the entrance market: United Kingdom, where regulatory and reimbursement contexts were systematized, and for Germany the country of development and manufacturing, where the impact of governmental support and the integration in a biotechnology cluster are critical favorable factors. In the microenvironmental analysis the high barriers to entrance and the importance of planning an exit strategy were underlined. The economic and financial viability analysis revealed that governmental funding is a critical success factor, as demonstrated by the positivity of the APV and emphasized the importance of a market expansion plan before starting operations. The scenario analysis explored how reimbursement and healthcare policies may impact the economic and financial viability of the project.A DEOXY Technologies é um projeto, baseado numa nanotecnologia inovadora de análise perfis de expressão genética (APEG), descoberta e patenteada na Universidade de Harvard. O projeto está integrado na Universidade de Ludwig-Maximilians, (Alemanha) e é candidato a fundos de investimento governamentais. A DEOXY Technologies acredita que por possuir uma tecnologia inovadora pode desenvolver máquinas de APEG e testes moleculares para o mercado clínico, onde o preço, automatização e rapidez serão vantagens competitivas. A DEOXY Technologies planeia tornar-se uma empresa global e "lean", focada no desenvolvimento e produção de testes moleculares "in vitro". Este plano de negócios contém a análise estratégica e económico-financeira para o mercado do cancro da mama, em Inglaterra (Reino Unido). O cancro da mama é o cancro mais frequente na mulher, afetando 12% desta população, e é paradigmático do sucesso da medicina de precisão. O promotor identifica uma necessidade clínica e para sua concretização propõe uma aliança com uma empresa biotecnológica detentora de ativos intelectuais complementares aos da DEOXY Technologies. A estratégia proposta baseia-se na análise PEST para o Reino Unido, contendo a regulamentação e etapas-chave para obter reembolso, e análise PEST para Alemanha, destacando-se a relevância do apoio governamental e da inserção num cluster biotecnológico como fatores críticos de sucesso. Da análise micro-ambiental salientam-se as barreiras à entrada e a importância da estratégia de saída nesta indústria. O estudo de viabilidade económico-financeira revelou que os fundos governamentais são um fator critico para a exequibilidade e viabilidade económico-financeira do projeto, sendo o valor atualizado ajustado o único indicador positivo. A análise de cenários demonstra como as políticas de cuidados de saúde influenciam a estratégia e a viabilidade económico-financeira do projeto

Investigating the attainment of optimum data quality for EHR Big Data: proposing a new methodological approach

The value derivable from the use of data is continuously increasing since some years. Both commercial and non-commercial organisations have realised the immense benefits that might be derived if all data at their disposal could be analysed and form the basis of decision taking. The technological tools required to produce, capture, store, transmit and analyse huge amounts of data form the background to the development of the phenomenon of Big Data. With Big Data, the aim is to be able to generate value from huge amounts of data, often in non-structured format and produced extremely frequently. However, the potential value derivable depends on general level of governance of data, more precisely on the quality of the data. The field of data quality is well researched for traditional data uses but is still in its infancy for the Big Data context. This dissertation focused on investigating effective methods to enhance data quality for Big Data. The principal deliverable of this research is in the form of a methodological approach which can be used to optimize the level of data quality in the Big Data context. Since data quality is contextual, (that is a non-generalizable field), this research study focuses on applying the methodological approach in one use case, in terms of the Electronic Health Records (EHR). The first main contribution to knowledge of this study systematically investigates which data quality dimensions (DQDs) are most important for EHR Big Data. The two most important dimensions ascertained by the research methods applied in this study are accuracy and completeness. These are two well-known dimensions, and this study confirms that they are also very important for EHR Big Data. The second important contribution to knowledge is an investigation into whether Artificial Intelligence with a special focus upon machine learning could be used in improving the detection of dirty data, focusing on the two data quality dimensions of accuracy and completeness. Regression and clustering algorithms proved to be more adequate for accuracy and completeness related issues respectively, based on the experiments carried out. However, the limits of implementing and using machine learning algorithms for detecting data quality issues for Big Data were also revealed and discussed in this research study. It can safely be deduced from the knowledge derived from this part of the research study that use of machine learning for enhancing data quality issues detection is a promising area but not yet a panacea which automates this entire process. The third important contribution is a proposed guideline to undertake data repairs most efficiently for Big Data; this involved surveying and comparing existing data cleansing algorithms against a prototype developed for data reparation. Weaknesses of existing algorithms are highlighted and are considered as areas of practice which efficient data reparation algorithms must focus upon. Those three important contributions form the nucleus for a new data quality methodological approach which could be used to optimize Big Data quality, as applied in the context of EHR. Some of the activities and techniques discussed through the proposed methodological approach can be transposed to other industries and use cases to a large extent. The proposed data quality methodological approach can be used by practitioners of Big Data Quality who follow a data-driven strategy. As opposed to existing Big Data quality frameworks, the proposed data quality methodological approach has the advantage of being more precise and specific. It gives clear and proven methods to undertake the main identified stages of a Big Data quality lifecycle and therefore can be applied by practitioners in the area. This research study provides some promising results and deliverables. It also paves the way for further research in the area. Technical and technological changes in Big Data is rapidly evolving and future research should be focusing on new representations of Big Data, the real-time streaming aspect, and replicating same research methods used in this current research study but on new technologies to validate current results

Clinical proteomics for precision medicine: the bladder cancer case

Precision medicine can improve patient management by guiding therapeutic decision based on molecular characteristics. The concept has been extensively addressed through the application of –omics based approaches. Proteomics attract high interest, as proteins reflect a “real-time” dynamic molecular phenotype. Focusing on proteomics applications for personalized medicine, a literature search was conducted to cover: a) disease prevention, b) monitoring/ prediction of treatment response, c) stratification to guide intervention and d) identification of drug targets. The review indicates the potential of proteomics for personalized medicine by also highlighting multiple challenges to be addressed prior to actual implementation. In oncology, particularly bladder cancer, application of precision medicine appears especially promising. The high heterogeneity and recurrence rates together with the limited treatment options, suggests that earlier and more efficient intervention, continuous monitoring and the development of alternative therapies could be accomplished by applying proteomics-guided personalized approaches. This notion is backed by studies presenting biomarkers that are of value in patient stratification and prognosis, and by recent studies demonstrating the identification of promising therapeutic targets. Herein, we aim to present an approach whereby combining the knowledge on biomarkers and therapeutic targets in bladder cancer could serve as basis towards proteomics- guided personalized patient management