Radical nursing and the emergence of technique as healthcare technology

The integration of technology in care is core business in nursing and this role requires that we must understand and use technology informed by evidence that goes much deeper and broader than actions and behaviours. We need to delve more deeply into its complexity because there is nothing minor or insignificant about technology as a major influence in healthcare outcomes and experiences. Evidence is needed that addresses technology and nursing from perspectives that examine the effects of technology, especially related to increasing demands for efficiency, the relationship of technology to nursing and caring, and a range of philosophical questions associated with empowering people in their healthcare choices. Specifically, there is a need to confront in practice the ways technique influences care. Technique is the creation of a kind of thinking that is necessary for contemporary healthcare technology to develop and be applied in an efficient and rational manner. Technique is not an entity or specific thing, but rather a way of thinking that seeks to shape and organize nursing activity, and manage efficiently individual difference(s) in care. It emphasizes predetermined causal relationships, conformity, and sameness of product, process, and thought. In response is needed a radical vision of nursing that attempts in a real sense to ensure we meet the needs of individuals and their community. Activism and advocacy are needed, and a willingness to create a certain detachment from the imperatives that technique demands. It is argued that our responsibility as nurses is to respond in practice to the errors, advantages, difficulties, and temptations of technology for the benefit of those who most need our assistance and care.

Managing healthcare technology in quality management framework

Healthcare services available these days deploy high technology to satisfy both internal and external customers by continuously improving various quality parameters. Quality improvement in healthcare services is a complex and multidimensional task. Although various quality management tools are routinely deployed for identifying quality issues in healthcare delivery, there is absence of an integrated approach, which can identify and analyse issues, provide solutions to resolve those issues and develop a project management framework to implement and evaluate those solutions. This study introduces an integrated and uniform quality management framework for healthcare services. This study uses the Logical Framework Analysis (LFA) to improve the performance of healthcare services. LFA has three major steps - problem identification, solution derivation and formation of a planning matrix for implementation and evaluation. LFA has been applied in a case study environment to three acute healthcare services (Operating Room (OR) utilisation, Accident and Emergency (A&E) and intensive care) in order to demonstrate its effectiveness. Copyright © 2007 Inderscience Enterprises Ltd.

Managing healthcare quality using combined SWOT and the analytic process

Improving healthcare quality is a growing need of any society. Although various quality improvement projects are routinely deployed by the healthcare professional, they are characterised by a fragmented approach, i.e. they are not linked with the strategic intent of the organisation. This study introduces a framework which integrates all quality improvement projects with the strategic intent of the organisation. It first derives the strengths, weaknesses, opportunities and threats (SWOT) matrix of the system with the involvement of the concerned stakeholders (clinical professional), which helps identify a few projects, the implementation of which ensures achievement of desired quality. The projects are then prioritised using the analytic hierarchy process with the involvement of the concerned stakeholders (clinical professionals) and implemented in order to improve system performance. The effectiveness of the method has been demonstrated using a case study in the intensive care unit of Queen Elizabeth Hospital in Bridgetown, Barbados.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Moving tele-monitoring and tele-treatment from promise to practice : a business model approach for a chronic lower back pain application

The availability of new information and communication technologies creates opportunities for new, mobile tele-health services. While many promising tele-health projects deliver working R&D prototypes, they often do not result in actual deployment. We aim to identify critical issues than can increase our understanding and enhance the viability of the mobile tele-health services beyond the R&D phase by developing a business model. The present study describes the systematic development and evaluation of a service-oriented business model for tele-monitoring and -treatment of chronic lower back pain patients based on a mobile technology prototype. We address challenges of multi-sector collaboration and disruptive innovation.

Cardiac health diagnosis using higher order spectra and support vector machine

The Electrocardiogram (ECG) is an important bio-signal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. The HRV signal can be used as a base signal to observe the heart's functioning. These signals are non-linear and non-stationary in nature. So, higher order spectral (HOS) analysis, which is more suitable for non-linear systems and is robust to noise, was used. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, we have extracted seven features from the heart rate signals using HOS and fed them to a support vector machine (SVM) for classification. Our performance evaluation protocol uses 330 subjects consisting of five different kinds of cardiac disease conditions. We demonstrate a sensitivity of 90% for the classifier with a specificity of 87.93%. Our system is ready to run on larger data sets.

Methodology for Validating Artifact Removal Techniques for Physiological Signals

Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods for this process has become particularly acute as healthcare technology deployment undergoes transition from the current hospital-centric setting toward a wearable and ubiquitous monitoring environment. Currently, determining the relative efficacy and performance of the multiple artifact removal techniques available on real world data can be problematic, due to incomplete information on the uncorrupted desired signal. The majority of techniques are presently evaluated using simulated data, and therefore, the quality of the conclusions is contingent on the fidelity of the model used. Consequently, in the biomedical signal processing community, there is considerable focus on the generation and validation of appropriate signal models for use in artifact suppression. Most approaches rely on mathematical models which capture suitable approximations to the signal dynamics or underlying physiology and, therefore, introduce some uncertainty to subsequent predictions of algorithm performance. This paper describes a more empirical approach to the modeling of the desired signal that we demonstrate for functional brain monitoring tasks which allows for the procurement of a ground truth signal which is highly correlated to a true desired signal that has been contaminated with artifacts. The availability of this ground truth, together with the corrupted signal, can then aid in determining the efficacy of selected artifact removal techniques. A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform. © 2012 IEEE.

Introdução e difusão de novas tecnologias : impacto do financiamento e do estatuto jurídico hospitalar

RESUMO - Os gastos com a saúde, em Portugal, como nos países da União Europeia e da OCDE, têm crescido a um ritmo superior ao do crescimento económico, assumindo uma importância crescente face ao PIB. Entre estes factores surge a velocidade da introdução da inovação e dos desenvolvimentos tecnológicos dos domínios do diagnóstico e da terapêutica. Uma das mais difíceis e importantes questões para as políticas de saúde é a relação entre a saúde e os gastos com a prestação de cuidados de saúde. Estudos recentes sugerem que os cuidados de saúde ocupam um papel importante na melhoria da saúde da população, e que os recentes avanços tecnológicos são custo-efectivos aceites na generalidade por cada ano de vida ganho. Este trabalho visa estudar a influência que o financiamento e o estatuto jurídico hospitalar têm na introdução e adopção de novas tecnologias em saúde. Para isso, além da revisão bibliográfica, foi realizada uma análise a uma base de dados, cujos elementos se cingem a pacientes com doenças cardiovasculares atendidos num dos hospitais do Serviço Nacional de Saúde, entre 2000 e 2006. --- ------------------------------------ABSTRACT - Health expenditures in Portugal, as in EU countries and in the OECD, have developed at a higher rate than economic growth, assuming an increasing importance to the GDP. Among these factors appears the speed of the introduction of innovation and technological development in diagnosis and therapy areas. One of the most difficult and most important questions for health policy is the relationship of health to health care spending. Studies now suggest that medical care has played an important role in improving the health of the population, and recent technical advances are cost-effective at generally accepted values of an added year of life. This work aims to study the influence that the prospective payment and the hospital’s legal status have in introduction and adoption of new technologies in health. For this, besides the literature review, an analysis was made to a database, whose elements are confined to patients with cardiovascular disease treated in the hospitals of t

Potential of telemedicine : a preliminary evaluation through the innovation diffusion lens

With the rapid diffusion of innovative technologies in the healthcare industry, the potential of telemedicine has increasingly come into focus. Touted as a catalyst for an equitable healthcare framework among nations, research is wide and one spotlight is on the potential of this innovation to diffuse among the wider society. In this paper, we attempt a preliminary evaluation of the potential of telemedicine through the components of [Diffusion of Innovations (4th ed.). NY: The Free Press] diffusion of innovations theoretical lens, drawing also as relevant from reported literature. We expect that this preliminary evaluation will facilitate further academic research and make other stakeholders, such as regulators, medical practitioners, telecommunication providers and vendors, aware of potential steps to be taken to leverage telemedicine diffusion.

A experiência do cuidador familiar e da equipe multiprofissional com processo de cuidar de doentes renais crônicos em hemodiálise

Pós-graduação em Enfermagem (mestrado profissional) - FMB

Genetic association of CD247 (CD3ζ) with SLE in a large-scale multiethnic study

A classic T-cell phenotype in systemic lupus erythematosus (SLE) is the downregulation and replacement of the CD3ζ chain that alters T-cell receptor signaling. However, genetic associations with SLE in the human CD247 locus that encodes CD3ζ are not well established and require replication in independent cohorts. Our aim was therefore to examine, localize and validate CD247-SLE association in a large multiethnic population. We typed 44 contiguous CD247 single-nucleotide polymorphisms (SNPs) in 8922 SLE patients and 8077 controls from four ethnically distinct populations. The strongest associations were found in the Asian population (11 SNPs in intron 1, 4.99 × 10(-4) < P < 4.15 × 10(-2)), where we further identified a five-marker haplotype (rs12141731-rs2949655-rs16859085-rs12144621-rs858554; G-G-A-G-A; P(hap) = 2.12 × 10(-5)) that exceeded the most associated single SNP rs858554 (minor allele frequency in controls = 13%; P = 4.99 × 10(-4), odds ratio = 1.32) in significance. Imputation and subsequent association analysis showed evidence of association (P < 0.05) at 27 additional SNPs within intron 1. Cross-ethnic meta-analysis, assuming an additive genetic model adjusted for population proportions, showed five SNPs with significant P-values (1.40 × 10(-3) < P< 3.97 × 10(-2)), with one (rs704848) remaining significant after Bonferroni correction (P(meta) = 2.66 × 10(-2)). Our study independently confirms and extends the association of SLE with CD247, which is shared by various autoimmune disorders and supports a common T-cell-mediated mechanism.

Understanding the Diversity of User Requirements for Interactive Online Health Services

Peer reviewed

Clinical factors and technological barriers as determinants for the intention to use wireless handheld technology in healthcare environment: an Indian case study

Abstract]: Traditional technology adoption models identified ‘ease of use’ and ‘usefulness’ as the dominating factors for technology adoption. However, recent studies in healthcare have established that these two factors are not always reliable on their own and other factors may influence technology adoption. To establish the identity of these additional factors, a mixed method approach was used and data were collected through interviews and a survey. The survey instrument was specifically developed for this study so that it is relevant to the Indian healthcare setting. We identified clinical management and technological barriers as the dominant factors influencing the wireless handheld technology adoption in the Indian healthcare environment. The results of this study showed that new technology models will benefit by considering the clinical influences of wireless handheld technology, in addition to known factors. The scope of this study is restricted to wireless handheld devices such as PDAs, smart phones, and handheld PCs Gururajan, Raj and Hafeez-Baig, Abdul and Gururajan, Vijaya

Examining the post-adoptive infusion of mobile technology in a healthcare domain: determinants and outcomes

The healthcare industry is beginning to appreciate the benefits which can be obtained from using Mobile Health Systems (MHS) at the point-of-care. As a result, healthcare organisations are investing heavily in mobile health initiatives with the expectation that users will employ the system to enhance performance. Despite widespread endorsement and support for the implementation of MHS, empirical evidence surrounding the benefits of MHS remains to be fully established. For MHS to be truly valuable, it is argued that the technological tool be infused within healthcare practitioners work practices and used to its full potential in post-adoptive scenarios. Yet, there is a paucity of research focusing on the infusion of MHS by healthcare practitioners. In order to address this gap in the literature, the objective of this study is to explore the determinants and outcomes of MHS infusion by healthcare practitioners. This research study adopts a post-positivist theory building approach to MHS infusion. Existing literature is utilised to develop a conceptual model by which the research objective is explored. Employing a mixed-method approach, this conceptual model is first advanced through a case study in the UK whereby propositions established from the literature are refined into testable hypotheses. The final phase of this research study involves the collection of empirical data from a Canadian hospital which supports the refined model and its associated hypotheses. The results from both phases of data collection are employed to develop a model of MHS infusion. The study contributes to IS theory and practice by: (1) developing a model with six determinants (Availability, MHS Self-Efficacy, Time-Criticality, Habit, Technology Trust, and Task Behaviour) and individual performance-related outcomes of MHS infusion (Effectiveness, Efficiency, and Learning), (2) examining undocumented determinants and relationships, (3) identifying prerequisite conditions that both healthcare practitioners and organisations can employ to assist with MHS infusion, (4) developing a taxonomy that provides conceptual refinement of IT infusion, and (5) informing healthcare organisations and vendors as to the performance of MHS in post-adoptive scenarios.