Quality of information for quality of life: Healthcare big data analytics

Big data analysis in healthcare sector is still in its early stages when comparing with that of other business sectors due to numerous reasons. Accommodating the volume, velocity and variety of healthcare data Identifying platforms that examine data from multiple sources, such as clinical records, genomic data, financial systems, and administrative systems Electronic Health Record (EHR) is a key information resource for big data analysis and is also composed of varied co-created values. Successful integration and crossing of different subfields of healthcare data such as biomedical informatics and health informatics could lead to huge improvement for the end users of the health care system, i.e. the patients.

Information Accountability of Healthcare Big Data

Huge amount of data are generated from a variety of information sources in healthcare while the data sources originate from a veracity of clinical information systems and corporate data warehouses. The data derived from the above data sources are used for analysis and trending purposes thus playing an influential role as a real time decision-making tool. The unstructured, narrative data provided by these data sources qualify as healthcare big-data and researchers argue that the application of big-data in healthcare might enable the accountability and efficiency.

Resilience: A new integrative approach to health and mental health research

We know from anecdote and research, science and art, that human resilience is a powerful, seemingly ubiquitous force. What is needed is a better understanding of the properties, variations, and applications of that concept to health and well-being. In this paper we put forth two definitions of resilience: Sustainability of purpose in the face of stress, and recovery from adversity. We review current thinking in the social sciences on the nature of biological, psychological and socio-community processes that may confer resilience. In doing so, we encourage greater attention to aspects of biopsychosocial resourcefulness as a dimension of influence on health and mental health distinct from measures of risk found in standard models of public health inquiry. Multi-level, longitudinal, and intervention methods are advocated for research and applications of the concept with conceptual guidelines for the examination of laboratory, diary, and community indicator data on manifestations of resilience across the life span.

Integrating LGBTIQ health personnel in the workplace: A literature review

Aim Lesbian, Gay, Bisexual, Transgender (LGBTIQ) issues have attracted attention in the popular media. The purpose of this study was to explore the workplace acceptance and experiences of LGBTIQ health and medical practitioners. Methods A systematic search of academic databases and reference lists from selected papers were the sources of the data. Inclusion criteria were research papers published in English, which focused on workplace acceptance and experiences of LGBTIQ health personnel. Both authors abstracted data from all eligible papers. Results Thirty-three papers were included in this review. Evidence indicated that LGBTIQ health personnel experienced discrimination from their patients, heterosexual colleagues and within the LGBTIQ community. Positive contribution of LGBTIQ health personnel include improved patient care and role models for LGBTIQ peers. Inclusive policy is required for LGBTIQ health personnel workforce retention. Conclusions There has been improvement in the acceptance and experiences of LGBTIQ health personnel in recent times. An inclusive workplace policy of LGBTIQ embraces and celebrates the value of diversity.

Adopting healthcare big data in Sri Lankan healthcare sector

The concept of big data has already outperformed traditional data management efforts in almost all industries. Other instances it has succeeded in obtaining promising results that provide value from large-scale integration and analysis of heterogeneous data sources for example Genomic and proteomic information. Big data analytics have become increasingly important in describing the data sets and analytical techniques in software applications that are so large and complex due to its significant advantages including better business decisions, cost reduction and delivery of new product and services [1]. In a similar context, the health community has experienced not only more complex and large data content, but also information systems that contain a large number of data sources with interrelated and interconnected data attributes. That have resulted in challenging, and highly dynamic environments leading to creation of big data with its enumerate complexities, for instant sharing of information with the expected security requirements of stakeholders. When comparing big data analysis with other sectors, the health sector is still in its early stages. Key challenges include accommodating the volume, velocity and variety of healthcare data with the current deluge of exponential growth. Given the complexity of big data, it is understood that while data storage and accessibility are technically manageable, the implementation of Information Accountability measures to healthcare big data might be a practical solution in support of information security, privacy and traceability measures. Transparency is one important measure that can demonstrate integrity which is a vital factor in the healthcare service. Clarity about performance expectations is considered to be another Information Accountability measure which is necessary to avoid data ambiguity and controversy about interpretation and finally, liability [2]. According to current studies [3] Electronic Health Records (EHR) are key information resources for big data analysis and is also composed of varied co-created values [3]. Common healthcare information originates from and is used by different actors and groups that facilitate understanding of the relationship for other data sources. Consequently, healthcare services often serve as an integrated service bundle. Although a critical requirement in healthcare services and analytics, it is difficult to find a comprehensive set of guidelines to adopt EHR to fulfil the big data analysis requirements. Therefore as a remedy, this research work focus on a systematic approach containing comprehensive guidelines with the accurate data that must be provided to apply and evaluate big data analysis until the necessary decision making requirements are fulfilled to improve quality of healthcare services. Hence, we believe that this approach would subsequently improve quality of life.

From maternity paper hand-held records to electronic health records: What do women tell us about their use?

The paper hand-held record (PHR) has been used extensively in general practice (GP) shared care management of pregnant women, and recently, the first Mater Shared Electronic Health Record (MSEHR) was introduced. The aim of this qualitative study was to examine women’s experiences using the records and the contribution of the records to integrate care. At the 36-week antenatal visit in a maternity tertiary centre clinic, women were identified as a user of either the PHR or the MSEHR and organised into Phase 1 and Phase 2 studies respectively. Fifteen women were interviewed in Phase 1 and 12 women in Phase 2. Semi-structured interviews were used for data collection, and analysed using qualitative content analysis. Four main themes were identified: (1) purpose of the record; (2) perceptions of the record; (3) content of the record, and; (4) sharing the record. Findings indicate that the PHR is a well-liked maternity tool. The findings also indicate there is under-usage of the MSEHR due to health-care providers failing to follow up and discuss the option of using the electronic health record option or if a woman has completed the log-in process. This paper adds to an already favourable body of knowledge about the use of the PHR. It is recommended that continued implementation of the MSEHR be undertaken to facilitate its use.

A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. © 2013 Mechelli et al.

Cardiovascular disease is increased prior to onset of rheumatoid arthritis but not osteoarthritis: The population-based Nord-Trøndelag health study (HUNT)

Introduction: Patients with rheumatoid arthritis (RA) have increased risk of cardiovascular (CV) events. We sought to test the hypothesis that due to increased inflammation, CV disease and risk factors are associated with increased risk of future RA development. Methods: The population-based Nord-Trøndelag health surveys (HUNT) were conducted among the entire adult population of Nord-Trøndelag, Norway. All inhabitants 20 years or older were invited, and information was collected through comprehensive questionnaires, a clinical examination, and blood samples. In a cohort design, data from HUNT2 (1995-1997, baseline) and HUNT3 (2006-2008, follow-up) were obtained to study participants with RA (n = 786) or osteoarthritis (n = 3,586) at HUNT3 alone, in comparison with individuals without RA or osteoarthritis at both times (n = 33,567). Results: Female gender, age, smoking, body mass index, and history of previous CV disease were associated with self-reported incident RA (previous CV disease: odds ratio 1.52 (95% confidence interval 1.11-2.07). The findings regarding previous CV disease were confirmed in sensitivity analyses excluding participants with psoriasis (odds ratio (OR) 1.70 (1.23-2.36)) or restricting the analysis to cases with a hospital diagnosis of RA (OR 1.90 (1.10-3.27)) or carriers of the shared epitope (OR 1.76 (1.13-2.74)). History of previous CV disease was not associated with increased risk of osteoarthritis (OR 1.04 (0.86-1.27)). Conclusion: A history of previous CV disease was associated with increased risk of incident RA but not osteoarthritis.

Trans-disciplinary research in synthesis of grass pollen aerobiology and its importance for respiratory health in Australasia

Grass pollen is a major trigger for allergic rhinitis and asthma, yet little is known about the timing and levels of human exposure to airborne grass pollen across Australasian urban environments. The relationships between environmental aeroallergen exposure and allergic respiratory disease bridge the fields of ecology, aerobiology, geospatial science and public health. The Australian Aerobiology Working Group comprised of experts in botany, palynology, biogeography, climate change science, plant genetics, biostatistics, ecology, pollen allergy, public and environmental health, and medicine, was established to systematically source, collate and analyse atmospheric pollen concentration data from 11 Australian and six New Zealand sites. Following two week-long workshops, post-workshop evaluations were conducted to reflect upon the utility of this analysis and synthesis approach to address complex multidisciplinary questions. This Working Group described i) a biogeographically dependent variation in airborne pollen diversity, ii) a latitudinal gradient in the timing, duration and number of peaks of the grass pollen season, and iii) the emergence of new methodologies based on trans-disciplinary synthesis of aerobiology and remote sensing data. Challenges included resolving methodological variations between pollen monitoring sites and temporal variations in pollen datasets. Other challenges included “marrying” ecosystem and health sciences and reconciling divergent expert opinion. The Australian Aerobiology Working Group facilitated knowledge transfer between diverse scientific disciplines, mentored students and early career scientists, and provided an uninterrupted collaborative opportunity to focus on a unifying problem globally. The Working Group provided a platform to optimise the value of large existing ecological datasets that have importance for human respiratory health and ecosystems research. Compilation of current knowledge of Australasian pollen aerobiology is a critical first step towards the management of exposure to pollen in patients with allergic disease and provides a basis from which the future impacts of climate change on pollen distribution can be assessed and monitored.

Medical Data Access Accountability in EHR Systems, A Practical Perspective

The world has experienced a large increase in the amount of available data. Therefore, it requires better and more specialized tools for data storage and retrieval and information privacy. Recently Electronic Health Record (EHR) Systems have emerged to fulfill this need in health systems. They play an important role in medicine by granting access to information that can be used in medical diagnosis. Traditional systems have a focus on the storage and retrieval of this information, usually leaving issues related to privacy in the background. Doctors and patients may have different objectives when using an EHR system: patients try to restrict sensible information in their medical records to avoid misuse information while doctors want to see as much information as possible to ensure a correct diagnosis. One solution to this dilemma is the Accountable e-Health model, an access protocol model based in the Information Accountability Protocol. In this model patients are warned when doctors access their restricted data. They also enable a non-restrictive access for authenticated doctors. In this work we use FluxMED, an EHR system, and augment it with aspects of the Information Accountability Protocol to address these issues. The Implementation of the Information Accountability Framework (IAF) in FluxMED provides ways for both patients and physicians to have their privacy and access needs achieved. Issues related to storage and data security are secured by FluxMED, which contains mechanisms to ensure security and data integrity. The effort required to develop a platform for the management of medical information is mitigated by the FluxMED's workflow-based architecture: the system is flexible enough to allow the type and amount of information being altered without the need to change in your source code.

A randomized controlled trial of a multiple health behavior change intervention delivered to colorectal cancer survivors: Effects on sedentary behavior

BACKGROUND Sedentary behavior may independently contribute to morbidity and mortality among survivors of colorectal cancer. In the current study, the authors assessed whether a telephone-delivered multiple health behavior change intervention had an effect on the sedentary behavior of recently diagnosed colorectal cancer survivors. METHODS A total of 410 participants were recruited through the Queensland Cancer Registry and randomized to the health coaching (intervention) or usual-care (control) group. Eleven health coaching sessions addressing multiple health behaviors, including sedentary behavior, were delivered over a period of 6 months. Data were collected at baseline (before randomization), at 6 months, and at 12 months via a telephone interview. RESULTS At 12 months, there was a significant decrease noted in the hours per day of sedentary time in both the health coaching (−1.21; 95% confidence interval [95% CI], −1.71 to −0.70) and usual-care groups (−0.55; 95% CI, −1.06 to −0.05), but the between-group difference was not found to be statistically significant (−0.65; 95% CI, −1.37 to 0.06 [P = .07]). In stratified subgroup analyses, the multiple health behavior change intervention was found to have a significant effect on total sedentary time (hours/day) at 12 months in survivors of colorectal cancer who were aged > 60 years (−0.90; 95% CI, −1.80 to −0.01 [P = .05]), male (−1.33; 95% CI, −2.44 to −0.21 [P = .02]), and nonobese (−1.10; 95% CI, −1.96 to −0.25; [P = .01]). CONCLUSIONS Incorporating simple messages about limiting sedentary behaviors into a multiple health behavior change intervention was found to have modest effects on sedentary behavior. A sedentary behavior-specific intervention strategy may be required to achieve substantial changes in sedentary behavior among colorectal cancer survivors

Workplace stress: What is the role of positive mental health?

Objective: To examine whether positive mental health (PMH)—a positively focused well-being construct—moderates the job stress–distress relationship. Methods: Longitudinal regression was used to test two waves of matched, population-level data from a sample of older, working Australian adults (n = 3291) to see whether PMH modified the relationship between work stress and later psychological distress. Results: Time 1 work stress was positively associated with distress at both time points. Positive mental health was negatively associated with work stress at both time points. Positive mental health modified the impact of work stress on psychological distress. This effect only occurred for those with the highest levels of PMH. Conclusions: Positive mental health may help protect workers from the effect of workplace stress but only in a small proportion of the population. Therefore, to improve workplace mental health, workplaces need to both prevent stress and promote PMH.

Creating change in government to address the social determinants of health: How can efforts be improved?

Background The evidence base for the impact of social determinants of health has been strengthened considerably in the last decade. Increasingly, the public health field is using this as a foundation for arguments and actions to change government policies. The Health in All Policies (HiAP) approach, alongside recommendations from the 2010 Marmot Review into health inequalities in the UK (which we refer to as the ‘Fairness Agenda’), go beyond advocating for the redesign of individual policies, to shaping the government structures and processes that facilitate the implementation of these policies. In doing so, public health is drawing on recent trends in public policy towards ‘joined up government’, where greater integration is sought between government departments, agencies and actors outside of government. Methods In this paper we provide a meta-synthesis of the empirical public policy research into joined up government, drawing out characteristics associated with successful joined up initiatives. We use this thematic synthesis as a basis for comparing and contrasting emerging public health interventions concerned with joined-up action across government. Results We find that HiAP and the Fairness Agenda exhibit some of the characteristics associated with successful joined up initiatives, however they also utilise ‘change instruments’ that have been found to be ineffective. Moreover, we find that – like many joined up initiatives – there is room for improvement in the alignment between the goals of the interventions and their design. Conclusion Drawing on public policy studies, we recommend a number of strategies to increase the efficacy of current interventions. More broadly, we argue that up-stream interventions need to be ‘fit-for-purpose’, and cannot be easily replicated from one context to the next.

Data driven modeling for power transformer lifespan evaluation

Large sized power transformers are important parts of the power supply chain. These very critical networks of engineering assets are an essential base of a nation’s energy resource infrastructure. This research identifies the key factors influencing transformer normal operating conditions and predicts the asset management lifespan. Engineering asset research has developed few lifespan forecasting methods combining real-time monitoring solutions for transformer maintenance and replacement. Utilizing the rich data source from a remote terminal unit (RTU) system for sensor-data driven analysis, this research develops an innovative real-time lifespan forecasting approach applying logistic regression based on the Weibull distribution. The methodology and the implementation prototype are verified using a data series from 161 kV transformers to evaluate the efficiency and accuracy for energy sector applications. The asset stakeholders and suppliers significantly benefit from the real-time power transformer lifespan evaluation for maintenance and replacement decision support.

Occupational injury risk among Australian paramedics: An analysis of national data

Objective To identify the occupational risks for Australian paramedics, by describing the rate of injuries and fatalities and comparing those rates with other reports. Design and participants Retrospective descriptive study using data provided by Safe Work Australia for the period 2000–2010. The subjects were paramedics who had been injured in the course of their duties and for whom a claim had been made for workers compensation payments. Main outcome measures Rates of injury calculated from the data provided. Results The risk of serious injury among Australian paramedics was found to be more than seven times higher than the Australian national average. The fatality rate for paramedics was about six times higher than the national average. On average, every 2 years during the study period, one paramedic died and 30 were seriously injured in vehicle crashes. Ten Australian paramedics were seriously injured each year as a result of an assault. The injury rate for paramedics was more than two times higher than the rate for police officers. Conclusions The high rate of occupational injuries and fatalities among paramedics is a serious public health issue. The risk of injury in Australia is similar to that in the United States. While it may be anticipated that injury rates would be higher as a result of the nature of the work and environment of paramedics, further research is necessary to identify and validate the strategies required to minimise the rates of occupational injury for paramedics.