Secondary prevention of osteoporosis in Australia: Analysis of government-dispensed prescription data

Background Osteoporosis is a common cause of disability and death in elderly men and women. Until 2007, Australian Government-subsidized use of oral bisphosphonates, raloxifene and calcitriol (1α,25-dihydroxycholecalciferol) was limited to secondary prevention (requiring x-ray evidence of previous low-trauma fracture). The cost to the Pharmaceutical Benefits Scheme was substantial (164 million Australian dollars in 2005/6). Objective To examine the dispensed prescriptions for oral bisphosphonates, raloxifene, calcitriol and two calcium products for the secondary prevention of osteoporosis (after previous low-trauma fracture) in the Australian population. Methods We analysed government data on prescriptions for oral bisphosphonates, raloxifene, calcitriol and two calcium products from 1995 to 2006, and by sex and age from 2002 to 2006. Prescription counts were converted to defined daily doses (DDD)/1000 population/day. This standardized drug utilization method used census population data, and adjusts for the effects of aging in the Australian population. Results Total bisphosphonate use increased 460% from 2.19 to 12.26 DDD/1000 population/day between June 2000 and June 2006. The proportion of total bisphosphonate use in June 2006 was 75.1% alendronate, 24.6% risedronate and 0.3% etidronate. Raloxifene use in June 2006 was 1.32 DDD/1000 population/day. The weekly forms of alendronate and risedronate, introduced in 2001 and 2003, respectively, were quickly adopted. Bisphosphonate use peaked at age 80–89 years in females and 85–94 years in males, with 3-fold higher use in females than in males. Conclusions Pharmaceutical intervention for osteoporosis in Australia is increasing with most use in the elderly, the population at greatest risk of fracture. However, fracture prevalence in this population is considerably higher than prescribing of effective anti-osteoporosis medications, representing a missed opportunity for the quality use of medicines.

Twitter-archive und die Herausforderungen von "Big Social Data" für die Medien- und Kommunikationswissenschaft

Twitter ist eine besonders nützliche Quelle für Social-Media-Daten: mit dem Twitter-API (dem Application Programming Interface, das einen strukturierten Zugang zu Kommunikationsdaten in standardisierten Formaten bietet) ist es Forschern möglich, mit ein wenig Mühe und ausreichenden technische Ressourcen sehr große Archive öffentlich verbreiteter Tweets zu bestimmten Themen, Interessenbereichen, oder Veranstaltungen aufzubauen. Grundsätzlich liefert das API sehr langen Listen von Hunderten, Tausenden oder Millionen von Tweets und den Metadaten zu diesen Tweets; diese Daten können dann auf verschiedentlichste Weise extrahiert, kombiniert, und visualisiert werden, um die Dynamik der Social-Media-Kommunikation zu verstehen. Diese Forschung ist häufig um althergebrachte Fragestellungen herum aufgebaut, wird aber in der Regel in einem bislang unbekannt großen Maßstab durchgeführt. Die Projekte von Medien- und Kommunikationswissenschaftlern wie Papacharissi und de Fatima Oliveira (2012), Wood und Baughman (2012) oder Lotan et al. (2011) – um nur eine Handvoll der letzten Beispiele zu nennen – sind grundlegend auf Twitterdatensätze aufgebaut, die jetzt routinemäßig Millionen von Tweets und zugehörigen Metadaten umfassen, erfaßt nach einer Vielzahl von Kriterien. Was allen diesen Fällen gemein ist, ist jedoch die Notwendigkeit, neue methodische Wege in der Verarbeitung und Analyse derart großer Datensätze zur medienvermittelten sozialen Interaktion zu gehen.

Stop-signal response inhibition in schizophrenia : Behavioural, event-related potential and functional neuroimaging data

Inhibitory control deficits are well documented in schizophrenia, supported by impairment in an established measure of response inhibition, the stop-signal reaction time (SSRT). We investigated the neural basis of this impairment by comparing schizophrenia patients and controls matched for age, sex and education on behavioural, functional magnetic resonance imaging (fMRI) and event-related potential (ERP) indices of stop-signal task performance. Compared to controls, patients exhibited slower SSRT and reduced right inferior frontal gyrus (rIFG) activation, but rIFG activation correlated with SSRT in both groups. Go stimulus and stop-signal ERP components (N1/P3) were smaller in patients, but the peak latencies of stop-signal N1 and P3 were also delayed in patients, indicating impairment early in stop-signal processing. Additionally, response-locked lateralised readiness potentials indicated response preparation was prolonged in patients. An inability to engage rIFG may predicate slowed inhibition in patients, however multiple spatiotemporal irregularities in the networks underpinning stop-signal task performance may contribute to this deficit.

Twitter data: what do they represent?

Scholarly research into the uses of social media has become a major area of growth in recent years, as the adoption of social media for public communication itself has continued apace. While social media platforms provide ready avenues for data access through their Application Programming interfaces, it is increasingly important to think through exactly what these data represent, and what conclusions about the role of social media in society the research which is based on such data therefore enables. This article explores these issues especially for one of the currently leading social media platforms: Twitter.

Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets

Analytically or computationally intractable likelihood functions can arise in complex statistical inferential problems making them inaccessible to standard Bayesian inferential methods. Approximate Bayesian computation (ABC) methods address such inferential problems by replacing direct likelihood evaluations with repeated sampling from the model. ABC methods have been predominantly applied to parameter estimation problems and less to model choice problems due to the added difficulty of handling multiple model spaces. The ABC algorithm proposed here addresses model choice problems by extending Fearnhead and Prangle (2012, Journal of the Royal Statistical Society, Series B 74, 1–28) where the posterior mean of the model parameters estimated through regression formed the summary statistics used in the discrepancy measure. An additional stepwise multinomial logistic regression is performed on the model indicator variable in the regression step and the estimated model probabilities are incorporated into the set of summary statistics for model choice purposes. A reversible jump Markov chain Monte Carlo step is also included in the algorithm to increase model diversity for thorough exploration of the model space. This algorithm was applied to a validating example to demonstrate the robustness of the algorithm across a wide range of true model probabilities. Its subsequent use in three pathogen transmission examples of varying complexity illustrates the utility of the algorithm in inferring preference of particular transmission models for the pathogens.

Meta-analysis of microarray data identifies GAS6 expression as an independent predictor of poor survival in ovarian cancer

Seeking new biomarkers for epithelial ovarian cancer, the fifth most common cause of death from all cancers in women and the leading cause of death from gynaecological malignancies, we performed a meta-analysis of three independent studies and compared the results in regard to clinicopathological parameters. This analysis revealed that GAS6 was highly expressed in ovarian cancer and therefore was selected as our candidate of choice. GAS6 encodes a secreted protein involved in physiological processes including cell proliferation, chemotaxis, and cell survival. We performed immunohistochemistry on various ovarian cancer tissues and found that GAS6 expression was elevated in tumour tissue samples compared to healthy control samples (P < 0.0001). In addition, GAS6 expression was also higher in tumours from patients with residual disease compared to those without. Our data propose GAS6 as an independent predictor of poor survival, suggesting GAS6, both on the mRNA and on the protein level, as a potential biomarker for ovarian cancer. In clinical practice, the staining of a tumour biopsy for GAS6 may be useful to assess cancer prognosis and/or to monitor disease progression.

Improving national hospice/palliative care service symptom outcomes systematically through point-of-care data collection, structured feedback and benchmarking

PURPOSE Every health care sector including hospice/palliative care needs to systematically improve services using patient-defined outcomes. Data from the national Australian Palliative Care Outcomes Collaboration aims to define whether hospice/palliative care patients' outcomes and the consistency of these outcomes have improved in the last 3 years. METHODS Data were analysed by clinical phase (stable, unstable, deteriorating, terminal). Patient-level data included the Symptom Assessment Scale and the Palliative Care Problem Severity Score. Nationally collected point-of-care data were anchored for the period July-December 2008 and subsequently compared to this baseline in six 6-month reporting cycles for all services that submitted data in every time period (n = 30) using individual longitudinal multi-level random coefficient models. RESULTS Data were analysed for 19,747 patients (46 % female; 85 % cancer; 27,928 episodes of care; 65,463 phases). There were significant improvements across all domains (symptom control, family care, psychological and spiritual care) except pain. Simultaneously, the interquartile ranges decreased, jointly indicating that better and more consistent patient outcomes were being achieved. CONCLUSION These are the first national hospice/palliative care symptom control performance data to demonstrate improvements in clinical outcomes at a service level as a result of routine data collection and systematic feedback.

Knowledge management challenges in small-and medium-sized enterprises

Background & Research Focus Managing knowledge for innovation and organisational benefit has been extensively investigated in studies of large firms (Smith, Collins & Clark, 2005; Zucker, et al., 2007) and to a large extent there is limited research into studies of small- and medium- sized enterprises (SMEs). There are some investigations in knowledge management research on SMEs, but what remains to be seen in particular is the question of where are the potential challenges for managing knowledge more effectively within these firms? Effective knowledge management (KM) processes and systems lead to improved performance in pursuing distinct capabilities that contribute to firm-level innovation (Nassim 2009; Zucker et al. 2007; Verona and Ravasi 2003). Managing internal and external knowledge in a way that links it closely to the innovation process can assist the creation and implementation of new products and services. KM is particularly important in knowledge intensive firms where the knowledge requirements are highly specialized, diverse and often emergent. However, to a large extent the KM processes of small firms that are often the source of new knowledge and an important element of the value networks of larger companies have not been closely studied. To address this gap which is of increasing importance with the growing number of small firms, we need to further investigate knowledge management processes and the ways that firms find, capture, apply and integrate knowledge from multiple sources for their innovation process. This study builds on the previous literature and applies existing frameworks and takes the process and activity view of knowledge management as a starting point of departure (see among others Kraaijenbrink, Wijnhoven & Groen, 2007; Enberg, Lindkvist, & Tell, 2006; Lu, Wang & Mao, 2007). In this paper, it is attempted to develop a better understanding of the challenges of knowledge management within the innovation process in small knowledge-oriented firms. The paper aims to explore knowledge management processes and practices in firms that are engaged in the new product/service development programs. Consistent with the exploratory character of the study, the research question is: How is knowledge integrated, sourced and recombined from internal and external sources for innovation and new product development? Research Method The research took an exploratory case study approach and developed a theoretical framework to investigate the knowledge situation of knowledge-intensive firms. Equipped with the conceptual foundation, the research adopted a multiple case study method investigating four diverse Australian knowledge-intensive firms from IT, biotechnology, nanotechnology and biochemistry industries. The multiple case study method allowed us to document in some depth the knowledge management experience of the theses firms. Case study data were collected through a review of company published data and semi-structured interviews with managers using an interview guide to ensure uniform coverage of the research themes. This interview guide was developed following development of the framework and a review of the methodologies and issues covered by similar studies in other countries and used some questions common to these studies. It was framed to gather data around knowledge management activity within the business, focusing on the identification, acquisition and utilisation of knowledge, but collecting a range of information about subject as well. The focus of the case studies was on the use of external and internal knowledge to support their knowledge intensive products and services. Key Findings Firstly a conceptual and strategic knowledge management framework has been developed. The knowledge determinants are related to the nature of knowledge, organisational context, and mechanism of the linkages between internal and external knowledge. Overall, a number of key observations derived from this study, which demonstrated the challenges of managing knowledge and how important KM is as a management tool for innovation process in knowledge-oriented firms. To summarise, findings suggest that knowledge management process in these firms is very much project focused and not embedded within the overall organisational routines and mainly based on ad hoc and informal processes. Our findings highlighted lack of formal knowledge management process within our sampled firms. This point to the need for more specialised capabilities in knowledge management for these firms. We observed a need for an effective knowledge transfer support system which is required to facilitate knowledge sharing and particularly capturing and transferring tacit knowledge from one team members to another. In sum, our findings indicate that building effective and adaptive IT systems to manage and share knowledge in the firm is one of the biggest challenges for these small firms. Also, there is little explicit strategy in small knowledge-intensive firms that is targeted at systematic KM either at the strategic or operational level. Therefore, a strategic approach to managing knowledge for innovation as well as leadership and management are essential to achieving effective KM. In particular, research findings demonstrate that gathering tacit knowledge, internal and external to the organization, and applying processes to ensure the availability of knowledge for innovation teams, drives down the risks and cost of innovation. KM activities and tools, such as KM systems, environmental scanning, benchmarking, intranets, firm-wide databases and communities of practice to acquire knowledge and to make it accessible, were elements of KM. Practical Implications The case study method that used in this study provides practical insight into the knowledge management process within Australian knowledge-intensive firms. It also provides useful lessons which can be used by other firms in managing the knowledge more effectively in the innovation process. The findings would be helpful for small firms that may be searching for a practical method for managing and integrating their specialised knowledge. Using the results of this exploratory study and to address the challenges of knowledge management, this study proposes five practices that are discussed in the paper for managing knowledge more efficiently to improve innovation: (1) Knowledge-based firms must be strategic in knowledge management processes for innovation, (2) Leadership and management should encourage various practices for knowledge management, (3) Capturing and sharing tacit knowledge is critical and should be managed, (4)Team knowledge integration practices should be developed, (5) Knowledge management and integration through communication networks, and technology systems should be encouraged and strengthen. In sum, the main managerial contribution of the paper is the recognition of knowledge determinants and processes, and their effects on the effective knowledge management within firm. This may serve as a useful benchmark in the strategic planning of the firm as it utilises new and specialised knowledge.