Economics and preventing healthcare acquired infection

The evolution of organisms that cause healthcare acquired infections (HAI) puts extra stress on hospitals already struggling with rising costs and demands for greater productivity and cost containment. Infection control can save scarce resources, lives, and possibly a facility’s reputation, but statistics and epidemiology are not always sufficient to make the case for the added expense. Economics and Preventing Healthcare Acquired Infection presents a rigorous analytic framework for dealing with this increasingly serious problem. ----- Engagingly written for the economics non-specialist, and brimming with tables, charts, and case examples, the book lays out the concepts of economic analysis in clear, real-world terms so that infection control professionals or infection preventionists will gain competence in developing analyses of their own, and be confident in the arguments they present to decision-makers. The authors: ----- Ground the reader in the basic principles and language of economics. ----- Explain the role of health economists in general and in terms of infection prevention and control. ----- Introduce the concept of economic appraisal, showing how to frame the problem, evaluate and use data, and account for uncertainty. ----- Review methods of estimating and interpreting the costs and health benefits of HAI control programs and prevention methods. ----- Walk the reader through a published economic appraisal of an infection reduction program. ----- Identify current and emerging applications of economics in infection control. ---- Economics and Preventing Healthcare Acquired Infection is a unique resource for practitioners and researchers in infection prevention, control and healthcare economics. It offers valuable alternate perspective for professionals in health services research, healthcare epidemiology, healthcare management, and hospital administration. ----- Written for: Professionals and researchers in infection control, health services research, hospital epidemiology, healthcare economics, healthcare management, hospital administration; Association of Professionals in Infection Control (APIC), Society for Healthcare Epidemiologists of America (SHEA)

Krylov subspace methods for approximating functions of symmetric positive definite matrices with applications to applied statistics and anomalous diffusion

Matrix function approximation is a current focus of worldwide interest and finds application in a variety of areas of applied mathematics and statistics. In this thesis we focus on the approximation of A^(-α/2)b, where A ∈ ℝ^(n×n) is a large, sparse symmetric positive definite matrix and b ∈ ℝ^n is a vector. In particular, we will focus on matrix function techniques for sampling from Gaussian Markov random fields in applied statistics and the solution of fractional-in-space partial differential equations. Gaussian Markov random fields (GMRFs) are multivariate normal random variables characterised by a sparse precision (inverse covariance) matrix. GMRFs are popular models in computational spatial statistics as the sparse structure can be exploited, typically through the use of the sparse Cholesky decomposition, to construct fast sampling methods. It is well known, however, that for sufficiently large problems, iterative methods for solving linear systems outperform direct methods. Fractional-in-space partial differential equations arise in models of processes undergoing anomalous diffusion. Unfortunately, as the fractional Laplacian is a non-local operator, numerical methods based on the direct discretisation of these equations typically requires the solution of dense linear systems, which is impractical for fine discretisations. In this thesis, novel applications of Krylov subspace approximations to matrix functions for both of these problems are investigated. Matrix functions arise when sampling from a GMRF by noting that the Cholesky decomposition A = LL^T is, essentially, a `square root' of the precision matrix A. Therefore, we can replace the usual sampling method, which forms x = L^(-T)z, with x = A^(-1/2)z, where z is a vector of independent and identically distributed standard normal random variables. Similarly, the matrix transfer technique can be used to build solutions to the fractional Poisson equation of the form ϕn = A^(-α/2)b, where A is the finite difference approximation to the Laplacian. Hence both applications require the approximation of f(A)b, where f(t) = t^(-α/2) and A is sparse. In this thesis we will compare the Lanczos approximation, the shift-and-invert Lanczos approximation, the extended Krylov subspace method, rational approximations and the restarted Lanczos approximation for approximating matrix functions of this form. A number of new and novel results are presented in this thesis. Firstly, we prove the convergence of the matrix transfer technique for the solution of the fractional Poisson equation and we give conditions by which the finite difference discretisation can be replaced by other methods for discretising the Laplacian. We then investigate a number of methods for approximating matrix functions of the form A^(-α/2)b and investigate stopping criteria for these methods. In particular, we derive a new method for restarting the Lanczos approximation to f(A)b. We then apply these techniques to the problem of sampling from a GMRF and construct a full suite of methods for sampling conditioned on linear constraints and approximating the likelihood. Finally, we consider the problem of sampling from a generalised Matern random field, which combines our techniques for solving fractional-in-space partial differential equations with our method for sampling from GMRFs.

Asia

Reporters sans frontiéres (RSF) has repeatedly declared Asia to be the most demanding continent for journalists and their news organizations to operate in, and in some countries, even simply to survive in. The many reports issued by RSF and other global agencies regularly show Asia to be the region in which the largest number of murders of journalists occur per year, even when Asian–Arabic states and Central Asia are not included in the definition of ‘Asia’. The reports describe numerous physical, legal and economic threats as well as serious political repression and restrictions that journalists face as they attempt to function as watch-dogs, agenda-setters and gate-keepers for their societies. The statistics and examples provided within these reports, however, do not provide the full picture. Most Asian nations also host vibrant media cultures in which journalists play an important role in supporting social and democratic processes and activities. This chapter outlines the political and economic influences on Asian journalism; the impact of new technologies; the debates about philosophies such as 'development journalism', 'peace journalism' and 'Asian values'; and the influence of the so-called 'envelope culture' or practices of gift-giving and bribery that pervade journalism in some countries. To illustrate how these principles affect journalists' practice, the chapter presents a comparison of the starkly contrasting situations in India versus North Korea (Democratic People's Republic of Korea). The chapter also describes issues affecting countries as far afield as China to Kazakhstan, including a short case study of journalism during the so-called Saffron Revolution in Burma in 2007. The chapter concludes with suggestions about how training and aid for the Asian should be contextualized to take into account the specific cultural, economic and political factors that shape and limit the media’s performance, and how journalists might be best placed to negotiate around them. Such training needs to be sensitive to valid variations in perceptions of what kind of governance and journalism best serves development, without serving politically motivated rhetoric.

Why creative industries matter to economic evolution

This paper proposes that the 'creative industries'(CIs) play an important yet widely unexamined function in economic evolution through their role in the innovation process. This occurs in terms of the facilitation of demand for novelty, the provision and development of social technologies for producer-consumer interactions, and the adoption and embedding of new technologies as institutions. The incorporation of CIs into the Schumpeterian model of economic evolution thus fills a notable gap in the social technologies of the origination, adoption and retention of innovation.

Spatial analysis of notified cryptosporidiosis infections in Brisbane, Australia

Purpose: This study explored the spatial distribution of notified cryptosporidiosis cases and identified major socioeconomic factors associated with the transmission of cryptosporidiosis in Brisbane, Australia. Methods: We obtained the computerized data sets on the notified cryptosporidiosis cases and their key socioeconomic factors by statistical local area (SLA) in Brisbane for the period of 1996 to 2004 from the Queensland Department of Health and Australian Bureau of Statistics, respectively. We used spatial empirical Bayes rates smoothing to estimate the spatial distribution of cryptosporidiosis cases. A spatial classification and regression tree (CART) model was developed to explore the relationship between socioeconomic factors and the incidence rates of cryptosporidiosis. Results: Spatial empirical Bayes analysis reveals that the cryptosporidiosis infections were primarily concentrated in the northwest and southeast of Brisbane. A spatial CART model shows that the relative risk for cryptosporidiosis transmission was 2.4 when the value of the social economic index for areas (SEIFA) was over 1028 and the proportion of residents with low educational attainment in an SLA exceeded 8.8%. Conclusions: There was remarkable variation in spatial distribution of cryptosporidiosis infections in Brisbane. Spatial pattern of cryptosporidiosis seems to be associated with SEIFA and the proportion of residents with low education attainment.

A multilevel study of area socio-economic status and food purchasing behaviour

Objective: This study examined the association between area socioeconomic status (SES) and food purchasing behaviour.----- Setting: Melbourne city, Australia, 2003.----- Participants: Residents of 2,564 households located in 50 small areas.----- Design: Data were collected by mail survey (64.2% response rate). Area SES was indicated by the proportion of households in each area earning less than Aus$400 per week, and individual-level socioeconomic position was measured using education, occupation, and household income. Food purchasing was measured on the basis of compliance with dietary guideline recommendations (for grocery foods) and variety of fruit and vegetable purchase. Multilevel regression examined the association between area SES and food purchase after adjustment for individual-level demographic (age, sex, household composition) and socioeconomic factors.----- Results: Residents of low SES areas were significantly less likely than their counterparts in advantaged areas to purchase grocery foods that were high in fibre and low in fat, salt, and sugar; and they purchased a smaller variety of fruits. There was no evidence of an association between area SES and vegetable variety.----- Conclusions In Melbourne, area SES was associated with some food purchasing behaviours independent of individual-level factors, suggesting that areas in this city may be differentiated on the basis of food availability, accessibility, and affordability, making the purchase of some types of foods more difficult in disadvantaged areas.

Value-mapping for major economic infrastructure projects

The establishment of corporate objectives regarding economic, environmental, social, and ethical responsibilities, to inform business practice, has been gaining credibility in the business sector since the early 1990’s. This is witnessed through (i) the formation of international forums for sustainable and accountable development, (ii) the emergence of standards, systems, and frameworks to provide common ground for regulatory and corporate dialogue, and (iii) the significant quantum of relevant popular and academic literature in a diverse range of disciplines. How then has this move towards greater corporate responsibility become evident in the provision of major urban infrastructure projects? The gap identified, in both academic literature and industry practice, is a structured and auditable link between corporate intent and project outcomes. Limited literature has been discovered which makes a link between corporate responsibility; project performance indicators (or critical success factors) and major infrastructure provision. This search revealed that a comprehensive mapping framework, from an organisation’s corporate objectives through to intended, anticipated and actual outcomes and impacts has not yet been developed for the delivery of such projects. The research problem thus explored is ‘the need to better identify, map and account for the outcomes, impacts and risks associated with economic, environmental, social and ethical outcomes and impacts which arise from major economic infrastructure projects, both now, and into the future’. The methodology being used to undertake this research is based on Checkland’s soft system methodology, engaging in action research on three collaborative case studies. A key outcome of this research is a value-mapping framework applicable to Australian public sector agencies. This is a decision-making methodology which will enable project teams responsible for delivering major projects, to better identify and align project objectives and impacts with stated corporate objectives.

Socio-environmental factors and suicide in Queensland, Australia

Suicide has drawn much attention from both the scientific community and the public. Examining the impact of socio-environmental factors on suicide is essential in developing suicide prevention strategies and interventions, because it will provide health authorities with important information for their decision-making. However, previous studies did not examine the impact of socio-environmental factors on suicide using a spatial analysis approach. The purpose of this study was to identify the patterns of suicide and to examine how socio-environmental factors impact on suicide over time and space at the Local Governmental Area (LGA) level in Queensland. The suicide data between 1999 and 2003 were collected from the Australian Bureau of Statistics (ABS). Socio-environmental variables at the LGA level included climate (rainfall, maximum and minimum temperature), Socioeconomic Indexes for Areas (SEIFA) and demographic variables (proportion of Indigenous population, unemployment rate, proportion of population with low income and low education level). Climate data were obtained from Australian Bureau of Meteorology. SEIFA and demographic variables were acquired from ABS. A series of statistical and geographical information system (GIS) approaches were applied in the analysis. This study included two stages. The first stage used average annual data to view the spatial pattern of suicide and to examine the association between socio-environmental factors and suicide over space. The second stage examined the spatiotemporal pattern of suicide and assessed the socio-environmental determinants of suicide, using more detailed seasonal data. In this research, 2,445 suicide cases were included, with 1,957 males (80.0%) and 488 females (20.0%). In the first stage, we examined the spatial pattern and the determinants of suicide using 5-year aggregated data. Spearman correlations were used to assess associations between variables. Then a Poisson regression model was applied in the multivariable analysis, as the occurrence of suicide is a small probability event and this model fitted the data quite well. Suicide mortality varied across LGAs and was associated with a range of socio-environmental factors. The multivariable analysis showed that maximum temperature was significantly and positively associated with male suicide (relative risk [RR] = 1.03, 95% CI: 1.00 to 1.07). Higher proportion of Indigenous population was accompanied with more suicide in male population (male: RR = 1.02, 95% CI: 1.01 to 1.03). There was a positive association between unemployment rate and suicide in both genders (male: RR = 1.04, 95% CI: 1.02 to 1.06; female: RR = 1.07, 95% CI: 1.00 to 1.16). No significant association was observed for rainfall, minimum temperature, SEIFA, proportion of population with low individual income and low educational attainment. In the second stage of this study, we undertook a preliminary spatiotemporal analysis of suicide using seasonal data. Firstly, we assessed the interrelations between variables. Secondly, a generalised estimating equations (GEE) model was used to examine the socio-environmental impact on suicide over time and space, as this model is well suited to analyze repeated longitudinal data (e.g., seasonal suicide mortality in a certain LGA) and it fitted the data better than other models (e.g., Poisson model). The suicide pattern varied with season and LGA. The north of Queensland had the highest suicide mortality rate in all the seasons, while there was no suicide case occurred in the southwest. Northwest had consistently higher suicide mortality in spring, autumn and winter. In other areas, suicide mortality varied between seasons. This analysis showed that maximum temperature was positively associated with suicide among male population (RR = 1.24, 95% CI: 1.04 to 1.47) and total population (RR = 1.15, 95% CI: 1.00 to 1.32). Higher proportion of Indigenous population was accompanied with more suicide among total population (RR = 1.16, 95% CI: 1.13 to 1.19) and by gender (male: RR = 1.07, 95% CI: 1.01 to 1.13; female: RR = 1.23, 95% CI: 1.03 to 1.48). Unemployment rate was positively associated with total (RR = 1.40, 95% CI: 1.24 to 1.59) and female (RR=1.09, 95% CI: 1.01 to 1.18) suicide. There was also a positive association between proportion of population with low individual income and suicide in total (RR = 1.28, 95% CI: 1.10 to 1.48) and male (RR = 1.45, 95% CI: 1.23 to 1.72) population. Rainfall was only positively associated with suicide in total population (RR = 1.11, 95% CI: 1.04 to 1.19). There was no significant association for rainfall, minimum temperature, SEIFA, proportion of population with low educational attainment. The second stage is the extension of the first stage. Different spatial scales of dataset were used between the two stages (i.e., mean yearly data in the first stage, and seasonal data in the second stage), but the results are generally consistent with each other. Compared with other studies, this research explored the variety of the impact of a wide range of socio-environmental factors on suicide in different geographical units. Maximum temperature, proportion of Indigenous population, unemployment rate and proportion of population with low individual income were among the major determinants of suicide in Queensland. However, the influence from other factors (e.g. socio-culture background, alcohol and drug use) influencing suicide cannot be ignored. An in-depth understanding of these factors is vital in planning and implementing suicide prevention strategies. Five recommendations for future research are derived from this study: (1) It is vital to acquire detailed personal information on each suicide case and relevant information among the population in assessing the key socio-environmental determinants of suicide; (2) Bayesian model could be applied to compare mortality rates and their socio-environmental determinants across LGAs in future research; (3) In the LGAs with warm weather, high proportion of Indigenous population and/or unemployment rate, concerted efforts need to be made to control and prevent suicide and other mental health problems; (4) The current surveillance, forecasting and early warning system needs to be strengthened, to trace the climate and socioeconomic change over time and space and its impact on population health; (5) It is necessary to evaluate and improve the facilities of mental health care, psychological consultation, suicide prevention and control programs; especially in the areas with low socio-economic status, high unemployment rate, extreme weather events and natural disasters.

A review of the economic consequences of a policy of universal leucodepletion as compared to existing practices

Leucodepletion, the removal of leucocytes from blood products improves the safety of blood transfusion by reducing adverse events associated with the incidental non-therapeutic transfusion of leucocytes. Leucodepletion has been shown to have clinical benefit for immuno-suppressed patients who require transfusion. The selective leucodepletion of blood products by bed side filtration for these patients has been widely practiced. This study investigated the economic consequences in Queensland of moving from a policy of selective leucodepletion to one of universal leucodepletion, that is providing all transfused patients with blood products leucodepleted during the manufacturing process. Using an analytic decision model a cost-effectiveness analysis was conducted. An ICER of $16.3M per life year gained was derived. Sensitivity analysis found this result to be robust to uncertainty in the parameters used in the model. This result argues against moving to a policy of universal leucodepletion. However during the course of the study the policy decision for universal leucodepletion was made and implemented in Queensland in October 2008. This study has concluded that cost-effectiveness is not an influential factor in policy decisions regarding quality and safety initiatives in the Australian blood sector.

The statistics of refractive error maps : managing wavefront aberration analysis without Zernike polynomials

The refractive error of a human eye varies across the pupil and therefore may be treated as a random variable. The probability distribution of this random variable provides a means for assessing the main refractive properties of the eye without the necessity of traditional functional representation of wavefront aberrations. To demonstrate this approach, the statistical properties of refractive error maps are investigated. Closed-form expressions are derived for the probability density function (PDF) and its statistical moments for the general case of rotationally-symmetric aberrations. A closed-form expression for a PDF for a general non-rotationally symmetric wavefront aberration is difficult to derive. However, for specific cases, such as astigmatism, a closed-form expression of the PDF can be obtained. Further, interpretation of the distribution of the refractive error map as well as its moments is provided for a range of wavefront aberrations measured in real eyes. These are evaluated using a kernel density and sample moments estimators. It is concluded that the refractive error domain allows non-functional analysis of wavefront aberrations based on simple statistics in the form of its sample moments. Clinicians may find this approach to wavefront analysis easier to interpret due to the clinical familiarity and intuitive appeal of refractive error maps.