A test vehicle for compliance with resilience requirements in index-based e-health systems

Increasingly, national and international governments have a strong mandate to develop national e-health systems to enable delivery of much-needed healthcare services. Research is, therefore, needed into appropriate security and reliance structures for the development of health information systems which must be compliant with governmental and alike obligations. The protection of e-health information security is critical to the successful implementation of any e-health initiative. To address this, this paper proposes a security architecture for index-based e-health environments, according to the broad outline of Australia’s National E-health Strategy and National E-health Transition Authority (NEHTA)’s Connectivity Architecture. This proposal, however, could be equally applied to any distributed, index-based health information system involving referencing to disparate health information systems. The practicality of the proposed security architecture is supported through an experimental demonstration. This successful prototype completion demonstrates the comprehensibility of the proposed architecture, and the clarity and feasibility of system specifications, in enabling ready development of such a system. This test vehicle has also indicated a number of parameters that need to be considered in any national indexed-based e-health system design with reasonable levels of system security. This paper has identified the need for evaluation of the levels of education, training, and expertise required to create such a system.

Use of virtual index for measuring efficiency of innovation systems : a cross-country study

In this study we propose a virtual index for measuring the relative innovativeness of countries. Using a multistage virtual benchmarking process, the best and rational benchmark is extracted for inefficient ISs. Furthermore, Tobit and Ordinary Least Squares (OLS) regression models are used to investigate the likelihood of changes in inefficiencies by investigating country-specific factors. The empirical results relating to the virtual benchmarking process suggest that the OLS regression model would better explain changes in the performance of innovation- inefficient countries.

Infinite-horizon policy-gradient estimation

Gradient-based approaches to direct policy search in reinforcement learning have received much recent attention as a means to solve problems of partial observability and to avoid some of the problems associated with policy degradation in value-function methods. In this paper we introduce GPOMDP, a simulation-based algorithm for generating a biased estimate of the gradient of the average reward in Partially Observable Markov Decision Processes (POMDPs) controlled by parameterized stochastic policies. A similar algorithm was proposed by Kimura, Yamamura, and Kobayashi (1995). The algorithm's chief advantages are that it requires storage of only twice the number of policy parameters, uses one free parameter β ∈ [0,1) (which has a natural interpretation in terms of bias-variance trade-off), and requires no knowledge of the underlying state. We prove convergence of GPOMDP, and show how the correct choice of the parameter β is related to the mixing time of the controlled POMDP. We briefly describe extensions of GPOMDP to controlled Markov chains, continuous state, observation and control spaces, multiple-agents, higher-order derivatives, and a version for training stochastic policies with internal states. In a companion paper (Baxter, Bartlett, & Weaver, 2001) we show how the gradient estimates generated by GPOMDP can be used in both a traditional stochastic gradient algorithm and a conjugate-gradient procedure to find local optima of the average reward. ©2001 AI Access Foundation and Morgan Kaufmann Publishers. All rights reserved.

Exponentiated gradient algorithms for conditional random fields and max-margin Markov Networks

Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of parameters in these models is therefore an important problem, and becomes a key factor when learning from very large data sets. This paper describes exponentiated gradient (EG) algorithms for training such models, where EG updates are applied to the convex dual of either the log-linear or max-margin objective function; the dual in both the log-linear and max-margin cases corresponds to minimizing a convex function with simplex constraints. We study both batch and online variants of the algorithm, and provide rates of convergence for both cases. In the max-margin case, O(1/ε) EG updates are required to reach a given accuracy ε in the dual; in contrast, for log-linear models only O(log(1/ε)) updates are required. For both the max-margin and log-linear cases, our bounds suggest that the online EG algorithm requires a factor of n less computation to reach a desired accuracy than the batch EG algorithm, where n is the number of training examples. Our experiments confirm that the online algorithms are much faster than the batch algorithms in practice. We describe how the EG updates factor in a convenient way for structured prediction problems, allowing the algorithms to be efficiently applied to problems such as sequence learning or natural language parsing. We perform extensive evaluation of the algorithms, comparing them to L-BFGS and stochastic gradient descent for log-linear models, and to SVM-Struct for max-margin models. The algorithms are applied to a multi-class problem as well as to a more complex large-scale parsing task. In all these settings, the EG algorithms presented here outperform the other methods.

Exponentiated gradient algorithms for large-margin structured classification

We consider the problem of structured classification, where the task is to predict a label y from an input x, and y has meaningful internal structure. Our framework includes supervised training of Markov random fields and weighted context-free grammars as special cases. We describe an algorithm that solves the large-margin optimization problem defined in [12], using an exponential-family (Gibbs distribution) representation of structured objects. The algorithm is efficient—even in cases where the number of labels y is exponential in size—provided that certain expectations under Gibbs distributions can be calculated efficiently. The method for structured labels relies on a more general result, specifically the application of exponentiated gradient updates [7, 8] to quadratic programs.

Adaptive online gradient descent

We study the rates of growth of the regret in online convex optimization. First, we show that a simple extension of the algorithm of Hazan et al eliminates the need for a priori knowledge of the lower bound on the second derivatives of the observed functions. We then provide an algorithm, Adaptive Online Gradient Descent, which interpolates between the results of Zinkevich for linear functions and of Hazan et al for strongly convex functions, achieving intermediate rates between [square root T] and [log T]. Furthermore, we show strong optimality of the algorithm. Finally, we provide an extension of our results to general norms.

Unbiased estimation of the half-life to price index convergence among U.S. cities

Estimates of the half-life to convergence of prices across a panel of cities are subject to bias from three potential sources: inappropriate cross-sectional aggregation of heterogeneous coefficients, presence of lagged dependent variables in a model with individual fixed effects, and time aggregation of commodity prices. This paper finds no evidence of heterogeneity bias in annual CPI data for 17 U.S. cities from 1918 to 2006, but correcting for the “Nickell bias” and time aggregation bias produces a half-life of 7.5 years, shorter than estimates from previous studies.

Cardiac ARIA Index: Measuring Accessibility to Cardiovascular Services in Rural and Remote Australia via Applied Geographic Spatial Technology

Cardiovascular disease (CVD) continues to impose a heavy burden in terms of cost, disability and death in Australia. Evidence suggests that increasing remoteness, where cardiac services are scarce, is linked to an increased risk of dying from CVD. Fatal CVD events are reported to be between 20% and 50% higher in rural areas compared to major cities. The Cardiac ARIA project, with its extensive use of geographic Information Systems (GIS), ranks each of Australia’s 20,387 urban, rural and remote population centres by accessibility to essential services or resources for the management of a cardiac event. This unique, innovative and highly collaborative project delivers a powerful tool to highlight and combat the burden imposed by cardiovascular disease (CVD) in Australia. Cardiac ARIA is innovative. It is a model that could be applied internationally and to other acute and chronic conditions such as mental health, midwifery, cancer, respiratory, diabetes and burns services. Cardiac ARIA was designed to: 1. Determine by expert panel, what were the minimal services and resources required for the management of a cardiac event in any urban, rural or remote population locations in Australia using a single patient pathway to access care. 2. Derive a classification using GIS accessibility modelling for each of Australia’s 20,387 urban, rural and remote population locations. 3. Compare the Cardiac ARIA categories and population locations with census derived population characteristics. Key findings are as follows: • In the event of a cardiac emergency, the majority of Australians had very good access to cardiac services. Approximately 71% or 13.9 million people lived within one hour of a category one hospital. • 68% of older Australians lived within one hour of a category one hospital (Principal Referral Hospital with access to Cardiac Catheterisation). • Only 40% of indigenous people lived within one hour of the category one hospital. • 16% (74000) of indigenous people lived more than one hour from a hospital. • 3% (91,000) of people 65 years of age or older lived more than one hour from any hospital or clinic. • Approximately 96%, or 19 million, of people lived within one hour of the four key services to support cardiac rehabilitation and secondary prevention. • 75% of indigenous people lived within one hour of the four cardiac rehabilitation services to support cardiac rehabilitation and secondary prevention. Fourteen percent (64,000 persons) indigenous people had poor access to the four key services to support cardiac rehabilitation and secondary prevention. • 12% (56,000) of indigenous people were more than one hour from a hospital and only had access one the four key services (usually a medical service) to support cardiac rehabilitation and secondary prevention.

Can the Cardiac ARIA Index Improve Cardiac Care for Australia's Indigenous Population?

Background: Timely access to appropriate cardiac care is critical for optimising outcomes. Our aim was to derive an objective, comparable, geographic measure reflecting access to cardiac services for Australia's 20,387 population locations. Methods: An expert panel defined a single patient care pathway. Using geographic information systems (GIS) the numeric/alpha index was modelled in two phases. The acute phase index (numeric) ranged from 1 (access to tertiary centre with PCI ≤1 h) to 8 (no ambulance service, >3 h to medical facility, air transport required). The aftercare index was modelled into 5 alphabetic categories; A (Access to general practitioner, pharmacy, cardiac rehabilitation, pathology ≤1 h) to E (no services available within 1 h). Results: Approximately 70% or 13.9 million people lived within a CardiacARIAindex category 1A location. Disparity continues in access to category 1A cardiac services for 5.8 million (30%) of all Australians, 60% of Aboriginal and Torres Strait Islander people and 32% of people over 65 years of age. In a cardiac emergency only 40% of the Indigenous population reside within one hour of category 1 hospital. Approximately 30% (81,491 Indigenous persons) are more than one to three hours from basic cardiac services. Conclusion: Geographically, the majority of Australian's have timely access for survival of a cardiac event. The CardiacARIAindex objectively demonstrates that the healthcare system may not be providing for the needs of 60% of Indigenous people residing outside the 1A geographic radius. Innovative clinical practice maybe required to address these disparities.

Where not to have a Heart Attack in Australia!: The Cardiac ARIA Index

Background/aims: Access to appropriate health care following an acute cardiac event is important for positive outcomes. The aim of the Cardiac ARIA index was to derive an objective, comparable, geographic measure reflecting access to cardiac services across Australia. Methods: Geographic Information Systems (GIS) were used to model a numeric-alpha index based on acute management from onset of symptoms to return to the community. Acute time frames have been calculated to include time for ambulance to arrive, assess and load patient, and travel to facility by road 40–80 kph. Results: The acute phase of the index was modelled into five categories: 1 [24/7 percutaneous cardiac intervention (PCI) ≤1 h]; 2 [24/7 PCI 1–3 h, and PCI less than an additional hour to nearest accident and emergency room (A&E)]: 3 [Nearest A&E ≤3 h (no 24/7 PCI within an extra hour)]: 4 [Nearest A&E 3–12 h (no 24/7 PCI within an extra hour)]: 5 [Nearest A&E 12–24 h (no 24/7 PCI within an extra hour)]. Discharge care was modelled into three categories based on time to a cardiac rehabilitation program, retail pharmacy, pathology services, hospital, GP or remote clinic: (A) all services ≤30 min; (B) >30 min and ≤60 min; (C) >60 min. Examples of the index indicate that the majority of population locations within capital cities were category 1A; Alice Springs and Byron Bay were 3A; and the Northern Territory town of Maningrida had minimal access to cardiac services with an index ranking of 5C. Conclusion: The Cardiac ARIA index provides an invaluable tool to inform appropriate strategies for the use of scarce cardiac resources.

A continuum model of the growth of engineered epidermal skin substitutes

We present a porous medium model of the growth and deterioration of the viable sublayers of an epidermal skin substitute. It consists of five species: cells, intracellular and extracellular calcium, tight junctions, and a hypothesised signal chemical emanating from the stratum corneum. The model is solved numerically in Matlab using a finite difference scheme. Steady state calcium distributions are predicted that agree well with the experimental data. Our model also demonstrates epidermal skin substitute deterioration if the calcium diffusion coefficient is reduced compared to reported values in the literature.

Anisotropy of articular cartilage reflects the ECM gradient architecture : Hough-Radon Transform Analysis

Tissue-specific extracellular matrix (ECM) is known to be an ideal bioscaffold to inspire the future of regenerative medicine. It holds the secret of how nature has developed such an organization of molecules into a unique functional complexity. This work exploited an innovative image processing algorithm and high resolution microscopy associated with mechanical analysis to establish a correlation between the gradient organization of cartiligous ECM and its anisotropic biomechanical response. This was hypothesized to be a reliable determinant that can elucidate how microarchitecture interrelates with biomechanical properties. Hough-Radon transform of the ECM cross-section images revealed its conformational variation from tangential interface down to subchondral region. As the orientation varied layer by layer, the anisotropic mechanical response deviated relatively. Although, results were in good agreement (Kendall's tau-b > 90%), there were evidences proposing that alignment of the fibrous network, specifically in middle zone, is not as random as it was previously thought.

Deprivation is an independent predictor of 1-year mortality in outpatients with chronic obstructive pulmonary disease

Deprivation is linked to increased incidence in a number of chronic diseases but its relationship to chronic obstructive pulmonary disease (COPD) is uncertain despite suggestions that the socioeconomic gradient seen in COPD is as great, if not greater, than any other disease (Prescott and Vestbo).1 There is also a need to take into account the confounding effects of malnutrition which have been shown to be independently linked to increased mortality (Collins et al).2 The current study investigated the influence of social deprivation on 1-year survival rates in COPD outpatients, independently of malnutrition. 424 outpatients with COPD were routinely screened for malnutrition risk using the ‘Malnutrition Universal Screening Tool’; ‘MUST’ (Elia),3 between July and May 2009; 222 males and 202 females; mean age 73 (SD 9.9) years; body mass index 25.8 (SD 6.3) kg/m2. Each individual's deprivation was calculated using the index of multiple deprivation (IMD) which was established according to the geographical location of each patient's address (postcode). IMD includes a number of indicators covering economic, housing and social issues (eg, health, education and employment) into a single deprivation score (Nobel et al).4 The lower the IMD score, the lower an individual's deprivation. The IMD was assigned to each outpatient at the time of screening and related to1-year mortality from the date screened. Outpatients who died within 1-year of screening were significantly more likely to reside within a deprived postcode (IMD 19.7±SD 13.1 vs 15.4±SD 10.7; p=0.023, OR 1.03, 95% CI 1.00 to 1.06) than those that did not die. Deprivation remained a significant independent risk factor for 1-year mortality even when adjusted for malnutrition as well as age, gender and disease severity (binary logistic regression; p=0.008, OR 1.04, 95% CI 1.04 to 1.07). Deprivation was not associated with disease-severity (p=0.906) or body mass index, kg/m2 (p=0.921) using ANOVA. This is the first study to show that deprivation, assessed using IMD, is associated with increased 1-year mortality in outpatients with COPD independently of malnutrition, age and disease severity. Deprivation should be considered in the targeted management of these patients.