Factors to drive clinical practice improvement in a Malaysian intensive care unit : assessment of organisational readiness using a mixed method approach

This study assessed organisational readiness and factors to drive clinical practice improvement for VAP, CRBSI and PU in a Malaysian intensive care unit (ICU). A mixed method study approach was undertaken in a 16-bed ICU in regional Malaysia using an environmental scan, key informant interviews, staff surveys, and patient audit to elucidate factors contributing to planning for clinical practice improvement. Measurements of sustainability of practice and regard for the practice environment were assessed using validated measures. An environmental scan demonstrated high patient occupancy and case load. Nineteen percent of ICU patients developed complications according to validated measures. Survey results indicated that the majority of nurses had a good knowledge of strategies to prevent ICU complications and a positive attitude toward change processes. Engaging executive leadership was identified as crucial in priming the clinical site for practice change. Providing nurses with tools to monitor their clinical practice and empowering them to change practices are important in improving clinical outcomes.

Pricing innovations in consumption growth: a re-evaluation of the recursive utility model

We re-evaluate the cross-sectional asset pricing implications of the recursive utility function of Epstein and Zin, 1989 and Epstein and Zin, 1991, using innovations in future consumption growth in our tests. Our empirical specification helps explain the size, value and momentum effects. Specifically, we find that (і) the beta associated with news about consumption growth has a systematic pattern: beta decreases along the size dimension and increases along the book-to-market and momentum dimensions, (іі) innovation in consumption growth is significantly priced in asset returns using both the Fama and MacBeth (1973) and the stochastic discount factor approaches, and (ііі) the model performs better than both the CAPM and Fama–French model.

Directed search, coordination failure, and seller profits: an experimental comparison of posted pricing with single and multiple prices

We experimentally examine posted pricing and directed search. In one treatment, capacity-constrained sellers post fixed prices, which buyers observe before choosing whom to visit. In the other, firms post both “single-buyer” (applied when one buyer visits) and “multibuyer” (when multiple buyers visit) prices. We find, based on a 2 × 2 (two buyers and two sellers) market and a follow-up experiment with 3 and 2 × 3 markets, that multibuyer prices can be lower than single-buyer prices or prices in the one-price treatment. Also, allowing the multibuyer price does not affect seller profits and increases market frictions.

Size and power properties of structural break unit root tests

In this article, we compare the small sample size and power properties of a newly developed endogenous structural break unit root test of Narayan and Popp (NP, 2010) with the existing two break unit root tests, namely the Lumsdaine and Papell (LP, 1997) and the Lee and Strazicich (LS, 2003) tests. In contrast to the widely used LP and LS tests, the NP test chooses the break date by maximizing the significance of the break dummy coefficient. Using Monte Carlo simulations, we show that the NP test has better size and high power, and identifies the structural breaks accurately. Power and size comparisons of the NP test with the LP and LS tests reveal that the NP test is significantly superior.

A computationally convenient unit root test with covariates, conditional heteroskedasticity and efficient detrending

When testing for a unit root in a time series, in spite of the well-known power problem of univariate tests, it is quite common to use only the information regarding the autoregressive behaviour contained in that series. In a series of influential papers, Elliott et al. (Efficient tests for an autoregressive unit root, Econometrica 64, 813–836, 1996), Hansen (Rethinking the univariate approach to unit root testing: using covariates to increase power, Econometric Theory 11, 1148–1171, 1995a) and Seo (Distribution theory for unit root tests with conditional heteroskedasticity, Journal of Econometrics 91, 113–144, 1999) showed that this practice can be rather costly and that the inclusion of the extraneous information contained in the near-integratedness of many economic variables, their heteroskedasticity and their correlation with other covariates can lead to substantial power gains. In this article, we show how these information sets can be combined into a single unit root test.

A modified LLC panel unit root test of the PPP hypothesis

In a recent study, Westerlund (Empir Econ 37:517–531, 2009) shows that the performance of the popular LLC (Levin et al., J Econ 108:1–24, 2002) panel unit root test depends critically on the choice of lag truncation used when correcting for serial correlation, and that it is only when this parameter is set as a function of time that the power raises above size. The purpose of the current paper is to propose a modified test that does not suffer from this drawback. The new test is not only simpler to compute but also superior in terms of small-sample performance, which is illustrated using an example purchasing power parity for less developed countries.

Testing for unit roots in panel time-series models with multiple level breaks

This paper proposes two new unit root tests that are appropriate in the presence of an unknown number of structural breaks in the level of the data. One is based on a single time series and the other is based on a panel of multiple series. For the estimation of the number of breaks and their locations, a simple procedure based on outlier detection is proposed. The limiting distributions of the tests are derived and evaluated in small samples using simulation experiments. The implementation of the tests is illustrated using as an example purchasing power parity.

Modelling attribute dependencies in single unit game combat settings

The relative strengths of individual units, described as attributes, determine the outcome during unit conflicts involving units in the armies of opponents in large strategy games. We describe a process for developing predictive models of the outcome for such conflicts where combat involves single unit adversaries where each unit is defined in terms of 4 fundamental attributes. These attributes: range, speed, health and damage are common to unit descriptions in many successful real-time strategy games. Our analysis process identifies three phases of game play with invariant properties that hold throughout each phase. We demonstrate the utility of this analysis by creating a model that predicts game outcomes. Predictions are validated against the game simulation. The game outcomes are explicitly related to the attributes of the two units involved, highlighting the significance and role of each attribute.

Examining adverse events after intensive care unit discharge : outcomes from a pilot questionnaire

Adverse events are common in acute clinical settings but little is known about these events occurring after Intensive Care discharge. This study aimed to develop a reliable and valid tool for exploring clinicians’ opinions of factors associated with post-Intensive Care adverse events. A convenience sample of Australian Intensive Care Liaison Nurses was invited to complete and appraise a questionnaire using structured guidelines. Content validity and internal consistency were assessed.

Twelve Intensive Care Liaison Nurses completed the questionnaire. Cronbach?s alpha coefficient showed high internal consistency for the questionnaire; all 24 items on the questionnaire had coefficients greater than 0.852. The content validity index of the questionnaire overall was 0.76.

The post-Intensive Care adverse events questionnaire demonstrated reliability and validity. It is a tool that can be used to explore clinicians? opinions of factors associated with these events. The tool is important as it facilitates further insight into the causes of post-Intensive Care adverse events.

A hierarchical cloud pricing system

Cloud computing is experiencing phenomenal growth and there are now many vendors offering their cloud services. In cloud computing, cloud providers cooperate together to offer their computing resource as a utility and software as a service to customers. The demands and the price of cloud service should be negotiated between providers and users based on the Service Level Agreement (SLA). In order to help cloud providers achieving an agreeable price for their services and maximizing the benefits of both cloud providers and clients, this paper proposes a cloud pricing system consisting of hierarchical system, M/M/c queuing model and pricing model. Simulation results verify the efficiency of our proposed system.