A normative method to analyse workarounds in a healthcare environment: motivations, consequences, and constraints

Healthcare information systems have the potential to enhance productivity, lower costs, and reduce medication errors by automating business processes. However, various issues such as system complexity and system abilities in a relation to user requirements as well as rapid changes in business needs have an impact on the use of these systems. In many cases failure of a system to meet business process needs has pushed users to develop alternative work processes (workarounds) to fill this gap. Some research has been undertaken on why users are motivated to perform and create workarounds. However, very little research has assessed the consequences on patient safety. Moreover, the impact of performing these workarounds on the organisation and how to quantify risks and benefits is not well analysed. Generally, there is a lack of rigorous understanding and qualitative and quantitative studies on healthcare IS workarounds and their outcomes. This project applies A Normative Approach for Modelling Workarounds to develop A Model of Motivation, Constraints, and Consequences. It aims to understand the phenomenon in-depth and provide guidelines to organisations on how to deal with workarounds. Finally the method is demonstrated on a case study example and its relative merits discussed.

Linking urban water balance and energy balance models to analyse urban design options

Using a water balance modelling framework, this paper analyses the effects of urban design on the water balance, with a focus on evapotranspiration and storm water. First, two quite different urban water balance models are compared: Aquacycle which has been calibrated for a suburban catchment in Canberra, Australia, and the single-source urban evapotranspiration-interception scheme (SUES), an energy-based approach with a biophysically advanced representation of interception and evapotranspiration. A fair agreement between the two modelled estimates of evapotranspiration was significantly improved by allowing the vegetation cover (leaf area index, LAI) to vary seasonally, demonstrating the potential of SUES to quantify the links between water sensitive urban design and microclimates and the advantage of comparing the two modelling approaches. The comparison also revealed where improvements to SUES are needed, chiefly through improved estimates of vegetation cover dynamics as input to SUES, and more rigorous parameterization of the surface resistance equations using local-scale suburban flux measurements. Second, Aquacycle is used to identify the impact of an array of water sensitive urban design features on the water balance terms. This analysis confirms the potential to passively control urban microclimate by suburban design features that maximize evapotranspiration, such as vegetated roofs. The subsequent effects on daily maximum air temperatures are estimated using an atmospheric boundary layer budget. Potential energy savings of about 2% in summer cooling are estimated from this analysis. This is a clear ‘return on investment’ of using water to maintain urban greenspace, whether as parks distributed throughout an urban area or individual gardens or vegetated roofs.

Diagnostic tool to analyse colour-magnitude diagrams of poorly populated stellar concentrations

The dynamical processes that lead to open cluster disruption cause its mass to decrease. To investigate such processes from the observational point of view, it is important to identify open cluster remnants (OCRs), which are intrinsically poorly populated. Due to their nature, distinguishing them from field star fluctuations is still an unresolved issue. In this work, we developed a statistical diagnostic tool to distinguish poorly populated star concentrations from background field fluctuations. We use 2MASS photometry to explore one of the conditions required for a stellar group to be a physical group: to produce distinct sequences in a colour-magnitude diagram (CMD). We use automated tools to (i) derive the limiting radius; (ii) decontaminate the field and assign membership probabilities; (iii) fit isochrones; and (iv) compare object and field CMDs, considering the isochrone solution, in order to verify the similarity. If the object cannot be statistically considered as a field fluctuation, we derive its probable age, distance modulus, reddening and uncertainties in a self-consistent way. As a test, we apply the tool to open clusters and comparison fields. Finally, we study the OCR candidates DoDz 6, NGC 272, ESO 435 SC48 and ESO 325 SC15. The tool is optimized to treat these low-statistic objects and to separate the best OCR candidates for studies on kinematics and chemical composition. The study of the possible OCRs will certainly provide a deep understanding of OCR properties and constraints for theoretical models, including insights into the evolution of open clusters and dissolution rates.

Using stochastic volatility models to analyse weekly ozone averages in Mexico City

In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.