Using operations research methodologies to improve operating theatre scheduling

A hospital consists of a number of wards, units and departments that provide a variety of medical services and interact on a day-to-day basis. Nearly every department within a hospital schedules patients for the operating theatre (OT) and most wards receive patients from the OT following post-operative recovery. Because of the interrelationships between units, disruptions and cancellations within the OT can have a flow-on effect to the rest of the hospital. This often results in dissatisfied patients, nurses and doctors, escalating waiting lists, inefficient resource usage and undesirable waiting times. The objective of this study is to use Operational Research methodologies to enhance the performance of the operating theatre by improving elective patient planning using robust scheduling and improving the overall responsiveness to emergency patients by solving the disruption management and rescheduling problem. OT scheduling considers two types of patients: elective and emergency. Elective patients are selected from a waiting list and scheduled in advance based on resource availability and a set of objectives. This type of scheduling is referred to as ‘offline scheduling’. Disruptions to this schedule can occur for various reasons including variations in length of treatment, equipment restrictions or breakdown, unforeseen delays and the arrival of emergency patients, which may compete for resources. Emergency patients consist of acute patients requiring surgical intervention or in-patients whose conditions have deteriorated. These may or may not be urgent and are triaged accordingly. Most hospitals reserve theatres for emergency cases, but when these or other resources are unavailable, disruptions to the elective schedule result, such as delays in surgery start time, elective surgery cancellations or transfers to another institution. Scheduling of emergency patients and the handling of schedule disruptions is an ‘online’ process typically handled by OT staff. This means that decisions are made ‘on the spot’ in a ‘real-time’ environment. There are three key stages to this study: (1) Analyse the performance of the operating theatre department using simulation. Simulation is used as a decision support tool and involves changing system parameters and elective scheduling policies and observing the effect on the system’s performance measures; (2) Improve viability of elective schedules making offline schedules more robust to differences between expected treatment times and actual treatment times, using robust scheduling techniques. This will improve the access to care and the responsiveness to emergency patients; (3) Address the disruption management and rescheduling problem (which incorporates emergency arrivals) using innovative robust reactive scheduling techniques. The robust schedule will form the baseline schedule for the online robust reactive scheduling model.

How can design methodologies build strategic renewal in SMEs?

Many firms develop successful businesses around competencies and over time these competencies can become core rigidities and barriers to new ways of working. This paper investigates how firms respond to a design innovation program apply design methodologies to their business. Early findings from a study of companies engaged in a design innovation program indicate that applying design principles to multiple aspects of their business provides a new strategic focus, tools for a better understanding of their business and the marketplace, new economic activity, awareness of the need for an innovative culture and strategic renewal.

Researching news discussion on Twitter : New methodologies

Twitter has become a major instrument for the rapid dissemination and subsequent debate of news stories, and comprehensive methodologies for systematic research into news discussion on Twitter are beginning to emerge. This paper outlines innovative approaches for large-scale quantitative research into how Twitter is used to discuss and cover the news, focusing especially on #hashtags: brief identifiers which mark a tweet as taking part in an established discussion.

Power in legal education : a (new) critical and analytical approach

This article explores power within legal education scholarship. It suggests that power relations are not effectively reflected on within this scholarship, and it provokes legal educators to consider power more explicitly and effectively. It then outlines in-depth a conceptual and methodological approach based on Michel Foucault’s concept of ‘governmentality’ to assist in such an analysis. By detailing the conceptual moves required in order to research power in legal education more effectively, this article seeks to stimulate new reflection and thought about the practice and scholarship of legal education, and allow for political interventions to become more ethically sensitive and potentially more effective.

New evaluation methodologies for public art programs in cultural instiutions

I put my abstract in for this conference back in March, based on some evaluation work I had been doing in 2010 with my colleague Professor Greg Hearn for the 3C Regional Writing NeoGreography Project. I had been swapping notes with a colleague from the Smithsonian’s Centre for Folklife and Cultural Heritage about their evaluation work, and stuck inside during the rains of January, I decided to apply for a Qld Smithsonian fellowship based on the quandary of evaluation-particular in public histories (oral histories) and digital storytelling. In July I was awarded the fellowship, so I have tweaked my presentation to talk about what we hope to do with this collaboration, to propel the importance placed on evaluation in public arts programs in Qld and beyond.

Leveraging social network data for analytical CRM strategies : the introduction of social BI

The skyrocketing trend for social media on the Internet greatly alters analytical Customer Relationship Management (CRM). Against this backdrop, the purpose of this paper is to advance the conceptual design of Business Intelligence (BI) systems with data identified from social networks. We develop an integrated social network data model, based on an in-depth analysis of Facebook. The data model can inform the design of data warehouses in order to offer new opportunities for CRM analyses, leading to a more consistent and richer picture of customers? characteristics, needs, wants, and demands. Four major contributions are offered. First, Social CRM and Social BI are introduced as emerging fields of research. Second, we develop a conceptual data model to identify and systematize the data available on online social networks. Third, based on the identified data, we design a multidimensional data model as an early contribution to the conceptual design of Social BI systems and demonstrate its application by developing management reports in a retail scenario. Fourth, intellectual challenges for advancing Social CRM and Social BI are discussed.

Analytical solutions of the multi-term modified power law wave equations in a finite domain

Fractional partial differential equations with more than one fractional derivative term in time, such as the Szabo wave equation, or the power law wave equation, describe important physical phenomena. However, studies of these multi-term time-space or time fractional wave equations are still under development. In this paper, multi-term modified power law wave equations in a finite domain are considered. The multi-term time fractional derivatives are defined in the Caputo sense, whose orders belong to the intervals (1, 2], [2, 3), [2, 4) or (0, n) (n > 2), respectively. Analytical solutions of the multi-term modified power law wave equations are derived. These new techniques are based on Luchko’s Theorem, a spectral representation of the Laplacian operator, a method of separating variables and fractional derivative techniques. Then these general methods are applied to the special cases of the Szabo wave equation and the power law wave equation. These methods and techniques can also be extended to other kinds of the multi term time-space fractional models including fractional Laplacian.

Analytical solutions for the two- and three-dimensional time-fractional telegraph equations by the method of separating variables

In this paper, a method of separating variables is effectively implemented for solving a time-fractional telegraph equation (TFTE) in two and three dimensions. We discuss and derive the analytical solution of the TFTE in two and three dimensions with nonhomogeneous Dirichlet boundary condition. This method can be extended to other kinds of the boundary conditions.

Analytical solutions for the multi-term time-space Caputo-Riesz fractional advection-diffusion equations on a finite domain

Generalized fractional partial differential equations have now found wide application for describing important physical phenomena, such as subdiffusive and superdiffusive processes. However, studies of generalized multi-term time and space fractional partial differential equations are still under development. In this paper, the multi-term time-space Caputo-Riesz fractional advection diffusion equations (MT-TSCR-FADE) with Dirichlet nonhomogeneous boundary conditions are considered. The multi-term time-fractional derivatives are defined in the Caputo sense, whose orders belong to the intervals [0, 1], [1, 2] and [0, 2], respectively. These are called respectively the multi-term time-fractional diffusion terms, the multi-term time-fractional wave terms and the multi-term time-fractional mixed diffusion-wave terms. The space fractional derivatives are defined as Riesz fractional derivatives. Analytical solutions of three types of the MT-TSCR-FADE are derived with Dirichlet boundary conditions. By using Luchko's Theorem (Acta Math. Vietnam., 1999), we proposed some new techniques, such as a spectral representation of the fractional Laplacian operator and the equivalent relationship between fractional Laplacian operator and Riesz fractional derivative, that enabled the derivation of the analytical solutions for the multi-term time-space Caputo-Riesz fractional advection-diffusion equations. © 2012.

Analytical solutions for the multi-term time-fractional diffusion-wave/diffusion equations in a finite domain

Multi-term time-fractional differential equations have been used for describing important physical phenomena. However, studies of the multi-term time-fractional partial differential equations with three kinds of nonhomogeneous boundary conditions are still limited. In this paper, a method of separating variables is used to solve the multi-term time-fractional diffusion-wave equation and the multi-term time-fractional diffusion equation in a finite domain. In the two equations, the time-fractional derivative is defined in the Caputo sense. We discuss and derive the analytical solutions of the two equations with three kinds of nonhomogeneous boundary conditions, namely, Dirichlet, Neumann and Robin conditions, respectively.

Analytical and numerical solutions of the space and time fractional bloch-torrey equation

Fractional order dynamics in physics, particularly when applied to diffusion, leads to an extension of the concept of Brown-ian motion through a generalization of the Gaussian probability function to what is termed anomalous diffusion. As MRI is applied with increasing temporal and spatial resolution, the spin dynamics are being examined more closely; such examinations extend our knowledge of biological materials through a detailed analysis of relaxation time distribution and water diffusion heterogeneity. Here the dynamic models become more complex as they attempt to correlate new data with a multiplicity of tissue compartments where processes are often anisotropic. Anomalous diffusion in the human brain using fractional order calculus has been investigated. Recently, a new diffusion model was proposed by solving the Bloch-Torrey equation using fractional order calculus with respect to time and space (see R.L. Magin et al., J. Magnetic Resonance, 190 (2008) 255-270). However effective numerical methods and supporting error analyses for the fractional Bloch-Torrey equation are still limited. In this paper, the space and time fractional Bloch-Torrey equation (ST-FBTE) is considered. The time and space derivatives in the ST-FBTE are replaced by the Caputo and the sequential Riesz fractional derivatives, respectively. Firstly, we derive an analytical solution for the ST-FBTE with initial and boundary conditions on a finite domain. Secondly, we propose an implicit numerical method (INM) for the ST-FBTE, and the stability and convergence of the INM are investigated. We prove that the implicit numerical method for the ST-FBTE is unconditionally stable and convergent. Finally, we present some numerical results that support our theoretical analysis.

A review of current statistical methodologies for in storage sampling and surveillance in the grains industry

Effective, statistically robust sampling and surveillance strategies form an integral component of large agricultural industries such as the grains industry. Intensive in-storage sampling is essential for pest detection, Integrated Pest Management (IPM), to determine grain quality and to satisfy importing nation’s biosecurity concerns, while surveillance over broad geographic regions ensures that biosecurity risks can be excluded, monitored, eradicated or contained within an area. In the grains industry, a number of qualitative and quantitative methodologies for surveillance and in-storage sampling have been considered. Primarily, research has focussed on developing statistical methodologies for in storage sampling strategies concentrating on detection of pest insects within a grain bulk, however, the need for effective and statistically defensible surveillance strategies has also been recognised. Interestingly, although surveillance and in storage sampling have typically been considered independently, many techniques and concepts are common between the two fields of research. This review aims to consider the development of statistically based in storage sampling and surveillance strategies and to identify methods that may be useful for both surveillance and in storage sampling. We discuss the utility of new quantitative and qualitative approaches, such as Bayesian statistics, fault trees and more traditional probabilistic methods and show how these methods may be used in both surveillance and in storage sampling systems.

An analytical tool that quantifies cellular morphology changes from three-dimensional fluorescence images

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology(1) even in complex tissue sections(2). Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells(3), however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.