Process mining for clinical processes: A comparative analysis of four Australian hospitals

Business process analysis and process mining, particularly within the health care domain, remain under-utilised. Applied research that employs such techniques to routinely collected, health care data enables stakeholders to empirically investigate care as it is delivered by different health providers. However, cross-organisational mining and the comparative analysis of processes present a set of unique challenges in terms of ensuring population and activity comparability, visualising the mined models and interpreting the results. Without addressing these issues, health providers will find it difficult to use process mining insights, and the potential benefits of evidence-based process improvement within health will remain unrealised. In this paper, we present a brief introduction on the nature of health care processes; a review of the process mining in health literature; and a case study conducted to explore and learn how health care data, and cross-organisational comparisons with process mining techniques may be approached. The case study applies process mining techniques to administrative and clinical data for patients who present with chest pain symptoms at one of four public hospitals in South Australia. We demonstrate an approach that provides detailed insights into clinical (quality of patient health) and fiscal (hospital budget) pressures in health care practice. We conclude by discussing the key lessons learned from our experience in conducting business process analysis and process mining based on the data from four different hospitals.

'I wouldn't say that' : finding a young adult, female voice in a Queensland mining town

This is a practice-led project consisting of a Young Adult novel, Open Cut, and an exegesis, 'I Wouldn't Say That': Finding a Young Adult, Female Voice in a Queensland Mining Town. The thesis investigates the use of first person narration in order to create an immediate engaging, realist Young Adult Fiction. The research design is bound by a feminist interpretative paradigm. The methodology employed is practice-led, auto-ethnography, and participant observation. Particular characteristics of first person narration used in Australian Young Adult Fiction are identified in an analysis of Dust, by Christine Bongers, and Jasper Jones, by Craig Silvey. The exegesis also contains a reflection on the researcher's creative work, and the process used to draft, edit, plot and construct the novel. The research contributes to knowledge in the field of Young Adult Literature because it offers a graphic portrayal of an Australian mining town that has not been heard before.

A short-term production scheduling methodology for open-pit mines

A multi-resource multi-stage scheduling methodology is developed to solve short-term open-pit mine production scheduling problems as a generic multi-resource multi-stage scheduling problem. It is modelled using essential characteristics of short-term mining production operations such as drilling, sampling, blasting and excavating under the capacity constraints of mining equipment at each processing stage. Based on an extended disjunctive graph model, a shifting-bottleneck-procedure algorithm is enhanced and applied to obtain feasible short-term open-pit mine production schedules and near-optimal solutions. The proposed methodology and its solution quality are verified and validated using a real mining case study.

Business process mining success

Process mining has developed into a popular research discipline and nowadays its associated techniques are widely applied in practice. What is currently ill-understood is how the success of a process mining project can be measured and what the antecedent factors of process mining success are. We consider an improved, grounded understanding of these aspects of value to better manage the effectiveness and efficiency of process mining projects in practice. As such, we advance a model, tailored to the characteristics of process mining projects, which identifies and relates success factors and measures. We draw inspiration from the literature from related fields for the construction of a theoretical, a priori model. That model has been validated and re-specified on the basis of a multiple case study, which involved four industrial process mining projects. The unique contribution of this paper is that it presents the first set of success factors and measures on the basis of an analysis of real process mining projects. The presented model can also serve as a basis for further extension and refinement using insights from additional analyses.

Observation of solution-induced corneal staining with fluorescein, rose bengal and lissamine green

Ever since sodium fluorescein (‘fluorescein’ [FL]) was first used to investigate the ocular surface over a century ago, the term ‘staining’ has been taken to mean the presence of ocular surface fluorescence [1]. This term has not been necessarily taken to infer any particular mechanism of causation, and indeed, can be attributed to a variety of possible aetiologies [2]. In recent times, there has been considerable interest in a form of ocular surface fluorescence seen in association with the use of certain combinations of soft contact lenses and multipurpose solutions. The first clinical account of this phenomenon was reported by Jones et al. [3], which was followed by a more formal investigation by the same author in 2002 [4]. Jones et al described this appearance as a ‘classic solution-based toxicity reaction’. Subsequently, this appearance has come to be known as ‘solution-induced corneal staining’ or more recently by the acronym ‘SICS’ [5]. The term SICS is potentially problematic in that from a cell biology point of view, there is an inference that ‘staining’ means the entry of a dye into corneal epithelial cells. Morgan and Maldonado-Codina [2] noted there was no foundation of solid scientific literature underpinning our understanding of the true basic causative mechanisms of this phenomenon; since that time, further work has been published in this field [6] and [7] but questions still remain about the precise aetiology of this phenomenon...

Oscar Pistorius and the death of Reeva Steenkamp : mapping public opinions on Twitter using frame analysis and data mining

This paper uses innovative content analysis techniques to map how the death of Oscar Pistorius' girlfriend, Reeva Steenkamp, was framed on Twitter conversations. Around 1.5 million posts from a two-week timeframe are analyzed with a combination of syntactic and semantic methods. This analysis is grounded in the frame analysis perspective and is different than sentiment analysis. Instead of looking for explicit evaluations, such as “he is guilty” or “he is innocent”, we showcase through the results how opinions can be identified by complex articulations of more implicit symbolic devices such as examples and metaphors repeatedly mentioned. Different frames are adopted by users as more information about the case is revealed: from a more episodic one, highly used in the very beginning, to more systemic approaches, highlighting the association of the event with urban violence, gun control issues, and violence against women. A detailed timeline of the discussions is provided.

‘Our’ community : corporate social responsibility, neoliberalisation, and mining industry community engagement in rural Australia

This paper addresses contemporary neoliberal mobilisations of community undertaken by private corporations. It does so by examining the ways in which the mining industry, empowered through the legitimising framework of corporate social responsibility, is increasingly and profoundly involved in shaping the meaning, practice, and experience of ‘local community’. We draw on a substantial Australian case study, consisting of interviews and document analysis, as a means to examine ‘community-engagement’ practices undertaken by BHP Billiton’s Ravensthorpe Nickel Operation in the Shire of Ravensthorpe in rural Australia. This engagement, we argue, as a process of deepening neoliberalisation simultaneously defines and transforms local community according to the logic of global capital. As such, this study has implications for critical understandings of the intersections among corporate social responsibility, neoliberalisation, community, and capital.

A finite volume method with linearisation in time for the solution of advection-reaction-diffusion systems

The numerical solution in one space dimension of advection--reaction--diffusion systems with nonlinear source terms may invoke a high computational cost when the presently available methods are used. Numerous examples of finite volume schemes with high order spatial discretisations together with various techniques for the approximation of the advection term can be found in the literature. Almost all such techniques result in a nonlinear system of equations as a consequence of the finite volume discretisation especially when there are nonlinear source terms in the associated partial differential equation models. This work introduces a new technique that avoids having such nonlinear systems of equations generated by the spatial discretisation process when nonlinear source terms in the model equations can be expanded in positive powers of the dependent function of interest. The basis of this method is a new linearisation technique for the temporal integration of the nonlinear source terms as a supplementation of a more typical finite volume method. The resulting linear system of equations is shown to be both accurate and significantly faster than methods that necessitate the use of solvers for nonlinear system of equations.

Detecting news topics from microblogs using sequential pattern mining

This thesis presents a sequential pattern based model (PMM) to detect news topics from a popular microblogging platform, Twitter. PMM captures key topics and measures their importance using pattern properties and Twitter characteristics. This study shows that PMM outperforms traditional term-based models, and can potentially be implemented as a decision support system. The research contributes to news detection and addresses the challenging issue of extracting information from short and noisy text.

Mining universities : can we count on the integrity of research coming out of today's mining-funded tertiary sector?

Australia's economic growth and national identity have been widely celebrated as being founded on the nation's natural resources. With the golden era of pastoralism fading into the distance, a renewed love affair with primary industries has been much lauded, particularly by purveyors of neoliberal ideology. The considerable wealth generated by resource extraction has, despite its environmental and social record, proved seductive to the university sector. The mining industry is one of a number of industries and sectors (alongside pharmaceutical, chemical and biotechnological) that is increasingly courting Australian universities. These new public-private alliances are often viewed as the much-needed cash cow to bridge the public funding shortfall in the tertiary sector. However, this trend also raises profound questions about the capacity of public good institutions, as universities were once assumed to be, to maintain institutional independence and academic freedoms.

Mining specific features for acquiring user information needs

Term-based approaches can extract many features in text documents, but most include noise. Many popular text-mining strategies have been adapted to reduce noisy information from extracted features; however, text-mining techniques suffer from low frequency. The key issue is how to discover relevance features in text documents to fulfil user information needs. To address this issue, we propose a new method to extract specific features from user relevance feedback. The proposed approach includes two stages. The first stage extracts topics (or patterns) from text documents to focus on interesting topics. In the second stage, topics are deployed to lower level terms to address the low-frequency problem and find specific terms. The specific terms are determined based on their appearances in relevance feedback and their distribution in topics or high-level patterns. We test our proposed method with extensive experiments in the Reuters Corpus Volume 1 dataset and TREC topics. Results show that our proposed approach significantly outperforms the state-of-the-art models.

A novel process of group-oriented question reduction for rule-based recommendation websites

Several websites utilise a rule-base recommendation system, which generates choices based on a series of questionnaires, for recommending products to users. This approach has a high risk of customer attrition and the bottleneck is the questionnaire set. If the questioning process is too long, complex or tedious; users are most likely to quit the questionnaire before a product is recommended to them. If the questioning process is short; the user intensions cannot be gathered. The commonly used feature selection methods do not provide a satisfactory solution. We propose a novel process combining clustering, decisions tree and association rule mining for a group-oriented question reduction process. The question set is reduced according to common properties that are shared by a specific group of users. When applied on a real-world website, the proposed combined method outperforms the methods where the reduction of question is done only by using association rule mining or only by observing distribution within the group.

Organo-LDH synthesized via tricalcium aluminate hydration in the present of Na-dodecylbenzenesulfate aqueous solution and subsequent investigated by near-infrared and mid-infrared

Na-dodecylbenzenesulfate (SDBS), a natural anionic surfactant, has been successfully intercalated into a Ca based LDH host structure during tricalcium aluminate hydration in the presence of SDBS aqueous solution (CaAl-SDBS-LDH). The resulting product was characterized by powder X-ray diffraction (XRD), mid-infrared (MIR) spectroscopy combined with near-infrared (NIR) spectroscopy technique, thermal analysis (TG–DTA) and scan electron microscopy (SEM). The XRD results revealed that the interlayer distance of resultant product was expanded to 30.46 Å. MIR combined with NIR spectra offered an effective method to illustrate this intercalation. The NIR spectra (6000–5500 cm−1) displayed prominent bands to expound SDBS intercalated into hydration product of C3A. And the bands around 8300 cm−1 were assigned to the second overtone of the first fundamental of CH stretching vibrations of SDBS. In addition, thermal analysis showed that the dehydration and dehydroxylation took place at ca. 220 °C and 348 °C, respectively. The SEM results appeared approximately hexagonal platy crystallites morphology for CaAl-SDBS-LDH, with particle size smaller and thinner.

A new approach to prepare ZVI and its application in removal of Cr(VI) from aqueous solution

Zero valent iron (ZVI) was prepared by reducing natural goethite (NG-ZVI) and synthetic goethite (SG-ZVI) in hydrogen at 550 °C. XRD, TEM, FESEM/EDS and specific surface area (SSA) and pore analyser were used to characterize goethites and reduced goethites. Both NG-ZVI and SG-ZVI with a size of nanoscale to several hundreds of nanometers were obtained by reducing goethites at 550 °C. The reductive capacity of the ZVIs was assessed by removal of Cr(VI) at ambient temperature in comparison with that of commercial iron powder (CIP). The effect of contact time, initial concentration and reaction temperature on Cr(VI) removal was investigated. Furthermore, the uptake mechanism was discussed according to isotherms, thermodynamic analysis and the results of XPS. The results showed that SG-ZVI had the best reductive capacity to Cr(VI) and reduced Cr(VI) to Cr(III). The results suggest that hydrogen reduction is a good approach to prepare ZVI and this type of ZVI is potentially useful in remediating heavy metals as a material of permeable reaction barrier.

Detection and quantification of tear phospholipids and cholesterol in contact lens deposits : the effect of contact lens material and lens care solution

PURPOSE. To examine the deposition of tear phospholipids and cholesterol onto worn contact lenses and the effect of lens material and lens care solution. METHODS. Lipids were extracted from tears and worn contact lenses using 2:1 chloroform: Methanol and the extract washed with aqueous ammonium acetate, before analysis by electrospray ionization tandem mass spectrometry (ESI-MS/MS). RESULTS. Twenty-three molecular lipids from the sphingomyelin (SM) and phosphatidylcholine (PC) classes were detected in tears, with total concentrations of each class determined to be 5 ± 1 pmol/μL (~3.8 μg/mL) and 6 ± 1 pmol/μL (~ 4.6μg/mL), respectively. The profile of individual phospholipids in both of these classes was shown to be similar in contact lens deposits. Deposition of representative polar and nonpolar lipids were shown to be significantly higher on senofilcon A contact lenses, with ~59 ng/lens SM, 195 ng/lens PC, and 9.9 μg/lens cholesterol detected, whereas balafilcon A lens extracts contained ~19 ng/lens SM, 19 ng/lens PC, and 3.9 μg/lens cholesterol. Extracts from lenses disinfected and cleaned with two lens care solutions showed no significant differences in total PC and SM concentrations; however, a greater proportion of PC than SM was observed, compared with that in tears. CONCLUSIONS. Phospholipid deposits extracted from worn contact lenses show a molecular profile similar to that in tears. The concentration of representative polar and nonpolar lipids deposited onto contact lenses is significantly affected by lens composition. There is a differential efficacy in the removal of PC and SM with lens care solutions.