Frada Burstein
Monash University, Faculty of Information Technology, Faculty Member
Research Interests:
If different individuals can be shown to behave differently in the presence of the same decision situation, then it is likely that there is a link between the unique personality of an individual and the decisions that that person make.... more
If different individuals can be shown to behave differently in the presence of the same decision situation, then it is likely that there is a link between the unique personality of an individual and the decisions that that person make. Many studies have attempted to manifest individual factors that may affect decision making. If the presence of such factors can be theoretically validated, they can be used as a basis of DSS design. These systems can be expected to provide support that is compatible with the needs of the targeted decision maker. To enable such a systems development paradigm, the effect of specific personality constructs and the methods of extracting those constructs should be articulated. This paper reviews contemporary personality and personality assessment literature and attempts to evaluate whether we currently have the necessary knowledge to undertake the development of decision support systems which can genuinely adapt to the user.
Research Interests:
Research Interests:
Abstract. In this paper, we propose a model for intelligent decision support model that draws upon the integration of case-based reasoning and fuzzy multicriteria decision-making. The model provides intelligent assistance, retrieval,... more
Abstract. In this paper, we propose a model for intelligent decision support model that draws upon the integration of case-based reasoning and fuzzy multicriteria decision-making. The model provides intelligent assistance, retrieval, reminder, and advice to a decision-maker. The ...
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Recent advances in mobile computing and sensor technology have provided new opportunities in data collection and analysis, especially in the medical fields of research. Low back pain is a key area within chronic pain management. It is a... more
Recent advances in mobile computing and sensor technology have provided new opportunities in data collection and analysis, especially in the medical fields of research. Low back pain is a key area within chronic pain management. It is a widespread problem and a major contributor towards disability worldwide. Researchers have concluded that pain can be an individualistic experience. Evidence from other fields of research show that studying the context of the phenomena can allow for a better understanding of its nature. Existing studies may not consider the full context of the patients’ pain, and collect data infrequently (e.g. monthly or yearly). An explanation for this could be due to the cost and difficulty of collecting such data in the past. In this research, we propose a descriptive contextual model that extends a current low back pain model, with contextual attributes and factors. The goal of this research is to provide researchers with a descriptive contextual classification o...
Research Interests:
BACKGROUND Traditional monitoring for adverse events following immunization (AEFI) relies on various established reporting systems, where there is inevitable lag between an AEFI occurring and its potential reporting and subsequent... more
BACKGROUND Traditional monitoring for adverse events following immunization (AEFI) relies on various established reporting systems, where there is inevitable lag between an AEFI occurring and its potential reporting and subsequent processing of reports. AEFI safety signal detection strives to detect AEFI as early as possible, ideally close to real time. Monitoring social media data holds promise as a resource for this. OBJECTIVE The primary aim of this study is to investigate the utility of monitoring social media for gaining early insights into vaccine safety issues, by extracting vaccine adverse event mentions (VAEMs) from Twitter, using natural language processing techniques. The secondary aims are to document the natural language processing techniques used and identify the most effective of them for identifying tweets that contain VAEM, with a view to define an approach that might be applicable to other similar social media surveillance tasks. METHODS A VAEM-Mine method was deve...
Research Interests:
Research Interests:
PurposeThis paper aims to explore the critical success factors (CSFs) necessary for adopting public private partnerships (PPPs) in both Mainland China and Hong Kong.Design/methodology/approachAn empirical questionnaire survey was... more
PurposeThis paper aims to explore the critical success factors (CSFs) necessary for adopting public private partnerships (PPPs) in both Mainland China and Hong Kong.Design/methodology/approachAn empirical questionnaire survey was conducted with relevant experienced practitioners in Mainland China and Hong Kong.FindingsBoth Mainland China and Hong Kong have been keen to deliver more infrastructure service projects through PPP mode, with the former aiming to meet its rapidly growing infrastructure demand and the latter uplifting its efficiency further. The results indicate that Hong Kong does not regard multi‐benefit objectives as importantly as Mainland China. Mainland China on the contrary felt more concerned with an equitable risk sharing mechanism, which is understandable given the problems affecting the financial market in Mainland China.Originality/valueIt is anticipated that the results presented in this paper will assist both the public and private sectors to deliver PPP proje...
Research Interests:
Research Interests:
Research Interests:
Organisational knowledge is that knowledge which is required at a specific instance to meet a specific organisational need. The need may be ongoing or a single occurrence. Meeting that need requires the aggregation of knowledge available... more
Organisational knowledge is that knowledge which is required at a specific instance to meet a specific organisational need. The need may be ongoing or a single occurrence. Meeting that need requires the aggregation of knowledge available at that specific instance. That is, “knowing what you need when you need to know it” (Snowden, 2002). The aim often is to achieve just in time delivery of a product or service to the relevant client base. This strategy to manage organisational knowledge can enhance innovation and creativity within and through the value chain of organisational activity potentially affecting revenue, the quality of staff output, and staff satisfaction.
Research Interests: Business()
()
Research Interests:
ABSTRACT This chapter explores the connections between decisions and knowledge, showing that decision making is a knowledge-intensive endeavor. Decision support systems are technologies that help get the right knowledge to the right... more
ABSTRACT This chapter explores the connections between decisions and knowledge, showing that decision making is a knowledge-intensive endeavor. Decision support systems are technologies that help get the right knowledge to the right decision makers at the right times in the right representations at the right costs. By doing so, these systems help decision making to be more productive, agile, innovative, and/or reputable.
Research Interests:
This chapter identifies parameters that can affect the benefits realized from organizational decision support systems. Some of these factors operate at a micro level. These design parameters stem from characteristics exhibited by the... more
This chapter identifies parameters that can affect the benefits realized from organizational decision support systems. Some of these factors operate at a micro level. These design parameters stem from characteristics exhibited by the organizational decision support system (ODSS). Other parameters affecting ODSS benefits operate at more of a macro level. These contextual parameters are concerned with the relationships between an ODSS and the organization in which it is deployed. Developers, administrators, and researchers of ODSSs need to be cognizant of both design and contextual parameters. The treatments of these parameters for a particular ODSS will affect the value realized from it on both operational and strategic levels. Ultimately, these benefits resolve into an organization’s competitiveness in riding environmental waves while weathering environmental storms.
Research Interests:
Research Interests: Marketing, Sociology, Knowledge Management, Leadership, Social Capital, and 11 moreResource Allocation, Core Competence, Knowledge Economy, Corporate culture, Knowledge Engineering, Resource Management, Awareness, Organisations, Empirical Method, Knowledge Management Strategy, and Psychology and Cognitive Sciences
ABSTRACT The Internet can serve as a source of massive, micro-level data. We discuss the opportunities and challenges in capturing and utilizing real-time data off the Internet, intranets, or extranets. Emphasis is placed on developing... more
ABSTRACT The Internet can serve as a source of massive, micro-level data. We discuss the opportunities and challenges in capturing and utilizing real-time data off the Internet, intranets, or extranets. Emphasis is placed on developing dynamic decision support systems (DSSs) in our new data-enabled environment. Illustrations of real-time data capture and potential DSS use are provided from work on online auctions, e-retailing, piracy, and intellectual property.
Research Interests:
Abstract Here, we argue that decision support systems (DSSs) research is a core area of the information systems (IS) discipline, being one of six major expansions that have occurred in the IS field. Interestingly, DSS research is often... more
Abstract Here, we argue that decision support systems (DSSs) research is a core area of the information systems (IS) discipline, being one of six major expansions that have occurred in the IS field. Interestingly, DSS research is often blended with some other expansions ...
Research Interests:
Length of Stay (LOS) is an important performance metric in Australian Emergency Departments (EDs). Recent evidence suggests that an LOS in excess of 4 h may be associated with increased mortality, but despite this, the average LOS... more
Length of Stay (LOS) is an important performance metric in Australian Emergency Departments (EDs). Recent evidence suggests that an LOS in excess of 4 h may be associated with increased mortality, but despite this, the average LOS continues to remain greater than 4 h in many EDs. Previous studies have found that Data Mining (DM) can be used to help hospitals to manage this metric and there is continued research into identifying factors that cause delays in ED LOS. Despite this, there is still a lack of specific research into how DM could use these factors to manage ED LOS. This study adds to the emerging literature and offers evidence that it is possible to predict delays in ED LOS to offer Clinical Decision Support (CDS) by using DM. Sixteen potentially relevant factors that impact ED LOS were identified through a literature survey and subsequently used as predictors to create six Data Mining Models (DMMs). An extract based on the Victorian Emergency Minimum Dataset (VEMD) was used...
Research Interests:
Research Interests:
article examines knowledge strategy from an empirical cognitive perspective, foregrounding strategic capability and collective intelligence as interrelated concepts. In more general terms, knowledge strategy is focused on a resource-based... more
article examines knowledge strategy from an empirical cognitive perspective, foregrounding strategic capability and collective intelligence as interrelated concepts. In more general terms, knowledge strategy is focused on a resource-based theory of the firm. This exploratory case study provides illustrative data using the cognitive perspective as a guide. Knowledge strategies were investigated in a chosen case that involved a firm engaged with the design and development of new products and technologies.
Research Interests:
Clinicians need to record clinical encounters in written or spoken language, not only for its work-flow naturalness but also for its expressivity, precision, and capacity to convey all required information, which codified structured data... more
Clinicians need to record clinical encounters in written or spoken language, not only for its work-flow naturalness but also for its expressivity, precision, and capacity to convey all required information, which codified structured data is incapable of. Therefore, the structured data which is required for aggregation and analysis must be obtained from clinical text as a later step. Specialised areas of medicine use their own clinical language and clinical coding systems, resulting in unique challenges for the extraction process. Rule-based information extraction techniques have been used effectively in commercial systems and are favoured because they are easily understood and controlled. However, there is promising research into the use of machine learning techniques for extracting information, and this research explores the effectiveness of a hybrid rule-based and machine learning-based audit coding system developed for the neurosurgical department of a major trauma hospital.
Research Interests:
In emergency management for mass gathering, the knowledge about crowd types can highly assist with providing timely response and effective resource allocation. Crowd monitoring can be achieved using computer vision based approaches and... more
In emergency management for mass gathering, the knowledge about crowd types can highly assist with providing timely response and effective resource allocation. Crowd monitoring can be achieved using computer vision based approaches and sensory data analysis. The emergence of social media platforms presents an opportunity to capture valuable information about how people feel and think. However, reviewing current works shows that there are a limited number of studies that use social media in crowd monitoring and/or incorporate a unified crowd model for consistency and interoperability. This presents a novel framework for crowd monitoring using social media. It includes a standard crowd model to represent different types of crowds. The proposed framework considers the effect of emotion on crowd behaviour and uses the emotion analysis of social media to identify the crowd types in an event. An experiment using historical data of a past event to validate our framework and model is descri...
Research Interests:
This paper examines the role of knowledge management and knowledge management systems (KMS) for supporting knowledge work. We argue that an organization benefits from knowledge management systems when it is focused on a specific task as... more
This paper examines the role of knowledge management and knowledge management systems (KMS) for supporting knowledge work. We argue that an organization benefits from knowledge management systems when it is focused on a specific task as knowledge is always task-specific and situated in the specific context in which the task is instantiated. Providing support for knowledge work at the task level complements the work practices of actors performing the task. Such a system supports extended functionality such as reasoning, memory aids, and explanation facilities and learning capability, amongst other facilities. A system with such capability can be defined Knowledge Work Support System. The paper discusses the task-based knowledge management approach at individual and organisational levels and describes its application to the strategy development at an International Bank.
Research Interests:
Knowledge management in a difficult concept but one that is fairly well understood by the Australian financial services sector. These organisations are in the process of implementing some form of strategy to manage knowledge. Many... more
Knowledge management in a difficult concept but one that is fairly well understood by the Australian financial services sector. These organisations are in the process of implementing some form of strategy to manage knowledge. Many organisations that do not claim to have a strategy to manage knowledge are implementing practical steps to do so. The results of this research are compared with previous research in this sector in the UK and Europe that have shown different understandings and strategies to manage it.
Research Interests:
This paper draws on preliminary empirical quantitative research into an understanding of the status of knowledge management in the Australian and New Zealand environments. The relevant literature is surveyed on the role of leadership in... more
This paper draws on preliminary empirical quantitative research into an understanding of the status of knowledge management in the Australian and New Zealand environments. The relevant literature is surveyed on the role of leadership in knowledge management strategies and techniques. This is set against research findings on the roles allocated to lead the knowledge management task. In particular findings within the government sector and the non-government sectors are compared. The paper concludes by presenting a preliminary evaluation of the role of knowledge management leadership within the organisation and suggests that the external influences also play a role
Research Interests:
Research Interests:
Despite polycystic ovary syndrome (PCOS) being the most common endocrine condition affecting reproductive-aged women, studies have shown the information needs of PCOS consumers are not currently met. The expressed need by women with PCOS... more
Despite polycystic ovary syndrome (PCOS) being the most common endocrine condition affecting reproductive-aged women, studies have shown the information needs of PCOS consumers are not currently met. The expressed need by women with PCOS for accessible, evidence-based personalized PCOS information informed the design and development of the PCOS mobile tool-AskPCOS. The App provides a range of unique features such as: evidence-based PCOS health information, self-diagnostic function, a question prompt list to optimize health practitioner engagement, and a commonly asked questions list. A five-phase App development process involved extensive stakeholder consultation, system architecture design, development of the content repository, system prototyping, and evaluation. AskPCOS is the first evidence-based, consumer-driven mobile App developed by women and for women with PCOS and utilizes innovative technology to empower PCOS consumers and optimize health outcomes. The App content reposit...
Research Interests:
The healthcare industry generates a high throughput of medical, clinical and omics data of varying complexity and features. Clinical decision-support is gaining widespread attention as medical institutions and governing bodies turn... more
The healthcare industry generates a high throughput of medical, clinical and omics data of varying complexity and features. Clinical decision-support is gaining widespread attention as medical institutions and governing bodies turn towards better management of this data for effective and efficient healthcare delivery and quality assured outcomes. Amass of data across all stages, from disease diagnosis to palliative care, is further indication of the opportunities and challenges to effective data management, analysis, prediction and optimization techniques as parts of knowledge management in clinical environments. Big Data analytics (BDA) presents the potential to advance this industry with reforms in clinical decision-support and translational research. However, adoption of big data analytics has been slow due to complexities posed by the nature of healthcare data. The success of these systems is hard to predict, so further research is needed to provide a robust framework to ensure ...
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests: Computer Science, Decision Making, Decision Support Systems, Decision support system, Mathematical Sciences, and 10 moreMulticriteria Decision Analysis, Decision Support, Mobile Device, Decision Maker, Decision Support Systems (DSS), Decision Models, Elsevier, Support System, Dynamic Properties, and Quality of data
The healthcare industry generates a high throughput of medical, clinical and omics data of varying complexity and features. Clinical decision-support is gaining widespread attention as medical institutions and governing bodies turn... more
The healthcare industry generates a high throughput of medical, clinical and omics data of varying complexity and features. Clinical decision-support is gaining widespread attention as medical institutions and governing bodies turn towards better management of this data for effective and efficient healthcare delivery and quality assured outcomes. Amass of data across all stages, from disease diagnosis to palliative care, is further indication of the opportunities and challenges to effective data management, analysis, prediction and optimization techniques as parts of knowledge management in clinical environments. Big Data analytics (BDA) presents the potential to advance this industry with reforms in clinical decision-support and translational research. However, adoption of big data analytics has been slow due to complexities posed by the nature of healthcare data. The success of these systems is hard to predict, so further research is needed to provide a robust framework to ensure ...
Research Interests:
Knowledge-based decision support systems (KB-DSS) recommend decision actions based on stored knowledge. One of the challenges in time-critical clinical KB-DSS is the ability to maintain and continually improve the underlying... more
Knowledge-based decision support systems (KB-DSS) recommend decision actions based on stored knowledge. One of the challenges in time-critical clinical KB-DSS is the ability to maintain and continually improve the underlying knowledge-base. This challenge stems from the dynamic nature of the knowledge, and from the time constraints associated with the time critical interventions which do not afford for a traditional knowledge engineering approaches to feasibly occur during actual system usage. This paper explores the proposition that a usage-driven design approach could act as an enabler for the continual improvement of time critical, real-time KB DSS. We will describe a case study of an existing trauma reception and resuscitation time-critical real-time decision support system to express the challenges found in the current implementation and define the information requirements for supporting the proposed approach using a design-science-research methodology.
Research Interests:
The graduation of healthcare delivery from its foundational mainstay into patient-centred care has widespread implications for health and wellbeing. Information systems and technology are front-runners in necessitating this transition. In... more
The graduation of healthcare delivery from its foundational mainstay into patient-centred care has widespread implications for health and wellbeing. Information systems and technology are front-runners in necessitating this transition. In its ideal form, patient-centred care is respectful of and responsive to individual patient preferences, needs, values and ensures that patient values guide all clinical decisions (Epstein et al. 2010). In both its ideal and actual forms, preferences, needs and values connote the significance of information in enabling patient-centred care.
Research Interests:
More people are travelling overseas for health or wellness reasons; however, there is limited understanding of the background of those travelling and how information is sourced for decisionmaking. Those travelling for treatment are likely... more
More people are travelling overseas for health or wellness reasons; however, there is limited understanding of the background of those travelling and how information is sourced for decisionmaking. Those travelling for treatment are likely to be unaware of all of the risks. Reliable information sources are scattered and not easy to find. Interviews were conducted with 51 Australians contemplating or who had travelled for stem cell treatment. Information sources people used were identified, and an analysis was undertaken of how this influenced their decision. The data highlight that health travellers are likely to search extensively using a wide range of sources including information on clinics’ websites, Facebook, blogs, friends and family. Interviewees highlight that often decisions are made based on unreliable sources. The implications are that without quality, reliable information health travellers are at risk of suffering adverse outcomes and spending significant funds without an...
Research Interests: Business()
()
Advances in sensors and mobile technology have helped evolve the use of eHealth, especially in the field of chronic pain. Chronic pain is a widespread problem where self-management is important. Current studies tend to collect data at... more
Advances in sensors and mobile technology have helped evolve the use of eHealth, especially in the field of chronic pain. Chronic pain is a widespread problem where self-management is important. Current studies tend to collect data at sparse intervals due to the cost involved in collecting data using traditional instruments. We demonstrate how technology enables richer data collection frequencies to analyse the influence of patients’ context on their pain levels. In this paper, we present a case study as an add-on analysis to a clinical trial for lateral epicondylitis (tennis elbow). We explore the usefulness of on-line key data collected at higher frequencies in explaining or discovering changes in pain. This dataset allowed us to learn that there are no associations with temperature and humidity to this type of pain, that patients tend to have different pain experiences, and that pain at night tends to be higher than overall or activity-related pain.
Research Interests: Medicine()
()
Clinical auditing requires codified data for aggregation and analysis of patterns. However in the medical domain obtaining structured data can be difficult as the most natural, expressive and comprehensive way to record a clinical... more
Clinical auditing requires codified data for aggregation and analysis of patterns. However in the medical domain obtaining structured data can be difficult as the most natural, expressive and comprehensive way to record a clinical encounter is through natural language. The task of creating structured data from naturally expressed information is known as information extraction. Specialised areas of medicine use their own language and data structures; the translation process has unique challenges, and often requires a fresh approach. This research is devoted to creating a novel semi-automated method for generating codified auditing data from clinical notes recorded in a neurosurgical department in an Australian teaching hospital. The method encapsulates specialist knowledge in rules that instantaneously make precise decisions for the majority of the matches, followed up by dictionary-based matching of the remaining text.
Research Interests:
Design of mobile, personalised healthcare information systems facilitate a paradigm shift in management of chronic conditions. They provide an infrastructure for creating personalised treatment plans that are evidence based. This is... more
Design of mobile, personalised healthcare information systems facilitate a paradigm shift in management of chronic conditions. They provide an infrastructure for creating personalised treatment plans that are evidence based. This is especially important in chronic pain, which is a long-term condition and requires self-management by the patient. In this paper, we use a mobile accessible, web based system to collect daily reports on chronic low back pain. Based on this data a pain trajectory is generated to provide a report for patients to track their pain. We present an empirical study exploring the experiences of the participants, the usability, and issues that encompass frequent data collection using such systems in chronic low back pain.
Clinical intelligence gathered from data analytics plays a significant role in the development of preventive measures and aids the decision-making process. However, due to the scattered and distributed nature of digital healthcare... more
Clinical intelligence gathered from data analytics plays a significant role in the development of preventive measures and aids the decision-making process. However, due to the scattered and distributed nature of digital healthcare records, accessing data for analytics has become a huge challenge. The main reason for that is data custodians being reluctant to disseminate the records to the external entities due to security and privacy concerns. As the ultimate ownership of medical records lies with the individual patient, this is best resolved by integrating patient consent with existing access control mechanisms. Recently, blockchain has been shown as a promising technology to provide secure and privacy-preserving data sharing on distributed and decentralized environments. Therefore, to cater the requirement of privacy-preserving data acquisition for clinical data analytics in the modern digital health networks, we propose a dynamic consent management architecture leveraging blockch...
Diagrams for four different health care settings have been proposed: Snapshot Diagram, Diagnosis Diagram, Strength of Evidence Diagram and Patient Pathway Diagram. The availability of large amount of digital health care data and potential... more
Diagrams for four different health care settings have been proposed: Snapshot Diagram, Diagnosis Diagram, Strength of Evidence Diagram and Patient Pathway Diagram. The availability of large amount of digital health care data and potential to utilize its benefits led to the development of these diagrams. This paper presents an analysis of the diagrams based on the selection of a subset of Gestalt principles deemed relevant for each diagram. Although Gestalt and human-computer interaction principles are advanced to apply to all diagrams or user interfaces, in practice a sub-set of principles must be selected to evaluate a diagram or interface. The selection of a subset of principles to use on a diagram has not been widely studied. This paper presents an approach for identifying a subset of relevant Gestalt principles tailored for each of the four diagrams advanced for health care settings.