Are library and information professionals ready for evidence based practice?

Evidence based practice (EBP) is recognised as a way of improving the quality of professional practice in many disciplines however its adoption within library and information sciences (LIS) has been gradual. The term was first introduced into the library and information profession‟s vocabulary a decade ago but an impediment to its uptake is the lack of clear understanding regarding how LIS practitioners understand the concept. Partridge, Thorpe, Edwards and Hallam (2007) identified the need to understand how LIS professionals experience or understand evidence based practice and proposed a model of four categories of experience to describe how LIS professionals experience EBP. This paper extends that framework by refining the different conceptions of evidence based practice and identifying relationships which exist between the categories of experience to provide a rich description of the EBP phenomenon. The paper also argues that the phrase “evidence based librarianship” and its variations be abandoned as practitioners do not see a distinction between EBP as applied to librarianship and information practice and industry specific jargon like “evidence based library and information practice”. This research will help current and future LIS practitioners, leaders and educators engage more actively in the establishment of an evidence based culture to improve library and information practice in Australia and internationally.

Nutritional status and information needs of medical oncology patients receiving treatment at an Australian public hospital

This study aimed to identify: i) the prevalence of malnutrition according to the scored Patient Generated-Subjective Global Assessment (PG-SGA); ii) utilization of available nutrition resources; iii) patient nutrition information needs; and iv) external sources of nutrition information. An observational, cross-sectional study was undertaken at an Australian public hospital on 191 patients receiving oncology services. According to PG-SGA, 49% of patients were malnourished and 46% required improved symptom management and/or nutrition intervention. Commonly reported nutrition-impact symptoms included: peculiar tastes (31%), no appetite (24%) and nausea (24%). External sources of nutrition information were accessed by 37%, with popular choices being media/internet (n=19) and family/friends (n=13). In a sub-sample (n=65), 32 patients were aware of the available nutrition resources, 23 thought the information sufficient and 19 patients had actually read them. Additional information on supplements and modifying side effects was requested by 26 patients. Malnutrition is common in oncology patients receiving treatment at an Australian public hospital and almost half require improved symptom management and/or nutrition intervention. Patients who read the available nutrition information found it useful, however awareness of these nutrition resources and the provision of information on supplementation and managing symptoms requires attention.

The impact of health information technology on the quality of medical and health care : a systematic review

Objective: To systematically review the published evidence of the impact of health information technology (HIT) on the quality of medical and health care specifically clinicians’ adherence to evidence-based guidelines and the corresponding impact this had on patient clinical outcomes. In order to be as inclusive as possible the research examined literature discussing the use of health information technologies and systems in both medical care such as clinical and surgical, and other health care such as allied health and preventive services.----- Design: Systematic review----- Data Sources: Relevant literature was systematically searched on English language studies indexed in MEDLINE and CINAHL(1998 to 2008), Cochrane Library, PubMed, Database of Abstracts of Review of Effectiveness (DARE), Google scholar and other relevant electronic databases. A search for eligible studies (matching the inclusion criteria) was also performed by searching relevant conference proceedings available through internet and electronic databases, as well as using reference lists identified from cited papers.----- Selection criteria: Studies were included in the review if they examined the impact of Electronic Health Record (EHR), Computerised Provider Order-Entry (CPOE), or Decision Support System (DS); and if the primary outcomes of the studies were focused on the level of compliance with evidence-based guidelines among clinicians. Measures could be either changes in clinical processes resulting from a change of the providers’ behaviour or specific patient outcomes that demonstrated the effectiveness of a particular treatment given by providers. ----- Methods: Studies were reviewed and summarised in tabular and text form. Due to heterogeneity between studies, meta-analysis was not performed.----- Results: Out of 17 studies that assessed the impact of health information technology on health care practitioners’ performance, 14 studies revealed a positive improvement in relation to their compliance with evidence-based guidelines. The primary domain of improvement was evident from preventive care and drug ordering studies. Results from the studies that included an assessment for patient outcomes however, were insufficient to detect either clinically or statistically important improvements as only a small proportion of these studies found benefits. For instance, only 3 studies had shown positive improvement, while 5 studies revealed either no change or adverse outcomes.----- Conclusion: Although the number of included studies was relatively small for reaching a conclusive statement about the effectiveness of health information technologies and systems on clinical care, the results demonstrated consistency with other systematic reviews previously undertaken. Widescale use of HIT has been shown to increase clinician’s adherence to guidelines in this review. Therefore, it presents ongoing opportunities to maximise the uptake of research evidence into practice for health care organisations, policy makers and stakeholders.

Personalised ontology learning and mining for web information gathering

Over the last decade, the rapid growth and adoption of the World Wide Web has further exacerbated user needs for e±cient mechanisms for information and knowledge location, selection, and retrieval. How to gather useful and meaningful information from the Web becomes challenging to users. The capture of user information needs is key to delivering users' desired information, and user pro¯les can help to capture information needs. However, e®ectively acquiring user pro¯les is di±cult. It is argued that if user background knowledge can be speci¯ed by ontolo- gies, more accurate user pro¯les can be acquired and thus information needs can be captured e®ectively. Web users implicitly possess concept models that are obtained from their experience and education, and use the concept models in information gathering. Prior to this work, much research has attempted to use ontologies to specify user background knowledge and user concept models. However, these works have a drawback in that they cannot move beyond the subsumption of super - and sub-class structure to emphasising the speci¯c se- mantic relations in a single computational model. This has also been a challenge for years in the knowledge engineering community. Thus, using ontologies to represent user concept models and to acquire user pro¯les remains an unsolved problem in personalised Web information gathering and knowledge engineering. In this thesis, an ontology learning and mining model is proposed to acquire user pro¯les for personalised Web information gathering. The proposed compu- tational model emphasises the speci¯c is-a and part-of semantic relations in one computational model. The world knowledge and users' Local Instance Reposito- ries are used to attempt to discover and specify user background knowledge. From a world knowledge base, personalised ontologies are constructed by adopting au- tomatic or semi-automatic techniques to extract user interest concepts, focusing on user information needs. A multidimensional ontology mining method, Speci- ¯city and Exhaustivity, is also introduced in this thesis for analysing the user background knowledge discovered and speci¯ed in user personalised ontologies. The ontology learning and mining model is evaluated by comparing with human- based and state-of-the-art computational models in experiments, using a large, standard data set. The experimental results are promising for evaluation. The proposed ontology learning and mining model in this thesis helps to develop a better understanding of user pro¯le acquisition, thus providing better design of personalised Web information gathering systems. The contributions are increasingly signi¯cant, given both the rapid explosion of Web information in recent years and today's accessibility to the Internet and the full text world.

Open Access and Public Sector Information : Policy Developments in Australia and Key Jurisdictions

This book chapter considers recent developments in Australia and key jurisdictions both in relation to the formation of a national information strategy and the management of legal rights in public sector information.

Consumer trends in digital news and information in Australia

We all know that the future of news is digital. But mainstream news providers are still grappling with how to entice more customers to their online sites. This paper provides context for a survey currently underway on user intentions towards online news and entertainment, by exploring: 1. Consumer behaviours and intentions with regards to accessing online news and information; 2. Current trends in the Australian online news and information sector; and 3. Key issues and emerging opportunities in the Australian (and global) environment. Key influences on use of online news and information are pricing and access. The paper highlights emerging technical opportunities and flags service gaps. These gaps include multiple disconnects between: 1. Changing user intentions towards online and location based news (news based on a specific locality as chosen by the user) and information; 2. The ability by consumers to act on these intentions via the availability and cost of technologies; 3. Younger users may prefer entertainment to news, or ‘infotainment’; and 4. Current online offerings of traditional news providers and opportunities. These disconnects present an opportunity for online news suppliers to appraise and resolve. Doing so may enhance their online news and information offering, attract consumers and improve loyalty. Outcomes from this paper will be used to identify knowledge gaps and contribute to the development of further analysis on Australian consumers and their behaviours and intentions towards online news and information. This will be undertaken via focus groups as part of a broader study.

Predicate-based key exchange

We provide the first description of and security model for authenticated key exchange protocols with predicate-based authentication. In addition to the standard goal of session key security, our security model also provides for credential privacy: a participating party learns nothing more about the other party's credentials than whether they satisfy the given predicate. Our model also encompasses attribute-based key exchange since it is a special case of predicate-based key exchange.---------- We demonstrate how to realize a secure predicate-based key exchange protocol by combining any secure predicate-based signature scheme with the basic Diffie-Hellman key exchange protocol, providing an efficient and simple solution.

The mobile Internet and small business : an exploratory study of needs, uses and adoption with full-adopters of technology

The technological environment in which contemporary small and medium-sized enterprises (SMEs) operate can only be described as dynamic. The exponential rate of technological change, characterised by perceived increases in the benefits associated with various technologies, shortening product life cycles and changing standards, provides for the SME a complex and challenging operational context. The primary aim of this research was to concentrate on those SMEs that had already adopted technology in order to identify their needs for the new mobile data technologies (MDT), the mobile Internet. The research design utilised a mixed approach whereby both qualitative and quantitative data was collected to address the question. Overall, the needs of these SMEs for MDT can be conceptualised into three areas where the technology will assist business practices; communication, eCommerce and security.

Mobile data technology for small business : needs, uses, and adoption

The technological environment in which contemporary small and medium-sized enterprises (SMEs) operate can only be described as dynamic. The exponential rate of technological change, characterised by perceived increases in the benefits associated with various technologies, shortening product life cycles and changing standards, provides the SME a complex and challenging operational context. The primary aim of this research was to identify the needs of SMEs in regional areas for mobile data technologies (MDT). In this study a distinction was drawn between those respondents who were full-adopters of technology, those who were partial-adopters and those who were non-adopters and these three segments articulated different needs and requirements for MDT. Overall the needs of regional SMEs for MDT can be conceptualised into three areas where the technology will assist business practices, communication, e-commerce and security.

Encryption safe harbours and data breach notification laws

Data breach notification laws require organisations to notify affected persons or regulatory authorities when an unauthorised acquisition of personal data occurs. Most laws provide a safe harbour to this obligation if acquired data has been encrypted. There are three types of safe harbour: an exemption; a rebuttable presumption and factor-based analysis. We demonstrate, using three condition-based scenarios, that the broad formulation of most encryption safe harbours is based on the flawed assumption that encryption is the silver bullet for personal information protection. We then contend that reliance upon an encryption safe harbour should be dependent upon a rigorous and competent risk-based review that is required on a case-by-case basis. Finally, we recommend the use of both an encryption safe harbour and a notification trigger as our preferred choice for a data breach notification regulatory framework.

Stakeholder perspectives regarding the mandatory notification of Australian data breaches

The advent of data breach notification laws in the United States (US) has unearthed a significant problem involving the mismanagement of personal information by a range of public and private sector organisations. At present, there is currently no statutory obligation under Australian law requiring public or private sector organisations to report a data breach of personal information to law enforcement agencies or affected persons. However, following a comprehensive review of Australian privacy law, the Australian Law Reform Commission (ALRC) has recommended the introduction of a mandatory data breach notification scheme. The issue of data breach notification has ignited fierce debate amongst stakeholders, especially larger private sector entities. The purpose of this article is to document the perspectives of key industry and government representatives to identify their standpoints regarding an appropriate regulatory approach to data breach notification in Australia.

A Two-stage information filtering based on rough decision rule and pattern mining

Information Overload and Mismatch are two fundamental problems affecting the effectiveness of information filtering systems. Even though both term-based and patternbased approaches have been proposed to address the problems of overload and mismatch, neither of these approaches alone can provide a satisfactory solution to address these problems. This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern-based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experimental results based on the RCV1 corpus show that the proposed twostage filtering model significantly outperforms the both termbased and pattern-based information filtering models.