Designing a quality health information system: Case study analysis of maternal and child health in Papua New Guinea

Papua New Guinea (PNG) is facing what must seem like an insurmountable challenge to deliver quality healthcare servicesfor women living in both rural and urban areas. Glo bal governing bodies and donor agencies including WHO and UN have indicated that PNG does not have an appropriate health information system. Although there are some systems in place, to date, little research has been conducted on improving or resolving the data integrity and integration issues of the existing health information systems and automating the capture of women and newborns information in PNG. This current research study concentrates on the adoption of eHealth, as an innovative tool to strengthen the health information systems in PNG to meet WHO standards. The research targets maternal and child health focussing on child birth records asan exemplar...

Information Accountability of Healthcare Big Data

Huge amount of data are generated from a variety of information sources in healthcare while the data sources originate from a veracity of clinical information systems and corporate data warehouses. The data derived from the above data sources are used for analysis and trending purposes thus playing an influential role as a real time decision-making tool. The unstructured, narrative data provided by these data sources qualify as healthcare big-data and researchers argue that the application of big-data in healthcare might enable the accountability and efficiency.

Firms’ information system characteristics and management accounting adaptability

This study explores the relationship between the qualities of an information system and management accounting adaptability (MAA) and effectiveness in firms. Design/methodology/approach I develop and empirically test a model where the qualities of the information system and management accounting effectiveness are mediated by MAA. Findings Information system flexibility (ISF) and shared knowledge had a significant and positive correlation with MAA, which in turn had a positive and significant correlation with management accounting effectiveness. There was also a moderation effect of ISF on the correlation betweeen information system integration and MAA. Research implications Information system integration may not lead to management accounting stability, but the lack of flexibility of a system and a lack of cooperation between the stakeholders might lead to its stagnation. Practical implications Organizations are advised to implement solutions that are relatively flexible and modular, as well as encourage cooperation between stakeholders to fully leverage and improve the existing and future systems. Originality/value The study extends the discourse on the interaction between management accounting and information systems by exploring the role of a number of factors that drive MAA.

Tracking the patient journey by combining multiple hospital database systems

With new national targets for patient flow in public hospitals designed to increase efficiencies in patient care and resource use, better knowledge of events affecting length of stay will support improved bed management and scheduling of procedures. This paper presents a case study involving the integration of material from each of three databases in operation at one tertiary hospital and demonstrates it is possible to follow patient journeys from admission to discharge. What is known about this topic? At present, patient data at one Queensland tertiary hospital are assembled in three information systems: (1) the Hospital Based Corporate Information System (HBCIS), which tracks patients from in-patient admission to discharge; (2) the Emergency Department Information System (EDIS) containing patient data from presentation to departure from the emergency department; and (3) Operation Room Management Information System (ORMIS), which records surgical operations. What does this paper add? This paper describes how a new enquiry tool may be used to link the three hospital information systems for studying the hospital journey through different wards and/or operating theatres for both individual and groups of patients. What are the implications for practitioners? An understanding of the patients’ journeys provides better insight into patient flow and provides the tool for research relating to access block, as well as optimising the use of physical and human resources.

“It’s in the syllabus”: Identifying information literacy and data information literacy opportunities using a grounded theory approach

Developing innovative library services requires a real world understanding of faculty members' desired curricular goals. This study aimed to develop a comprehensive and deeper understanding of Purdue's nutrition science and political science faculties' expectations for student learning related to information and data information literacies. Course syllabi were examined using grounded theory techniques that allowed us to identify how faculty were addressing information and data information literacies in their courses, but it also enabled us to understand the interconnectedness of these literacies to other departmental intentions for student learning, such as developing a professional identity or learning to conduct original research. The holistic understanding developed through this research provides the necessary information for designing and suggesting information literacy and data information literacy services to departmental faculty in ways supportive of curricular learning outcomes.

Indonesian library and information science professionals’ understanding of Library 2.0: A pilot study

The literature around Library 2.0 remains largely theoretical with few empirical studies and is particularly limited in developing countries such as Indonesia. This study addresses this gap and aims to provide information about the current state of knowledge on Indonesian LIS professionals’ understanding of Library 2.0. The researchers used qualitative and quantitative approaches for this study, asking thirteen closed- and open-ended questions in an online survey. The researchers used descriptive and in vivo coding to analyze the responses. Through their analysis, they identified three themes: technology, interactivity, and awareness of Library 2.0. Respondents demonstrated awareness of Library 2.0 and a basic understanding of the roles of interactivity and technology in libraries. However, overreliance on technology used in libraries to conceptualize Library 2.0 without an emphasis on its core characteristics and principles could lead to the misalignment of limited resources. The study results will potentially strengthen the research base for Library 2.0 practice as well as inform LIS curriculum in Indonesia so as to develop practitioners who are able to adapt to users’ changing needs and expectations. It is expected that the preliminary data from this study could be used to design a much larger and more complex future research project in this area.

Ideologies and their points of view

It is well known that different arguments appeal to different people. We all process information in ways that are adapted to be consistent with our underlying ideologies. These ideologies can sometimes be framed in terms of particular axes or dimensions, which makes it possible to represent some aspects of an ideology as a region in the kind of vector space that is typical of many generalised quantum models. Such models can then be used to explain and predict, in broad strokes, whether a particular argument or proposal is likely to appeal to an individual with a particular ideology. The choice of suitable arguments to bring about desired actions is traditionally part of the art or science of rhetoric, and today's highly polarised society means that this skill is becoming more important than ever. This paper presents a basic model for understanding how different goals will appeal to people with different ideologies, and thus how different rhetorical positions can be adopted to promote the same desired outcome. As an example, we consider different narratives and hence actions with respect to the environment and climate change, an important but currently highly controversial topic.

Exploring variation in the ways of experiencing health information literacy: A phenomenographic study

From a relational perspective of information literacy, health information literacy is interpreted as the different ways in which people experience using information to learn about health. Phenomenography was used as a research approach to explore variation in people's experience of using information to learn about health from data collected through semi-structured interviews. The findings identify seven categories that describe the qualitatively different ways in which people experience health information literacy: building a new knowledge base;weighing up information; discerning valid information; paying attention to bodily information; staying informed about health; Participating in learning communities, and envisaging health. These findings can be used to enhance awareness about the different ways of experiencing health information literacy, and to contribute to a nascent trajectory of research that has explored information literacy within the context of everyday life.

Agile innovation: Innovating with enterprise systems

The contemporary organisations are presented with an eclectic collection of technologies that has dramatically shifted the process of innovation. This thesis investigates the nature and the process of attaining innovation through the modern IT portfolio. A qualitative study of nine organizations was conducted. The results identified that the modern IT portfolio innovates through a new innovation process called 'agile innovation,' which differs from the existing innovation types.

Informed learning in the undergraduate classroom: The role of information experiences in shaping outcomes

This research aimed to inform the design of effective information literacy lessons in higher education. Phenomenography, a research approach designed to study human experience, was used to explore the experiences of a teacher and undergraduate students using information to learn about language and gender issues. The findings show that the way learners use information influences content-focused learning outcomes, and reveal an instructional pattern for enabling students to use information while becoming aware of the topic they are investigating. Based on the findings, a design model is offered in which learning outcomes are realized through targeted information literacy activities.

Analysis of word embeddings and sequence features for clinical information extraction

This study investigates the use of unsupervised features derived from word embedding approaches and novel sequence representation approaches for improving clinical information extraction systems. Our results corroborate previous findings that indicate that the use of word embeddings significantly improve the effectiveness of concept extraction models; however, we further determine the influence that the corpora used to generate such features have. We also demonstrate the promise of sequence-based unsupervised features for further improving concept extraction.

Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.

Integrating and evaluating neural word embeddings in information retrieval

Recent advances in neural language models have contributed new methods for learning distributed vector representations of words (also called word embeddings). Two such methods are the continuous bag-of-words model and the skipgram model. These methods have been shown to produce embeddings that capture higher order relationships between words that are highly effective in natural language processing tasks involving the use of word similarity and word analogy. Despite these promising results, there has been little analysis of the use of these word embeddings for retrieval. Motivated by these observations, in this paper, we set out to determine how these word embeddings can be used within a retrieval model and what the benefit might be. To this aim, we use neural word embeddings within the well known translation language model for information retrieval. This language model captures implicit semantic relations between the words in queries and those in relevant documents, thus producing more accurate estimations of document relevance. The word embeddings used to estimate neural language models produce translations that differ from previous translation language model approaches; differences that deliver improvements in retrieval effectiveness. The models are robust to choices made in building word embeddings and, even more so, our results show that embeddings do not even need to be produced from the same corpus being used for retrieval.

Information sharing in distance collaboration: A software engineering perspective

Information sharing in distance collaboration: A software engineering perspective, QueenslandFactors in software engineering workgroups such as geographical dispersion and background discipline can be conceptually characterized as "distances", and they are obstructive to team collaboration and information sharing. This thesis focuses on information sharing across multidimensional distances and develops an information sharing distance model, with six core dimensions: geography, time zone, organization, multi-discipline, heterogeneous roles, and varying project tenure. The research suggests that the effectiveness of workgroups may be improved through mindful conducts of information sharing, especially proactive consideration of, and explicit adjustment for, the distances of the recipient when sharing information.

An insight into the adoption of accountable-eHealth systems: n empirical research model based on the Australian context

This paper provides a first look at the acceptance of Accountable-eHealth (AeH) systems–a new genre of eHealth systems designed to manage information privacy concerns that hinder the proliferation of eHealth. The underlying concept of AeH systems is appropriate use of information through after-the-fact accountability for intentional misuse of information by healthcare professionals. An online questionnaire survey was utilised for data collection from three educational institutions in Queensland, Australia. A total of 23 hypotheses relating to 9 constructs were tested using a structural equation modelling technique. The moderation effects on the hypotheses were also tested based on six moderation factors to understand their role on the designed research model. A total of 334 valid responses were received. The cohort consisted of medical, nursing and other health related students studying at various levels in both undergraduate and postgraduate courses. Hypothesis testing provided sufficient data to accept 7 hypotheses. The empirical research model developed was capable of predicting 47.3% of healthcare professionals’ perceived intention to use AeH systems. All six moderation factors showed significant influence on the research model. A validation of this model with a wider survey cohort is recommended as a future study.