The reliability of information on work-related injuries available from hospitalisation data in Australia

Objective: To examine the reliability of work-related activity coding for injury-related hospitalisations in Australia. Method: A random sample of 4373 injury-related hospital separations from 1 July 2002 to 30 June 2004 were obtained from a stratified random sample of 50 hospitals across 4 states in Australia. From this sample, cases were identified as work-related if they contained an ICD-10-AM work-related activity code (U73) allocated by either: (i) the original coder; (ii) an independent auditor, blinded to the original code; or (iii) a research assistant, blinded to both the original and auditor codes, who reviewed narrative text extracted from the medical record. The concordance of activity coding and number of cases identified as work-related using each method were compared. Results: Of the 4373 cases sampled, 318 cases were identified as being work-related using any of the three methods for identification. The original coder identified 217 and the auditor identified 266 work-related cases (68.2% and 83.6% of the total cases identified, respectively). Around 10% of cases were only identified through the text description review. The original coder and auditor agreed on the assignment of work-relatedness for 68.9% of cases. Conclusions and Implications: The current best estimates of the frequency of hospital admissions for occupational injury underestimate the burden by around 32%. This is a substantial underestimate that has major implications for public policy, and highlights the need for further work on improving the quality and completeness of routine, administrative data sources for a more complete identification of work-related injuries.

The information systems discipline in Australian universities : a contextual framework

This chapter presents the contextual framework for the second phase of a multi-method, multiple study of the information systems (IS) academic discipline in Australia. The chapter outlines the genesis of a two-phase Australian study, and positions the study as the precursor to a larger Pacific-Asia study. Analysis of existing literature on the state of IS and on relevant theory underpins a series of individual Australian state case studies summarised in this chapter and represented as separate chapters in the book. This chapter outlines the methodological approach employed, with emphasis on the case-study method of the multiple state studies. The process of multiple peer review of the studies is described. Importantly, this chapter summarises and analyses each of the subsequent chapters of this book, emphasising the role of a framework developed to guide much of the data gathering and analysis. This chapter also highlights the process involved in conducting the meta-analysis reported in the final chapter of this book, and summarises some of the main results of the meta-analysis.

Formative and reflective measurement and validation mismatch in survey research : an archival analysis of information systems success constructs 1985-2007

The generic IS-success constructs first identified by DeLone and McLean (1992) continue to be widely employed in research. Yet, recent work by Petter et al (2007) has cast doubt on the validity of many mainstream constructs employed in IS research over the past 3 decades; critiquing the almost universal conceptualization and validation of these constructs as reflective when in many studies the measures appear to have been implicitly operationalized as formative. Cited examples of proper specification of the Delone and McLean constructs are few, particularly in light of their extensive employment in IS research. This paper introduces a four-stage formative construct development framework: Conceive > Operationalize > Respond > Validate (CORV). Employing the CORV framework in an archival analysis of research published in top outlets 1985-2007, the paper explores the extent of possible problems with past IS research due to potential misspecification of the four application-related success dimensions: Individual-Impact, Organizational-Impact, System-Quality and Information-Quality. Results suggest major concerns where there is a mismatch of the Respond and Validate stages. A general dearth of attention to the Operationalize and Respond stages in methodological writings is also observed.

Long-term outcomes of seriously injured children : a study using the Child Health Questionnaire

Objective: To assess the health-related quality of life (HRQoL) in children 1-2 years after they had sustained an injury. Methods: Parents of all children who were identified by the Queensland Trauma Registry during their admission to either of the two paediatric specialty hospitals in Brisbane, Australia, for the treatment of an injury, were invited to participate in this study. Parents who consented to participation received a copy of the Child Health Questionnaire (CHQ) that required them to provide information regarding their child’s HRQoL following injury. The CHQ scores for the study respondents were compared with those of the Australian norms. This study was approved by the relevant ethics committees. Results: Two hundred and forty-one completed questionnaires were returned. The majority of cases were male (65%) and there was even representation across all age groups. The majority of injuries were considered to be minor (81%) and were predominantly the result of falls and cycling accidents causing mainly fractures and intracranial injury. On the majority of subscales of the CHQ, study participants recorded scores that were statistically significantly below those of the Australian norms. None of the relevant variables collected by the Queensland Trauma Registry were found to predict scores on the CHQ in this study (for those children hospitalized for >24 h). Conclusion: Injured children are worse off than their Australian counterparts in terms of HRQoL even up to 2 years following an injury. Further research needs to be undertaken to identify factors that predict lower HRQoL in order to reduce the burden of injury on children and their families.

A 5 year review of information requests to QISU

The Queensland Injury Surveillance Unit (QISU) has been collecting and analysing injury data in Queensland since 1988. QISU data is collected from participating emergency departments (EDs) in urban, rural and remote areas of Queensland. Using this data, QISU produces several injury bulletins per year on selected topics, providing a picture of Queensland injury, and setting this in the context of relevant local, national and international research and policy. These bulletins are used by numerous government and non-government groups to inform injury prevention and practice throughout the state. QISU bulletins are also used by local and state media to inform the general public of injury risk and prevention strategies. In addition to producing the bulletins, QISU regularly responds to requests for information from a variety of sources. These requests often require additional analysis of QISU data to tailor the response to the needs of the end user. This edition of the bulletin reviews 5 years of information requests to QISU.

Assessing information systems success models : empirical comparison (Research in Progress)

Information System (IS) success may be the most arguable and important dependent variable in the IS field. The purpose of the present study is to address IS success by empirically assess and compare DeLone and McLean’s (1992) and Gable’s et al. (2008) models of IS success in Australian Universities context. The two models have some commonalities and several important distinctions. Both models integrate and interrelate multiple dimensions of IS success. Hence, it would be useful to compare the models to see which is superior; as it is not clear how IS researchers should respond to this controversy.

Evaluating information systems

The book within which this chapter appears is published as a research reference book (not a coursework textbook) on Management Information Systems (MIS) for seniors or graduate students in Chinese universities. It is hoped that this chapter, along with the others, will be helpful to MIS scholars and PhD/Masters research students in China who seek understanding of several central Information Systems (IS) research topics and related issues. The subject of this chapter - ‘Evaluating Information Systems’ - is broad, and cannot be addressed in its entirety in any depth within a single book chapter. The chapter proceeds from the truism that organizations have limited resources and those resources need to be invested in a way that provides greatest benefit to the organization. IT expenditure represents a substantial portion of any organization’s investment budget and IT related innovations have broad organizational impacts. Evaluation of the impact of this major investment is essential to justify this expenditure both pre- and post-investment. Evaluation is also important to prioritize possible improvements. The chapter (and most of the literature reviewed herein) admittedly assumes a blackbox view of IS/IT1, emphasizing measures of its consequences (e.g. for organizational performance or the economy) or perceptions of its quality from a user perspective. This reflects the MIS emphasis – a ‘management’ emphasis rather than a software engineering emphasis2, where a software engineering emphasis might be on the technical characteristics and technical performance. Though a black-box approach limits diagnostic specificity of findings from a technical perspective, it offers many benefits. In addition to superior management information, these benefits may include economy of measurement and comparability of findings (e.g. see Part 4 on Benchmarking IS). The chapter does not purport to be a comprehensive treatment of the relevant literature. It does, however, reflect many of the more influential works, and a representative range of important writings in the area. The author has been somewhat opportunistic in Part 2, employing a single journal – The Journal of Strategic Information Systems – to derive a classification of literature in the broader domain. Nonetheless, the arguments for this approach are believed to be sound, and the value from this exercise real. The chapter drills down from the general to the specific. It commences with a highlevel overview of the general topic area. This is achieved in 2 parts: - Part 1 addressing existing research in the more comprehensive IS research outlets (e.g. MISQ, JAIS, ISR, JMIS, ICIS), and Part 2 addressing existing research in a key specialist outlet (i.e. Journal of Strategic Information Systems). Subsequently, in Part 3, the chapter narrows to focus on the sub-topic ‘Information Systems Success Measurement’; then drilling deeper to become even more focused in Part 4 on ‘Benchmarking Information Systems’. In other words, the chapter drills down from Parts 1&2 Value of IS, to Part 3 Measuring Information Systems Success, to Part 4 Benchmarking IS. While the commencing Parts (1&2) are by definition broadly relevant to the chapter topic, the subsequent, more focused Parts (3 and 4) admittedly reflect the author’s more specific interests. Thus, the three chapter foci – value of IS, measuring IS success, and benchmarking IS - are not mutually exclusive, but, rather, each subsequent focus is in most respects a sub-set of the former. Parts 1&2, ‘the Value of IS’, take a broad view, with much emphasis on ‘the business Value of IS’, or the relationship between information technology and organizational performance. Part 3, ‘Information System Success Measurement’, focuses more specifically on measures and constructs employed in empirical research into the drivers of IS success (ISS). (DeLone and McLean 1992) inventoried and rationalized disparate prior measures of ISS into 6 constructs – System Quality, Information Quality, Individual Impact, Organizational Impact, Satisfaction and Use (later suggesting a 7th construct – Service Quality (DeLone and McLean 2003)). These 6 constructs have been used extensively, individually or in some combination, as the dependent variable in research seeking to better understand the important antecedents or drivers of IS Success. Part 3 reviews this body of work. Part 4, ‘Benchmarking Information Systems’, drills deeper again, focusing more specifically on a measure of the IS that can be used as a ‘benchmark’3. This section consolidates and extends the work of the author and his colleagues4 to derive a robust, validated IS-Impact measurement model for benchmarking contemporary Information Systems (IS). Though IS-Impact, like ISS, has potential value in empirical, causal research, its design and validation has emphasized its role and value as a comparator; a measure that is simple, robust and generalizable and which yields results that are as far as possible comparable across time, across stakeholders, and across differing systems and systems contexts.