Managers who work in publicly funded healthcare organizations are an understudied group. Some of the influences on their decisions may be unique to healthcare. This study considers how to integrate research knowledge effectively into healthcare managers' decision making, and how to manage and integrate information that will include community data. This first phase in a two-phase mixed methods research study used a qualitative, multiple case studies design. Nineteen semi-structured interviews were undertaken using the critical incident technique. Interview transcripts were analysed using the NatCen Framework. One theme represented `information and decisions'. Cases were determined to involve complex multi-level, multi-situational decisions with participants in practical rather than ceremonial work roles. Most considered organizational knowledge in the first two decision phases and external knowledge, including research, in the third phase. All participants engaged in satisficing to some degree.

This research extends and tests principles to establish good practice and overcome practical barriers in the strategic management of data quality. The research explores the issues that define and control data quality in national health data collections and the mechanisms and frameworks that can be developed to achieve and sustain good data quality. The aim is to make the strategic management of data quality, and the prevention of persistent errors, everyday, `institutionalized' activities. Using action research methodology and a combination of interpretive and positivist data collection and analysis methods, this research provides the health informatics community with an understanding of the issues related to developing and implementing programmes to improve data quality. Healthcare is a complex system that is highly political and culturally diverse, and applied health informatics research is essential to improve outcomes and performance.

A topic map is implemented for learning about clinical data associated with a hospital stay for patients diagnosed with chronic kidney disease, diabetes and hypertension. The question posed is: how might a topic map help bridge perspectival differences among communities of practice and help make commensurable the different classifications they use? The knowledge layer of the topic map was generated from existing ontological relationships in nosological, lexical, semantic and HL7 boundary objects. Discharge summaries, patient charts and clinical data warehouse entries reified the clinical knowledge used in practice. These clinical data were normalized to HL7 Clinical Document Architecture (CDA) markup standard and stored in the Clinical Document Repository. Each CDA entry was given a subject identifier and linked with the topic map. The ability of topic maps to function as the infostructure `glue' is assessed using dimensions of semantic interoperability and commensurability.

This paper describes the experiences of the Eastern Head Injury Study in creating a strategic regional head injury service framework using a collaborative action research methodology. The types of data, information and knowledge required to develop and support such a framework for both development and successful implementation are identified. This includes the identification of existing knowledge/information systems, the variability and gaps in these, and how the systems fit together, using a number of evidence-gathering and knowledge-sharing methods. The discussion debates the value of the action research approach and what principles are necessary in developing and maintaining knowledge networks. The project demonstrates that an understanding of the social learning cycle can help in understanding how the pieces fit together, and how the information systems need to be in place to provide the information (or data or knowledge) in the appropriate format to make the learning possible.

Cancer is the second most threatening disease in the world today, not only because of its mortality rate, but also due to the brutal changes it imposes on the patient's life, and the fact that its exact causes of progression remain to be discovered. Recent evolution in computer technology has resulted in the emergence of a combined approach to the diagnosis and prognosis process, with a data driven analytical approach complementing biomedical and clinical methods. Cost-sensitive learning is one such data mining method, particularly well suited for medical problems. This paper investigates the performance of a new system based on a hybrid cost-sensitive algorithm (ProICET) on a prostate cancer medical dataset, while trying to produce new medical knowledge. The target of such a system is to reduce the total cost while keeping a high classification accuracy.

Ageing populations and unhealthy lifestyles have led to some chronic conditions such as diabetes and heart disease reaching epidemic proportions in many developed nations. This paper explores the potential of mobile technologies to improve this situation. The pervasive nature of these technologies can contribute holistically across the whole spectrum of chronic care ranging from public information access and awareness, through monitoring and treatment of chronic disease, to support for patient carers. A related study to determine the perceptions of healthcare providers to m-health confirmed the view that attitudes were likely to be more important barriers to progress than technology. A key finding concerned the importance of seamless and integrated m-health processes across the spectrum of chronic disease management.

In light of the mass media coverage that the MMR (measles, mumps and rubella) vaccine received as a result of questions raised about its safety, a content analysis of mass media articles about the MMR vaccine was undertaken. The analysis examined 227 articles published in five different information sources in a 2 month period. The analysis looked at 94 content-based variables and the key attributes of these articles including word count and date of publication. Descriptive and analytical statistics relating to both article content and format were produced. The analysis showed that the content and format of articles between different information sources varied widely. These differences can be attributed to the information source in which they are published, but the variability in the content of these information sources provides a challenge to parents who were shown to be using the mass media as an information source.