914 resultados para Health information consumer


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Availability of health information is rapidly increasing and the expansion and proliferation of health information is inevitable. The Electronic Healthcare Record, Electronic Medical Record and Personal Health Record are at the core of this trend and are required for appropriate and practicable exchange and sharing of health information. However, it is becoming increasingly recognized that it is essential to preserve patient privacy and information security when utilising sensitive information for clinical, management and administrative processes. Furthermore, the usability of emerging healthcare applications is also becoming a growing concern. This paper proposes a novel approach for integrating consideration of information accountability with a perspective from usability engineering that can be applied when developing healthcare information technology applications. A social networking user case in the healthcare information exchange will be presented in the context of our approach.

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Health literacy is a vital tool to build health knowledge and enable empowerment in health decision making at a community and individual level. There are different views of what constitutes health literacy with the most inclusive addressing broadly the skills and competencies required “to seek out, comprehend, evaluate, and use health information and concepts to make informed choices, reduce health risks, and increase quality of life” (Zarcadoolas 2005). Poor health literacy has been shown to impact health seeking behaviour, access and awareness to preventive health.

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This study is the first to employ an epidemiological framework to evaluate the ‘fit-for-purpose’ of ICD-10-AM external cause of injury codes, ambulance and hospital clinical documentation for injury surveillance. Importantly, this thesis develops an evidence-based platform to guide future improvements in routine data collections used to inform the design of effective injury prevention strategies. Quantification of the impact of ambulance clinical records on the overall information quality of Queensland hospital morbidity data collections for injury causal information is a unique and notable contribution of this study.

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Information accountability is seen as a mode of usage control on the Web. Due to its many dimensions, information accountability has been expressed in various ways by computer scientists to address security and privacy in recent times. Information accountability is focused on how users participate in a system and the underlying policies that govern the participation. Healthcare is a domain in which the principles of information accountability can be utilised well. Modern health information systems are Internet based and the discipline is called eHealth. In this paper, we identify and discuss the goals of accountability systems and present the principles of information accountability. We characterise those principles in eHealth and discuss them contextually. We identify the current impediments to eHealth in terms of information privacy issues of eHealth consumers together with information usage requirements of healthcare providers and show how information accountability can be used in a healthcare context to address these needs. The challenges of implementing information accountability in eHealth are also discussed in terms of our efforts thus far.

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Effective management of chronic diseases is a global health priority. A healthcare information system offers opportunities to address challenges of chronic disease management. However, the requirements of health information systems are often not well understood. The accuracy of requirements has a direct impact on the successful design and implementation of a health information system. Our research describes methods used to understand the requirements of health information systems for advanced prostate cancer management. The research conducted a survey to identify heterogeneous sources of clinical records. Our research showed that the General Practitioner was the common source of patient's clinical records (41%) followed by the Urologist (14%) and other clinicians (14%). Our research describes a method to identify diverse data sources and proposes a novel patient journey browser prototype that integrates disparate data sources.

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TO THE EDITOR: In Australia, personal and health information that identifies an individual cannot be used or disclosed for research without specific requirements being met.1 Even if these requirements are met, data custodians may still refuse access if their views are discordant with those of the relevant human research ethics committee (HREC). It is now evident that there are adverse consequences of this well-meaning legislation...

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Background The implementation of the Australian Consumer Law in 2011 highlighted the need for better use of injury data to improve the effectiveness and responsiveness of product safety (PS) initiatives. In the PS system, resources are allocated to different priority issues using risk assessment tools. The rapid exchange of information (RAPEX) tool to prioritise hazards, developed by the European Commission, is currently being adopted in Australia. Injury data is required as a basic input to the RAPEX tool in the risk assessment process. One of the challenges in utilising injury data in the PS system is the complexity of translating detailed clinical coded data into broad categories such as those used in the RAPEX tool. Aims This study aims to translate hospital burns data into a simplified format by mapping the International Statistical Classification of Disease and Related Health Problems (Tenth Revision) Australian Modification (ICD-10-AM) burn codes into RAPEX severity rankings, using these rankings to identify priority areas in childhood product-related burns data. Methods ICD-10-AM burn codes were mapped into four levels of severity using the RAPEX guide table by assigning rankings from 1-4, in order of increasing severity. RAPEX rankings were determined by the thickness and surface area of the burn (BSA) with information extracted from the fourth character of T20-T30 codes for burn thickness, and the fourth and fifth characters of T31 codes for the BSA. Following the mapping process, secondary data analysis of 2008-2010 Queensland Hospital Admitted Patient Data Collection (QHAPDC) paediatric data was conducted to identify priority areas in product-related burns. Results The application of RAPEX rankings in QHAPDC burn data showed approximately 70% of paediatric burns in Queensland hospitals were categorised under RAPEX levels 1 and 2, 25% under RAPEX 3 and 4, with the remaining 5% unclassifiable. In the PS system, prioritisations are made to issues categorised under RAPEX levels 3 and 4. Analysis of external cause codes within these levels showed that flammable materials (for children aged 10-15yo) and hot substances (for children aged <2yo) were the most frequently identified products. Discussion and conclusions The mapping of ICD-10-AM burn codes into RAPEX rankings showed a favourable degree of compatibility between both classification systems, suggesting that ICD-10-AM coded burn data can be simplified to more effectively support PS initiatives. Additionally, the secondary data analysis showed that only 25% of all admitted burn cases in Queensland were severe enough to trigger a PS response.

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Background The implementation of the Australian Consumer Law in 2011 highlighted the need for better use of injury data to improve the effectiveness and responsiveness of product safety (PS) initiatives. In the PS system, resources are allocated to different priority issues using risk assessment tools. The rapid exchange of information (RAPEX) tool to prioritise hazards, developed by the European Commission, is currently being adopted in Australia. Injury data is required as a basic input to the RAPEX tool in the risk assessment process. One of the challenges in utilising injury data in the PS system is the complexity of translating detailed clinical coded data into broad categories such as those used in the RAPEX tool. Aims This study aims to translate hospital burns data into a simplified format by mapping the International Statistical Classification of Disease and Related Health Problems (Tenth Revision) Australian Modification (ICD-10-AM) burn codes into RAPEX severity rankings, using these rankings to identify priority areas in childhood product-related burns data. Methods ICD-10-AM burn codes were mapped into four levels of severity using the RAPEX guide table by assigning rankings from 1-4, in order of increasing severity. RAPEX rankings were determined by the thickness and surface area of the burn (BSA) with information extracted from the fourth character of T20-T30 codes for burn thickness, and the fourth and fifth characters of T31 codes for the BSA. Following the mapping process, secondary data analysis of 2008-2010 Queensland Hospital Admitted Patient Data Collection (QHAPDC) paediatric data was conducted to identify priority areas in product-related burns. Results The application of RAPEX rankings in QHAPDC burn data showed approximately 70% of paediatric burns in Queensland hospitals were categorised under RAPEX levels 1 and 2, 25% under RAPEX 3 and 4, with the remaining 5% unclassifiable. In the PS system, prioritisations are made to issues categorised under RAPEX levels 3 and 4. Analysis of external cause codes within these levels showed that flammable materials (for children aged 10-15yo) and hot substances (for children aged <2yo) were the most frequently identified products. Discussion and conclusions The mapping of ICD-10-AM burn codes into RAPEX rankings showed a favourable degree of compatibility between both classification systems, suggesting that ICD-10-AM coded burn data can be simplified to more effectively support PS initiatives. Additionally, the secondary data analysis showed that only 25% of all admitted burn cases in Queensland were severe enough to trigger a PS response.

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Abstract OBJECTIVE: Those with mental illness are at increased risk of physical health problems. The current study aimed to examine the information available online to the Australian public about the increased risk and consequences of physical illness in those with mental health problems and the services available to address these co-morbidities. METHODS: A structured online search was conducted with the search engine Google Australia (www.google.com.au) using generic search terms 'mental health information Australia', 'mental illness information Australia', 'depression', 'anxiety', and 'psychosis'. The direct content of websites was examined for information on the physical co-morbidities of mental illness. All external links on high-profile websites [the first five websites retrieved under each search term (n = 25)] were examined for information pertaining to physical health. RESULTS: Only 4.2% of websites informing the public about mental health contained direct content information about the increased risk of physical co-morbidities. The Australian Government's Department of Health and Ageing site did not contain any information. Of the high-profile websites, 62% had external links to resources about physical health and 55% had recommendations or resources for physical health. Most recommendations were generic. CONCLUSIONS: Relative to the seriousness of this problem, there is a paucity of information available to the public about the increased physical health risks associated with mental illness. Improved public awareness is the starting point of addressing this health inequity.

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Objectives The intent of this paper is in the examination of health IT implementation processes – the barriers to and facilitators of successful implementation, identification of a beginning set of implementation best practices, the identification of gaps in the health IT implementation body of knowledge, and recommendations for future study and application. Methods A literature review resulted in the identification of six health IT related implementation best practices which were subsequently debated and clarified by participants attending the NI2012 Research Post Conference held in Montreal in the summer of 2012. Using the framework for implementation research (CFIR) to guide their application, the six best practices were applied to two distinct health IT implementation studies to assess their applicability. Results Assessing the implementation processes from two markedly diverse settings illustrated both the challenges and potentials of using standardized implementation processes. In support of what was discovered in the review of the literature, “one size fits all” in health IT implementation is a fallacy, particularly when global diversity is added into the mix. At the same time, several frameworks show promise for use as “scaffolding” to begin to assess best practices, their distinct dimensions, and their applicability for use. Conclusions Health IT innovations, regardless of the implementation setting, requires a close assessment of many dimensions. While there is no “one size fits all”, there are commonalities and best practices that can be blended, adapted, and utilized to improve the process of implementation. This paper examines health IT implementation processes and identifies a beginning set of implementation best practices, which could begin to address gaps in the health IT implementation body of knowledge.

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We evaluated the effectiveness of a woman-held pregnancy record ('The Pregnancy Pocketbook') on improving health behaviors important for maternal and infant health. The Pregnancy Pocketbook was developed as a woman-focused preventive approach to pregnancy health based on antenatal management guidelines, behavior-change evidence, and formative research with the target population and health service providers. The Pregnancy Pocketbook was evaluated using a quasi-experimental, two-group design; one clinic cohort received the Pregnancy Pocketbook (n = 163); the other received Usual Care (n = 141). Smoking, fruit and vegetable intake, and physical activity were assessed at baseline (service-entry) and 12-weeks. Approximately two-thirds of women in the Pregnancy Pocketbook clinic recalled receiving the resource. A small, but significantly greater proportion of women at the Pregnancy Pocketbook site (7.6%) than the UC site (2.1%) quit smoking. No significant effect was observed of the Pregnancy Pocketbook on fruit and vegetable intake or physical activity. Few women completed sections that required health professional assistance. The Pregnancy Pocketbook produced small, but significant effects on smoking cessation, despite findings that indicate minimal interaction about the resource between health staff and the women in their care. A refocus of antenatal care toward primary prevention is required to provide essential health information and behavior change tools more consistently for improved maternal and infant health outcomes.

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Introduction: The built environment is increasingly recognised as being associated with health outcomes. Relationships between the built environment and health differ among age groups, especially between children and adults, but also between younger, mid-age and older adults. Yet few address differences across life stage groups within a single population study. Moreover, existing research mostly focuses on physical activity behaviours, with few studying objective clinical and mental health outcomes. The Life Course Built Environment and Health (LCBEH) project explores the impact of the built environment on self-reported and objectively measured health outcomes in a random sample of people across the life course. Methods and analysis: This cross-sectional data linkage study involves 15 954 children (0–15 years), young adults (16–24 years), adults (25–64 years) and older adults (65+years) from the Perth metropolitan region who completed the Health and Wellbeing Surveillance System survey administered by the Department of Health of Western Australia from 2003 to 2009. Survey data were linked to Western Australia's (WA) Hospital Morbidity Database System (hospital admission) and Mental Health Information System (mental health system outpatient) data. Participants’ residential address was geocoded and features of their ‘neighbourhood’ were measured using Geographic Information Systems software. Associations between the built environment and self-reported and clinical health outcomes will be explored across varying geographic scales and life stages. Ethics and dissemination: The University of Western Australia's Human Research Ethics Committee and the Department of Health of Western Australia approved the study protocol (#2010/1). Findings will be published in peer-reviewed journals and presented at local, national and international conferences, thus contributing to the evidence base informing the design of healthy neighbourhoods for all residents.

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Modern health information systems can generate several exabytes of patient data, the so called "Health Big Data", per year. Many health managers and experts believe that with the data, it is possible to easily discover useful knowledge to improve health policies, increase patient safety and eliminate redundancies and unnecessary costs. The objective of this paper is to discuss the characteristics of Health Big Data as well as the challenges and solutions for health Big Data Analytics (BDA) – the process of extracting knowledge from sets of Health Big Data – and to design and evaluate a pipelined framework for use as a guideline/reference in health BDA.

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We present an approach to automatically de-identify health records. In our approach, personal health information is identified using a Conditional Random Fields machine learning classifier, a large set of linguistic and lexical features, and pattern matching techniques. Identified personal information is then removed from the reports. The de-identification of personal health information is fundamental for the sharing and secondary use of electronic health records, for example for data mining and disease monitoring. The effectiveness of our approach is first evaluated on the 2007 i2b2 Shared Task dataset, a widely adopted dataset for evaluating de-identification techniques. Subsequently, we investigate the robustness of the approach to limited training data; we study its effectiveness on different type and quality of data by evaluating the approach on scanned pathology reports from an Australian institution. This data contains optical character recognition errors, as well as linguistic conventions that differ from those contained in the i2b2 dataset, for example different date formats. The findings suggest that our approach compares to the best approach from the 2007 i2b2 Shared Task; in addition, the approach is found to be robust to variations of training size, data type and quality in presence of sufficient training data.

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Searching for health advice on the web is becoming increasingly common. Because of the great importance of this activity for patients and clinicians and the effect that incorrect information may have on health outcomes, it is critical to present relevant and valuable information to a searcher. Previous evaluation campaigns on health information retrieval (IR) have provided benchmarks that have been widely used to improve health IR and record these improvements. However, in general these benchmarks have targeted the specialised information needs of physicians and other healthcare workers. In this paper, we describe the development of a new collection for evaluation of effectiveness in IR seeking to satisfy the health information needs of patients. Our methodology features a novel way to create statements of patients’ information needs using realistic short queries associated with patient discharge summaries, which provide details of patient disorders. We adopt a scenario where the patient then creates a query to seek information relating to these disorders. Thus, discharge summaries provide us with a means to create contextually driven search statements, since they may include details on the stage of the disease, family history etc. The collection will be used for the first time as part of the ShARe/-CLEF 2013 eHealth Evaluation Lab, which focuses on natural language processing and IR for clinical care.