This study explores the constructions of primary health care held by remote area nurses working in indigenous communities without resident medical practitioners, in the Northern Territory. Primary health care is increasingly permeating health policy in Australia, and nurses in remote areas are responsible for its implementation. The study investigates past and present discussions of the meaning of the concept of primary health care to begin to identify the major forces which have problematically impacted on its evolution and interpretation. It traces the threads which emerge from these forces through the more recent developments of health promotion and new pubflc health to explore the discourses and strategies they have produced, and which overtly and covertly influence the implementation of primary health care. Remote area nurses are individually interviewed and their discussions analysed to explore the constructions of primary health care which they hold. The analysis also explores some of the ways in which these constructions may have come to exist, the evident impact of current discourses, and the absence of effective support in the further development of these constructions. The remote area nurses' discussions display a view of primary health care as the most basic of health services, focussed on personal hygiene and the individual's responsibility in prevention of illness, operated through encounters which offer opportunities for education and basic curative care. While several of the nurses indicate discomfort with the paternalistic nature of such a service, none are aware of ways in which they might resolve their concerns about it. The study briefly explores positive approaches towards the democratization of health care, and examines the support needed by remote area nurses if primary health care is to be effectively implemented by them.

Doctor of Philosophy / All surveillance systems are based on an effective general surveillance system because this is the system that detects emerging diseases and the re-introduction of disease to a previously disease free area. General surveillance requires comprehensive coverage of the population through an extensive network of relationships between animal producers and observers and surveillance system officers. This system is under increasing threat in Australia (and many other countries) due to the increased biomass, animal movements, rate of disease emergence, and the decline in resource allocation for surveillance activities. The Australian surveillance system is state-based and has a complex management structure that includes State and Commonwealth government representatives, industry stakeholders (such as producer bodies) and private organisations. A developing problem is the decline in the effectiveness of the general surveillance system in the extensive (remote) cattle producing regions of northern Australia. The complex organisational structure of surveillance in Australia contributes to this, and is complicated by the incomplete capture of data (as demonstrated by slow uptake of electronic individual animal identification systems), poorly developed and integrated national animal health information systems, and declining funding streams for field and laboratory personnel and infrastructure. Of major concern is the reduction in contact between animal observers and surveillance personnel arising from the decline in resource allocation for surveillance. Fewer veterinarians are working in remote areas, fewer producers use veterinarians, and, as a result, fewer sick animals are being investigated by the general surveillance system. A syndrome is a collection of signs that occur in a sick individual. Syndromic surveillance is an emerging approach to monitoring populations for change in disease levels and is based on statistical monitoring of the distribution of signs, syndromes and associations between health variables in a population. Often, diseases will have syndromes that are characteristic and the monitoring of these syndromes may provide for early detection of outbreaks. Because the process uses general signs, this method may support the existing (struggling) general surveillance system for the extensive cattle producing regions of northern Australia. Syndromic surveillance systems offer many potential advantages. First, the signs that are monitored can be general and include any health-related variable. This generality provides potential as a detector of emerging diseases. Second, many of the data types used occur early in a disease process and therefore efficient syndromic surveillance systems can detect disease events in a timely manner. There are many hurdles to the successful deployment of a syndromic surveillance system and most relate to data. An effective system will ideally obtain data from multiple sources, all data will conform to a standard (therefore each data source can be validly combined), data coverage will be extensive (across the population) and data capture will be in real time (allowing early detection). This picture is one of a functional electronic data world and unfortunately this is not the norm for either human or animal heath. Less than optimal data, lack of data standards, incomplete coverage of the population and delayed data transmission result in a loss of sensitivity, specificity and timeliness of detection. In human syndromic surveillance, most focus has been placed on earlier detection of mass bioterrorism events and this has concentrated research on the problems of electronic data. Given the current state of animal health data, the development of efficient detection algorithms represents the least of the hurdles. However, the world is moving towards increased automation and therefore the problems with current data can be expected to be resolved in the next decade. Despite the lack of large scale deployment of these systems, the question is becoming when, not whether these system will contribute. The observations of a stock worker are always the start of the surveillance pathway in animal health. Traditionally this required the worker to contact a veterinarian who would investigate unusual cases with the pathway ending in laboratory samples and specific diagnostic tests. The process is inefficient as only a fraction of cases observed by stock workers end in diagnostic samples. These observations themselves are most likely to be amenable to capture and monitoring using syndromic surveillance techniques. A pilot study of stock workers in the extensive cattle producing Lower Gulf region of Queensland demonstrated that experienced non-veterinary observers of cattle can describe the signs that they see in sick cattle in an effective manner. Lay observers do not posses a veterinary vocabulary, but the provision of a system to facilitate effective description of signs resulted in effective and standardised description of disease. However, most producers did not see personal benefit from providing this information and worried that they might be exposing themselves to regulatory impost if they described suspicious signs. Therefore the pilot study encouraged the development of a syndromic surveillance system that provides a vocabulary (a template) for lay observers to describe disease and a reason for them to contribute their data. The most important disease related drivers for producers relate to what impact the disease may have in their herd. For this reason, the Bovine Syndromic Surveillance System (BOSSS) was developed incorporating the Bayesian cattle disease diagnostic program BOVID. This allowed the observer to receive immediate information from interpretation of their observation providing a differential list of diseases, a list of questions that may help further differentiate cause, access to information and other expertise, and opportunity to benchmark disease performance. BOSSS was developed as a web-based reporting system and used a novel graphical user interface that interlinked with an interrogation module to enable lay observers to accurately and fully describe disease. BOSSS used a hierarchical reporting system that linked individual users with other users along natural reporting pathways and this encouraged the seamless and rapid transmission of information between users while respecting confidentiality. The system was made available for testing at the state level in early 2006, and recruitment of producers is proceeding. There is a dearth of performance data from operational syndromic surveillance systems. This is due, in part, to the short period that these systems have been operational and the lack of major human health outbreaks in areas with operational systems. The likely performance of a syndromic surveillance system is difficult to theorise. Outbreaks vary in size and distribution, and quality of outbreak data capture is not constant. The combined effect of a lack of track record and the many permutations of outbreak and data characteristics make computer simulation the most suitable method to evaluate likely performance. A stochastic simulation model of disease spread and disease reporting by lay observers throughout a grid of farms was modelled. The reporting characteristics of lay observers were extrapolated from the pilot study and theoretical disease was modelled (as a representation of newly emergent disease). All diseases were described by their baseline prevalence and by conditional sign probabilities (obtained from BOVID and from a survey of veterinarians in Queensland). The theoretical disease conditional sign probabilities were defined by the user. Their spread through the grid of farms followed Susceptible-Infected-Removed (SIR) principles (in herd) and by mass action between herds. Reporting of disease events and signs in events was modelled as a probabilistic event using sampling from distributions. A non-descript disease characterised by gastrointestinal signs and a visually spectacular disease characterised by neurological signs were modelled, each over three outbreak scenarios (least, moderately and most contagious). Reports were examined using two algorithms. These were the cumulative sum (CuSum) technique of adding excess of cases (above a maximum limit) for individual signs and the generic detector What’s Strange About Recent Events (WSARE) that identifies change to variable counts or variable combination counts between time periods. Both algorithms detected disease for all disease and outbreak characteristics combinations. WSARE was the most efficient algorithm, detecting disease on average earlier than CuSum. Both algorithms had high sensitivity and excellent specificity. The timeliness of detection was satisfactory for the insidious gastrointestinal disease (approximately 24 months after introduction), but not sufficient for the visually spectacular neurological disease (approximately 20 months) as the traditional surveillance system can be expected to detect visually spectacular diseases in reasonable time. Detection efficiency was not influenced greatly by the proportion of producers that report or by the proportion of cases or the number of signs per case that are reported. The modelling process demonstrated that a syndromic surveillance system in this remote region is likely to be a useful addition to the existing system. Improvements that are planned include development of a hand-held computer version and enhanced disease and syndrome mapping capability. The increased use of electronic recording systems, including livestock identification, will facilitate the deployment of BOSSS. Long term sustainability will require that producers receive sufficient reward from BOSSS to continue to provide reports over time. This question can only be answered by field deployment and this work is currently proceeding.

Doctor of Philosophy / All surveillance systems are based on an effective general surveillance system because this is the system that detects emerging diseases and the re-introduction of disease to a previously disease free area. General surveillance requires comprehensive coverage of the population through an extensive network of relationships between animal producers and observers and surveillance system officers. This system is under increasing threat in Australia (and many other countries) due to the increased biomass, animal movements, rate of disease emergence, and the decline in resource allocation for surveillance activities. The Australian surveillance system is state-based and has a complex management structure that includes State and Commonwealth government representatives, industry stakeholders (such as producer bodies) and private organisations. A developing problem is the decline in the effectiveness of the general surveillance system in the extensive (remote) cattle producing regions of northern Australia. The complex organisational structure of surveillance in Australia contributes to this, and is complicated by the incomplete capture of data (as demonstrated by slow uptake of electronic individual animal identification systems), poorly developed and integrated national animal health information systems, and declining funding streams for field and laboratory personnel and infrastructure. Of major concern is the reduction in contact between animal observers and surveillance personnel arising from the decline in resource allocation for surveillance. Fewer veterinarians are working in remote areas, fewer producers use veterinarians, and, as a result, fewer sick animals are being investigated by the general surveillance system. A syndrome is a collection of signs that occur in a sick individual. Syndromic surveillance is an emerging approach to monitoring populations for change in disease levels and is based on statistical monitoring of the distribution of signs, syndromes and associations between health variables in a population. Often, diseases will have syndromes that are characteristic and the monitoring of these syndromes may provide for early detection of outbreaks. Because the process uses general signs, this method may support the existing (struggling) general surveillance system for the extensive cattle producing regions of northern Australia. Syndromic surveillance systems offer many potential advantages. First, the signs that are monitored can be general and include any health-related variable. This generality provides potential as a detector of emerging diseases. Second, many of the data types used occur early in a disease process and therefore efficient syndromic surveillance systems can detect disease events in a timely manner. There are many hurdles to the successful deployment of a syndromic surveillance system and most relate to data. An effective system will ideally obtain data from multiple sources, all data will conform to a standard (therefore each data source can be validly combined), data coverage will be extensive (across the population) and data capture will be in real time (allowing early detection). This picture is one of a functional electronic data world and unfortunately this is not the norm for either human or animal heath. Less than optimal data, lack of data standards, incomplete coverage of the population and delayed data transmission result in a loss of sensitivity, specificity and timeliness of detection. In human syndromic surveillance, most focus has been placed on earlier detection of mass bioterrorism events and this has concentrated research on the problems of electronic data. Given the current state of animal health data, the development of efficient detection algorithms represents the least of the hurdles. However, the world is moving towards increased automation and therefore the problems with current data can be expected to be resolved in the next decade. Despite the lack of large scale deployment of these systems, the question is becoming when, not whether these system will contribute. The observations of a stock worker are always the start of the surveillance pathway in animal health. Traditionally this required the worker to contact a veterinarian who would investigate unusual cases with the pathway ending in laboratory samples and specific diagnostic tests. The process is inefficient as only a fraction of cases observed by stock workers end in diagnostic samples. These observations themselves are most likely to be amenable to capture and monitoring using syndromic surveillance techniques. A pilot study of stock workers in the extensive cattle producing Lower Gulf region of Queensland demonstrated that experienced non-veterinary observers of cattle can describe the signs that they see in sick cattle in an effective manner. Lay observers do not posses a veterinary vocabulary, but the provision of a system to facilitate effective description of signs resulted in effective and standardised description of disease. However, most producers did not see personal benefit from providing this information and worried that they might be exposing themselves to regulatory impost if they described suspicious signs. Therefore the pilot study encouraged the development of a syndromic surveillance system that provides a vocabulary (a template) for lay observers to describe disease and a reason for them to contribute their data. The most important disease related drivers for producers relate to what impact the disease may have in their herd. For this reason, the Bovine Syndromic Surveillance System (BOSSS) was developed incorporating the Bayesian cattle disease diagnostic program BOVID. This allowed the observer to receive immediate information from interpretation of their observation providing a differential list of diseases, a list of questions that may help further differentiate cause, access to information and other expertise, and opportunity to benchmark disease performance. BOSSS was developed as a web-based reporting system and used a novel graphical user interface that interlinked with an interrogation module to enable lay observers to accurately and fully describe disease. BOSSS used a hierarchical reporting system that linked individual users with other users along natural reporting pathways and this encouraged the seamless and rapid transmission of information between users while respecting confidentiality. The system was made available for testing at the state level in early 2006, and recruitment of producers is proceeding. There is a dearth of performance data from operational syndromic surveillance systems. This is due, in part, to the short period that these systems have been operational and the lack of major human health outbreaks in areas with operational systems. The likely performance of a syndromic surveillance system is difficult to theorise. Outbreaks vary in size and distribution, and quality of outbreak data capture is not constant. The combined effect of a lack of track record and the many permutations of outbreak and data characteristics make computer simulation the most suitable method to evaluate likely performance. A stochastic simulation model of disease spread and disease reporting by lay observers throughout a grid of farms was modelled. The reporting characteristics of lay observers were extrapolated from the pilot study and theoretical disease was modelled (as a representation of newly emergent disease). All diseases were described by their baseline prevalence and by conditional sign probabilities (obtained from BOVID and from a survey of veterinarians in Queensland). The theoretical disease conditional sign probabilities were defined by the user. Their spread through the grid of farms followed Susceptible-Infected-Removed (SIR) principles (in herd) and by mass action between herds. Reporting of disease events and signs in events was modelled as a probabilistic event using sampling from distributions. A non-descript disease characterised by gastrointestinal signs and a visually spectacular disease characterised by neurological signs were modelled, each over three outbreak scenarios (least, moderately and most contagious). Reports were examined using two algorithms. These were the cumulative sum (CuSum) technique of adding excess of cases (above a maximum limit) for individual signs and the generic detector What’s Strange About Recent Events (WSARE) that identifies change to variable counts or variable combination counts between time periods. Both algorithms detected disease for all disease and outbreak characteristics combinations. WSARE was the most efficient algorithm, detecting disease on average earlier than CuSum. Both algorithms had high sensitivity and excellent specificity. The timeliness of detection was satisfactory for the insidious gastrointestinal disease (approximately 24 months after introduction), but not sufficient for the visually spectacular neurological disease (approximately 20 months) as the traditional surveillance system can be expected to detect visually spectacular diseases in reasonable time. Detection efficiency was not influenced greatly by the proportion of producers that report or by the proportion of cases or the number of signs per case that are reported. The modelling process demonstrated that a syndromic surveillance system in this remote region is likely to be a useful addition to the existing system. Improvements that are planned include development of a hand-held computer version and enhanced disease and syndrome mapping capability. The increased use of electronic recording systems, including livestock identification, will facilitate the deployment of BOSSS. Long term sustainability will require that producers receive sufficient reward from BOSSS to continue to provide reports over time. This question can only be answered by field deployment and this work is currently proceeding.

No description available.

Abstract Many studies about medial outcomes in rural areas or medial resource deficient areas have been published, but few discuss outcomes in areas deficient in oral medical resources. The program, improving underserved dental health care resources, has been implemented for near ten years, but no study explores the business models in different areas that are underserved dental health care resources. The purpose of this study is to compare different models of operating the program ¡§improving underserved dental health care resources¡¨. As to the business model, the program ¡§improving underserved dental health care resources¡¨ is executed in two main models. One is execution in fixed sites. The advantage of this model is high stability. Dentals can plan and set the equipments that they need to use. The other is medical tour. The advantage of this model is high flexibility, which let dentals can provide services as far as possible for patients in medial resource deficient areas. Finally, based on the research findings, this study proposes some suggestions, including that to use the medical-tour model as the major business to implement the program, to carefully assess the site for exestuation need, to consider the financial support on equipments (especially the dental mobile medical vehicle ), to strengthen local infrastructure investment is prior to plunge into health care resources, and so on. Keywords: Remote area, Health care delivery, No-dentist Rural Areas

No description available.

This presentation summarizes the preparation for, and execution of, audiology series provided by East Tennessee State University's Audiology, Program at Remote Area Medical (RAM) expeditiors in the Southern Appalachian region. In 2010 and 2012, ETSU audiology faculty and students evaluatd 281 patients and subsequently fit 178 hearing aids.

Remote area power supply (RAPS) is a potential early market for renewable energy - hydrogen systems because of the relatively high costs of conventional energy sources in remote regions. Solar-hydrogen RAPS systems commonly employ photovoltaic panels, a Proton Exchange Membrane (PEM) electrolyser, a storage for hydrogen gas, and a PEM fuel cell. Unitised Regenerative Fuel Cells (URFCs) use the same hardware for both electrolyser and fuel cell functions. Since both of these functions are not required simultaneously in a solar hydrogen RAPS system, URFCs based on PEM technology provide a promising opportunity for reducing the cost of the hydrogen subsystem used in renewable-energy hydrogen systems for RAPS. URFCs also have potential applications in the areas of aerospace, submarines, energy storage for central grids, and hydrogen cars. In this thesis, a general theoretical relationship between cell potential and current density of a single-cell PEM URFC operating in both fuel-cell (FC) and electrolyser (E) modes is developed using modified Butler-Volmer equations for both oxygen- and hydrogen-electrodes, and accounting for mass transport losses and saturation behaviour in both modes, membrane resistance to proton current, and membrane and electrode resistances to electron current. This theoretical relationship is used to construct a computer model based on Excel and Visual Basic to generate voltage-current (V-I) polarisation curves in both E and FC modes for URFCs with a range of membrane electrode assembly characteristics. The model is used to investigate the influence on polarisation curves of varying key parameters such charge transfer coefficients, exchange current densities, saturation currents, and membrane conductivity. A method for using the model to obtain best-fit values for electrode characteristics corresponding to an experime ntally-measured polarisation curve of a URFC is presented. The experimental component of the thesis has involved the design and construction of single PEM URFCs with an active area of 5 cm2 with a number of different catalyst types and loadings. V-I curves for all these cells have been measured and the performance of the cells compared. The computer model has then been used to obtain best-fit values for the electrode characteristics for the URFCs with single catalyst materials active in each mode on each electrode for the corresponding experimentally-measured V-I curves. Generally values have been found for exchange current densities, charge transfer coefficients, and saturation current densities that give a close fit between the empirical and theoretically-generated curves. The values found conform well to expectations based on the catalyst loadings, in partial confirmation of the validity of the modelling approach. The model thus promises to be a useful tool in identifying electrodes with materials and structures, together with optimal catalyst types and loadings that will improve URFC performance. Finally the role URFCs can play in developing cost-competitive solar- hydrogen RAPS systems is discussed, and some future directions for future URFC research and development are identified.

Since the year of 2000, some of the country and city governments had already established regulations or sent out official documents to encourage the schools under them to implement ¡§Primary School After-School-Care Service¡¨. 2003, it is officially classified into Children and Youth Welfare Act as a part of the law, and established ¡§After-School-Care services for Primary schools and staff qualification standards¡¨ to propose to the whole country. Its goal is to encourage women to give birth and to enable the parents to work without burdens, especially for those families who are receiving double-income, so that their children can grow up healthy. Also, schools which are located in the mountains, remote areas, or islanders, aborigines have the privilege to establish first, and the care service have to match the work hours of the parents. This research is taking Zuo-Zheng, Tainan as sample, and is researching on the conditions of remote primary schools¡¦ After-School-Care Service. We interviewed the principals of the primary schools, the head of administrative organizations and unofficial groups, and also did survey on the parents. We used descriptive statistics to analyze, and make discusses on if it is correspondent with the needs and goals, if gaps are found during the execution of the policy, and related advices are made for references. The conclusion of the founding are listed below: 1. After-School-Cares at remote areas cannot meet the needs. 2. After-School-Cares at remote areas are facing difficulties. 3. After-School-Cares at remote areas did not practice well. 4. The idea of After-School-Care is lack of cognition. 5. The policy of After-School-Care is complex and lack of continuity. At last according to the founding, we came up with advices for government organization of education: 1. Establish supplementary measures according to different regions. 2. Enhance the propaganda of the policy to enable the establishment of common views.

Librarians can be major contributors at multihealth profession community outreach efforts. East Tennessee State University Quillen College of Medicine Library (ETSU QCOML) partnered with the Remote Area Medical Group (RAM) at two health "expeditions" in northeastern Tennessee to provide consumer health information to the people who came to the event for medical, dental, and vision care. A booth staffed by library workers that utilized MedlinePlus.gov was set up at each event. Preselected handouts were used along with online searching. The library booth was able to provide consumer health information to 1,310 people. By participating in this event, it allowed not only the library workers to assist the public with consumer health questions but also exposed other health care professionals to what medical librarians can do to directly help patients.