27 research outputs found

    Health System Resource Gaps and Associated Mortality from Pandemic Influenza across Six Asian Territories

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    BACKGROUND: Southeast Asia has been the focus of considerable investment in pandemic influenza preparedness. Given the wide variation in socio-economic conditions, health system capacity across the region is likely to impact to varying degrees on pandemic mitigation operations. We aimed to estimate and compare the resource gaps, and potential mortalities associated with those gaps, for responding to pandemic influenza within and between six territories in Asia. METHODS AND FINDINGS: We collected health system resource data from Cambodia, Indonesia (Jakarta and Bali), Lao PDR, Taiwan, Thailand and Vietnam. We applied a mathematical transmission model to simulate a "mild-to-moderate" pandemic influenza scenario to estimate resource needs, gaps, and attributable mortalities at province level within each territory. The results show that wide variations exist in resource capacities between and within the six territories, with substantial mortalities predicted as a result of resource gaps (referred to here as "avoidable" mortalities), particularly in poorer areas. Severe nationwide shortages of mechanical ventilators were estimated to be a major cause of avoidable mortalities in all territories except Taiwan. Other resources (oseltamivir, hospital beds and human resources) are inequitably distributed within countries. Estimates of resource gaps and avoidable mortalities were highly sensitive to model parameters defining the transmissibility and clinical severity of the pandemic scenario. However, geographic patterns observed within and across territories remained similar for the range of parameter values explored. CONCLUSIONS: The findings have important implications for where (both geographically and in terms of which resource types) investment is most needed, and the potential impact of resource mobilization for mitigating the disease burden of an influenza pandemic. Effective mobilization of resources across administrative boundaries could go some way towards minimizing avoidable deaths

    Development of a resource modelling tool to support decision makers in pandemic influenza preparedness: The AsiaFluCap Simulator.

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    BACKGROUND: Health care planning for pandemic influenza is a challenging task which requires predictive models by which the impact of different response strategies can be evaluated. However, current preparedness plans and simulations exercises, as well as freely available simulation models previously made for policy makers, do not explicitly address the availability of health care resources or determine the impact of shortages on public health. Nevertheless, the feasibility of health systems to implement response measures or interventions described in plans and trained in exercises depends on the available resource capacity. As part of the AsiaFluCap project, we developed a comprehensive and flexible resource modelling tool to support public health officials in understanding and preparing for surges in resource demand during future pandemics. RESULTS: The AsiaFluCap Simulator is a combination of a resource model containing 28 health care resources and an epidemiological model. The tool was built in MS Excel© and contains a user-friendly interface which allows users to select mild or severe pandemic scenarios, change resource parameters and run simulations for one or multiple regions. Besides epidemiological estimations, the simulator provides indications on resource gaps or surpluses, and the impact of shortages on public health for each selected region. It allows for a comparative analysis of the effects of resource availability and consequences of different strategies of resource use, which can provide guidance on resource prioritising and/or mobilisation. Simulation results are displayed in various tables and graphs, and can also be easily exported to GIS software to create maps for geographical analysis of the distribution of resources. CONCLUSIONS: The AsiaFluCap Simulator is freely available software (http://www.cdprg.org) which can be used by policy makers, policy advisors, donors and other stakeholders involved in preparedness for providing evidence based and illustrative information on health care resource capacities during future pandemics. The tool can inform both preparedness plans and simulation exercises and can help increase the general understanding of dynamics in resource capacities during a pandemic. The combination of a mathematical model with multiple resources and the linkage to GIS for creating maps makes the tool unique compared to other available software

    Evolution and complexity of government policies to protect the health of undocumented/illegal migrants in Thailand – the unsolved challenges

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    Rapeepong Suphanchaimat,1,2 Weerasak Putthasri,1 Phusit Prakongsai,1,3 Viroj Tangcharoensathien1 1International Health Policy Program (IHPP), The Ministry of Public Health, Nonthaburi, 2Banphai Hospital, Khon Kaen, 3Bureau of International Health (BIH), The Ministry of Public Health, Nonthaburi, Thailand Background: Of the 65 million residents in Thailand, >1.5 million are undocumented/illegal migrants from neighboring countries. Despite several policies being launched to improve access to care for these migrants, policy implementation has always faced numerous challenges. This study aimed to investigate the policy makers’ views on the challenges of implementing policies to protect the health of undocumented/illegal migrants in light of the dynamics of all of the migrant policies in Thailand. Methods: This study used a qualitative approach. Data were collected by document review, from related laws/regulations concerning migration policy over the past 40 years, and from in-depth interviews with seven key policy-level officials. Thematic analysis was applied. Results: Three critical themes emerged, namely, national security, economic necessity, and health protection. The national security discourse played a dominant role from the early 1900s up to the 1980s as Thailand attempted to defend itself from the threats of colonialism and communism. The economic boom of the 1990s created a pronounced labor shortage, which required a large migrant labor force to drive the growing economy. The first significant attempt to protect the health of migrants materialized in the early 2000s, after Thailand achieved universal health coverage. During that period, public insurance for undocumented/illegal migrants was introduced. The insurance used premium-based financing. However, the majority of migrants remained uninsured. Recently, the government attempted to overhaul the entire migrant registry system by introducing a new measure, namely the One Stop Service. In principle, the One Stop Service aimed to integrate the functions of all responsible authorities, but several challenges still remained; these included ambiguous policy messages and the slow progress of the nationality verification process. Conclusion: The root causes of the challenges in migrant health policy are incoherent policy direction and objectives across government authorities and unclear policy messages. In addition, the health sector, especially the Ministry of Public Health, has been de facto powerless and, due to its outdated bureaucracy, has lacked the capacity to keep pace with the problems regarding human mobility. Keywords: migrant, health insurance, Thailand, policy formulation, policy proces

    The impact of rural-exposure strategies on the intention of dental students and dental graduates to practice in rural areas: a systematic review and meta-analysis

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    Rapeepong Suphanchaimat,1 Nisachol Cetthakrikul,1 Alexander Dalliston,2 Weerasak Putthasri1 1International Health Policy Program, Ministry of Public Health, Nonthaburi, Thailand; 2Master’s Student, School of Oriental and African Studies, University of London, London, UK Background and objectives: The objective of this study was to assess the impact of strategies on the intention of dental students/graduates to practice in rural areas. The strategies included the recruitment of dental students from rural backgrounds and clinical rotations in rural areas during the training of dental students. Materials and methods: The study undertook a systematic review and utilized meta-analysis to assess these strategies. International literature published between 2000 and 2015 was retrieved from three main search engines: Medline, Embase, and Scopus. The selected articles were scanned to extract the main content. The impact of the strategies was quantitatively assessed by meta-analysis, using the random-effect model. The pooled effect was reported in terms of odds ratios (ORs) with 95% confidence intervals. Sensitivity and subgroup analyses were performed. Publication bias was assessed by the Funnel plot and Egger’s test. Results: Seven of the initially selected 897 articles were included for the full review. The majority of the selected articles had been published in developed countries. The meta-analysis results revealed that the pooled OR of rural exposure on the intention to practice in rural areas was approximately 4.1, statistically significant. Subgroup analysis showed that clinical rotations in rural areas tended to have a slightly greater influence on rural dental practice than recruiting students from rural backgrounds (OR 4.3 versus 4.2). There was weaker evidence of publication bias, which was derived from small-study effects. Conclusion: Enrolling students with rural backgrounds and imposing compulsory clinical rotation in rural areas during their study appeared to be effective strategies in tackling the shortage and maldistribution of dentists in rural areas. Keywords: rural retention, rural background, dental students, dental graduates, systematic review, meta-analysi

    Health service resource needs for pandemic influenza in developing countries: a linked transmission dynamics, interventions and resource demand model.

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    We used a mathematical model to describe a regional outbreak and extrapolate the underlying health-service resource needs. This model was designed to (i) estimate resource gaps and quantities of resources needed, (ii) show the effect of resource gaps, and (iii) highlight which particular resources should be improved. We ran the model, parameterized with data from the 2009 H1N1v pandemic, for two provinces in Thailand. The predicted number of preventable deaths due to resource shortcomings and the actual resource needs are presented for two provinces and for Thailand as a whole. The model highlights the potentially huge impact of health-system resource availability and of resource gaps on health outcomes during a pandemic and provides a means to indicate where efforts should be concentrated to effectively improve pandemic response programmes

    Self-assessment of nursing competency among final year nursing students in Thailand: a comparison between public and private nursing institutions

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    Krisada Sawaengdee,1,2 Kanang Kantamaturapoj,3 Parinda Seneerattanaprayul,1 Weerasak Putthasri,1 Rapeepong Suphanchaimat,1,4 1International Health Policy Program (IHPP), 2Praboromrajchanok Institute for Health Workforce Development, Ministry of Public Health, Nonthaburi, 3Banphai Hospital, Khon Kaen, 4Department of Social Sciences, Faculty of Social Sciences and Humanities, Mahidol University, Nakhon Pathom, Thailand Introduction and objectives: Nurses play a major role in Thailand’s health care system. In recent years, the production of nurses, in both the public and private sectors, has been growing rapidly to respond to the shortage of health care staff. Alongside concerns over the number of nurses produced, the quality of nursing graduates is of equal importance. This study therefore aimed to 1) compare the self-assessed competency of final year Thai nursing students between public and private nursing schools, and 2) explore factors that were significantly associated with competency level.Methods: A cross-sectional clustered survey was conducted on 40 Thai nursing schools. Data were collected through self-administered questionnaires. The questionnaire consisted of questions about respondents’ background, their education profile, and a self-measured competency list. Descriptive statistics, factor analysis, and multivariate regression analysis were applied. Results: A total of 3,349 students participated in the survey. Approximately half of the respondents had spent their childhood in rural areas. The majority of respondents reported being “confident” or “very confident” in all competencies. Private nursing students reported a higher level of “public health competency” than public nursing students with statistical significance. However, there was no significant difference in “clinical competency” between the two groups.Conclusion: Nursing students from private institutions seemed to report higher levels of competency than those from public institutions, particularly with regard to public health. This phenomenon might have arisen because private nursing students had greater experience of diverse working environments during their training. One of the key limitations of this study was that the results were based on the subjective self-assessment of the respondents, which might risk respondent bias. Further studies that evaluate current nursing curricula in both public and private nursing schools to assess whether they meet the health needs of the population are recommended. Keywords: public health, factor analysis, regression analysis, confidenc
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