Integrated strategies to tackle the inequitable distribution of doctors in Thailand: four decades of experience

Inequitable distribution of doctors with high concentration in urban cities negatively affects the public health objective of Health for All. Thus it is one of the main concerns for most health policy makers, particularly in developing countries. This paper aims to summarize strategies to solve inequitable distribution of human resources for health (HRH) between urban and rural areas, by using four decades of experience in Thailand as a case study for analysis

Issues and challenges in international doctoral education

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/88184/1/ketefian-issues_challenges_international_doctoral.pd

Measuring and decomposing inequity in self-reported morbidity and self-assessed health in Thailand

<p>Abstract</p> <p>Background</p> <p>In recent years, interest in the study of inequalities in health has not stopped at quantifying their magnitude; explaining the sources of inequalities has also become of great importance. This paper measures socioeconomic inequalities in self-reported morbidity and self-assessed health in Thailand, and the contributions of different population subgroups to those inequalities.</p> <p>Methods</p> <p>The Health and Welfare Survey 2003 conducted by the Thai National Statistical Office with 37,202 adult respondents is used for the analysis. The health outcomes of interest derive from three self-reported morbidity and two self-assessed health questions. Socioeconomic status is measured by adult-equivalent monthly income per household member. The concentration index (CI) of ill health is used as a measure of socioeconomic health inequalities, and is subsequently decomposed into contributing factors.</p> <p>Results</p> <p>The CIs reveal inequality gradients disadvantageous to the poor for both self-reported morbidity and self-assessed health in Thailand. The magnitudes of these inequalities were higher for the self-assessed health outcomes than for the self-reported morbidity outcomes. Age and sex played significant roles in accounting for the inequality in reported chronic illness (33.7 percent of the total inequality observed), hospital admission (27.8 percent), and self-assessed deterioration of health compared to a year ago (31.9 percent). The effect of being female and aged 60 years or older was by far the strongest demographic determinant of inequality across all five types of health outcome. Having a low socioeconomic status as measured by income quintile, education and work status were the main contributors disadvantaging the poor in self-rated health compared to a year ago (47.1 percent) and self-assessed health compared to peers (47.4 percent). Residence in the rural Northeast and rural North were the main regional contributors to inequality in self-reported recent and chronic illness, while residence in the rural Northeast was the major contributor to the tendency of the poor to report lower levels of self-assessed health compared to peers.</p> <p>Conclusion</p> <p>The findings confirm that substantial socioeconomic inequalities in health as measured by self-reported morbidity and self-assessed health exist in Thailand. Decomposition analysis shows that inequalities in health status are associated with particular demographic, socioeconomic and geographic population subgroups. Vulnerable subgroups which are prone to both ill health and relative poverty warrant targeted policy attention.</p

Post universal health coverage trend and geographical inequalities of mortality in Thailand

BACKGROUND: Thailand has achieved remarkable improvement in health status since the achievement of universal health coverage in 2002. Health equity has improved significantly. However, challenges on health inequity still remain.This study aimed to determine the trends of geographical inequalities in disease specific mortality in Thailand after the country achieved universal health coverage. METHODS: National vital registration data from 2001 to 2014 were used to calculate age-adjusted mortality rate and standardized mortality ratio (SMR). To minimize large variations in mortality across administrative districts, the adjacent districts were systematically grouped into “super-districts” by taking into account the population size and proximity. Geographical mortality inequality among super-districts was measured by the coefficient of variation. Mixed effects modeling was used to test the difference in trends between super-districts. RESULTS: The overall SMR steadily declined from 1.2 in 2001 to 0.9 in 2014. The upper north and upper northeast regions had higher SMR whereas Greater Bangkok achieved the lowest SMR. Decreases in SMR were mostly seen in Greater Bangkok and the upper northern region. Coefficient of variation of SMR rapidly decreased from 20.0 in 2001 to 12.5 in 2007 and remained close to this value until 2014. The mixed effects modelling revealed significant differences in trends of SMR across super-districts. Inequality in mortality declined among adults (≥15 years old) but increased in children (0–14 years old). A declining trend in inequality of mortality was seen in almost all regions except Greater Bangkok where the inequality in SMR remained high throughout the study period. CONCLUSIONS: A decline in the adult mortality inequality across almost all regions of Thailand followed universal health coverage. Inequalities in child mortality rates and among residents of Greater Bangkok need further exploration

Self-assessed health among Thai elderly

<p>Abstract</p> <p>Background</p> <p>The ageing of the population is rapidly progressing in Thailand. Self-assessed health status can provide a holistic view of the health of the elderly. This study aims to identify the determinants of self-assessed health among older Thai people.</p> <p>Methods</p> <p>The data for this study were drawn from a national survey of older persons conducted in 2007. Stratified two-stage random sampling was used for data collection. The analysis was restricted to the population aged 60 and above. The study used univariate, bivariate, and multivariate analysis procedures to analyze the data. Bivariate analysis was used to identify the factors associated with self assessment of health status. After controlling for other variables, the variables were further examined using multivariate analysis (binary logistic regression) in order to identify the significant predictors of the likelihood of reporting poor health.</p> <p>Results</p> <p>Overall, 30,427 elderly people were interviewed in this study. More than half of the sampled respondents (53%) were aged 60-69 years and about one out of seven (13%) were aged 80 years or above. About three in five respondents (56%) reported that their health was either fair or very bad/bad. Logistic regression analysis found that age, education, marital status, working status, income, functional status, number of chronic diseases, and number of psychosocial symptoms are significant predictors in determining health status. Respondents who faced more difficulty in daily life were more likely to rate their health as poor compared to those who faced less such difficulty. For instance, respondents who could not perform 3 or more activities of daily living (ADLs) were 3.3 times more likely to assess their health as poor compared to those who could perform all the ADLs. Similarly, respondents who had 1, 2, or 3 or more chronic diseases were 1.8 times, 2.4 times, and 3.7 times, respectively, more likely to report their health as poor compared to those who had no chronic disease at all. Moreover, respondents who had 1-2, 3-4, or 5 or more psychosocial symptoms in the previous months were 1.6 times, 2.2 times, and 2.7 times, respectively, more likely to report poor health compared to those who did not have any psychosocial symptoms during the same period.</p> <p>Conclusion</p> <p>Self-assessed poor health is not uncommon among older people in Thailand. No single factor accounts for the self-assessed poor health. The study has found that chronic disease, functional status, and psychosocial symptoms are the strongest determinants of self-assessed poor health of elderly people living in Thailand. Therefore, health-related programs should focus on all the factors identified in this paper to improve the overall well-being of the ageing population of Thailand.</p

An approach to classifying human resources constraints to attaining health-related Millennium Development Goals

BACKGROUND: For any wide-ranging effort to scale up health-related priority interventions, human resources for health (HRH) are likely to be a key to success. This study explores constraints related to human resources in the health sector for achieving the Millennium Development Goals (MDGs) in low-income countries. METHODS AND FRAMEWORK: The analysis drew on information from a variety of publicly-available sources and principally on data presented in published papers in peer-reviewed journals. For classifying HRH constraints an analytical framework was used that considers constraints at five levels: individual characteristics, the health service delivery level, the health sector level, training capacities and the sociopolitical and economic context of a country. RESULTS AND DISCUSSION: At individual level, the decision to enter, remain and serve in the health sector workforce is influenced by a series of social, economic, cultural and gender-related determinants. For example, to cover the health needs of the poorest it is necessary to employ personnel with specific social, ethnic and cultural characteristics. At health-service level, the commitment of health staff is determined by a number of organizational and management factors. The workplace environment has a great impact not only on health worker performance, but also on the comprehensiveness and efficiency of health service delivery. At health-sector level, the use of monetary and nonmonetary incentives is of crucial importance for having the accurate skill mix at the appropriate place. Scaling up of priority interventions is likely to require significant investments in initial and continuous training. Given the lead time required to produce new health workers, such investments must occur in the early phases of scaling up. At the same time coherent national HRH policies are required for giving direction on HRH development and linking HRH into health-sector reform issues, the scaling-up of priority interventions, poverty reduction strategies, and training approaches. Multisectoral collaboration and the sociopolitical and economic context of a country determine health sector workforce development and potential emigration. CONCLUSIONS: Key determinants of success for achieving international development goals are closely related to human-resource development

The Epidemiology and Clinical Spectrum of Melioidosis: 540 Cases from the 20 Year Darwin Prospective Study

Melioidosis is an occupationally and recreationally acquired infection important in Southeast Asia and northern Australia. Recently cases have been reported from more diverse locations globally. The responsible bacterium, Burkholderia pseudomallei, is considered a potential biothreat agent. Risk factors predisposing to melioidosis are well recognised, most notably diabetes. The Darwin prospective melioidosis study has identified 540 cases of melioidosis over 20 years and analysis of the epidemiology and clinical findings provides important new insights into this disease. Risk factors identified in addition to diabetes, hazardous alcohol use and chronic renal disease include chronic lung disease, malignancies, rheumatic heart disease, cardiac failure and age ≥50 years. Half of patients presented with pneumonia and septic shock was common (21%). The decrease in mortality from 30% in the first 5 years of the study to 9% in the last five years is attributed to earlier diagnosis and improvements in intensive care management. Of the 77 fatal cases (14%), all had known risk factors for melioidosis. This supports the most important conclusion of the study, which is that melioidosis is very unlikely to kill a healthy person, provided the infection is diagnosed early and resources are available to provide appropriate antibiotics and critical care where required