Definition of “Rural” Determines the Placement Outcomes of a Rural Medical Education Program: Analysis of Jichi Medical University Graduates
ABSTRACT Purpose: To show the impact of changing the definition of what is “rural” on the outcomes of a rural medical education program.Methods: A cross-sectional sample of 643 graduates under obligatory rural service and 1,699 graduates after serving their obligation, all from Jichi Medical University (JMU), a binding rural education program in Japan, were used as the data source. Communities were divided into decile groups according to population density, and the cut-off for “rural/nonrural” was altered in order to study its impact on the data.Findings: The rural practice rate of obliged graduates had its peak in the decile groups with the lowest population densities, while the peak rates of postobligation graduates and non-JMU physicians were at the decile groups with the highest population densities. Rural practice rates of all of the 3 groups of physicians increased with the increase in inclusiveness of rural definition. The ratio of rural practice rate of obliged graduates to that of non-JMU physicians (“relative effectiveness”) increased remarkably with the increase in exclusiveness of rural definition. The relative effectiveness of postobligation graduates did not substantially increase after the cut-off exceeded a certain point of exclusiveness.Conclusions: Definition of “rural” largely determined the rural practice rate and relative effectiveness of JMU graduates. The results suggest that results of past outcome studies of rural medical education programs are potentially biased depending on how rural is defined.
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ABSTRACT: Inequity in physician distribution poses a challenge to many health systems. In Japan, a new postgraduate training program for all new medical graduates was introduced in 2004, and researchers have argued that this program has increased inequalities in physician distribution. We examined the trends in the geographic distribution of pediatricians as well as all physicians from 1996 to 2010 to identify the impact of the launch of the new training program. The Gini coefficient was calculated using municipalities as the study unit within each prefecture to assess whether there were significant changes in the intra-prefectural distribution of all physicians and pediatricians before and after the launch of the new training program. The effect of the new program was quantified by estimating the difference in the slope in the time trend of the Gini coefficients before and after 2004 using a linear change-point regression design. We categorized 47 prefectures in Japan into two groups: 1) predominantly urban and 2) others by the definition from OECD to conduct stratified analyses by urban-rural status. The trends in physician distribution worsened after 2004 for all physicians (p value<.0001) and pediatricians (p value = 0.0057). For all physicians, the trends worsened after 2004 both in predominantly urban prefectures (p value = 0.0012) and others (p value<0.0001), whereas, for pediatricians, the distribution worsened in others (p value = 0.0343), but not in predominantly urban prefectures (p value = 0.0584). The intra-prefectural distribution of physicians worsened after the launch of the new training program, which may reflect the impact of the new postgraduate program. In pediatrics, changes in the Gini trend differed significantly before and after the launch of the new training program in others, but not in predominantly urban prefectures. Further observation is needed to explore how this difference in trends affects the health status of the child population.PLoS ONE 10/2013; 8(10):e77045. DOI:10.1371/journal.pone.0077045 · 3.53 Impact Factor
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ABSTRACT: Objectives To explore determinants of change in pediatrician supply in Japan, and examine impacts of a 2004 reform of postgraduate medical education on pediatricians’ practice location choice. Methods Data were compiled from secondary data sources. The dependent variable was the change in the number of pediatricians at the municipality (“secondary tier of medical care” [STM]) level. To analyze the determinants of pediatrician location choices, we considered the following predictors: initial ratio of pediatricians per 1000 children under five years of age (pediatrician density) and under-5 mortality as measures of local area need, as well as measures of residential quality. Ordinary least-squares regression models were used to estimate the associations. A coefficient equality test was performed to examine differences in predictors before and after 2004. Basic comparisons of pediatrician coverage in the top and bottom 10% of STMs were conducted to assess inequality in pediatrician supply. Results Increased supply was inversely associated with baseline pediatrician density both in the pre-period and post-period. Estimated impact of pediatrician density declined over time (P = 0.026), while opposite trends were observed for measures of residential quality. More specifically, urban centers and the SES composite index were positively associated with pediatrician supply for the post-period, but no such associations were found for the pre-period. Inequality in pediatrician distribution increased substantially after the reform, with the best-served 10% of communities benefitting from five times the pediatrician coverage compared to the least-served 10%. Conclusions Residential quality increasingly became a function of location preference rather than public health needs after the reform. New placement schemes should be developed to achieve more equity in access to pediatric care.Journal of Epidemiology 03/2014; 24(3). DOI:10.2188/jea.JE20130117 · 2.86 Impact Factor
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ABSTRACT: In 2004, the Japanese government permitted medical graduates for the first time to choose their training location directly through a national matching system. While the reform has had a major impact on physicians' placement, research on the impact of the new system on physician distribution in Japan has been limited. In this study, we sought to examine the determinants of physicians' practice location choice, as well as factors influencing their geographic distribution before and after the launch of Japan's 2004 postgraduate medical training programme. We analyzed secondary data. The dependent variable was the change in physician supply at the secondary tier of medical care in Japan, a level which is roughly comparable to a Hospital Service Area in the US. Physicians were categorized into two groups according to the institutions where they practiced; specifically, hospitals and clinics. We considered the following predictors of physician supply: ratio of physicians per 1,000 population (physician density), age-adjusted mortality, as well as measures of residential quality. Ordinary least-squares regression models were used to estimate the associations. A coefficient equality test was performed to examine differences in predictors before and after 2004. Baseline physician density showed a positive association with the change in physician supply after the launch of the 2004 programme (P-value < .001), whereas no such effect was found before 2004. Urban locations were inversely associated with the change in physician supply before 2004 (P-value = .026), whereas a positive association was found after 2004 (P-value < .001). Urban location and area-level socioeconomic status were positively correlated with the change in hospital physician supply after 2004 (P-values < .001 for urban centre, and .025 for area-level socioeconomic status), even though in the period prior to the 2004 training scheme, urban location was inversely associated with the change in physician supply (P-value = .015) and area-level socioeconomic status was not correlated. Following the introduction of the 2004 postgraduate training programme, physicians in Japan were more likely to move to areas with already high physician density and urban locations. These changes worsened regional inequality in physician supply, particularly hospital doctors.Human Resources for Health 01/2015; 13(1):5. DOI:10.1186/1478-4491-13-5 · 1.83 Impact Factor