Measuring the inequalities in radiotherapy health resources in Japan: comparison of the Hokkaido-Tohoku and Tokyo districts

Ohba, Hisateru; Narumi, Masakazu; Hosokawa, Yoichiro; Aoki, Masahiko

doi:10.1007/s11604-009-0376-6

Cited by 7 publications

(4 citation statements)

References 8 publications

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“…Although 20% of the population live in rural regions in the U.S., only 3% of oncology professionals are in these regions (Kirkwood et al 2014). In Japan, the number of oncology professionals is also higher in urban than in rural regions, which have hardly any (Ohba et al 2010;Yamamoto and Tamura 2012;Fukuda et al 2018). As the number of patients with cancer has been steadily increasing in Japan, with the aim to provide an equal cancer treatment throughout the country, the Japanese government approved the Cancer Control Act in 2007 and the Basic Plan to Promote Cancer Control program was launched (Ministry of Health, Labour and Welfare 2007).…”

Section: Introductionmentioning

confidence: 99%

Difference in the Types of Treated Cancer between Clinics and Small-to-Middle-Sized Hospitals in Rural Communities of Japan

Komatsu

Teraura

Yamaguchi

et al. 2019

Tohoku J. Exp. Med.

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Resolution of regional disparities in cancer mortality is global challenge. Establishing an equal system of cancer treatment throughout the country is required under the Cancer Control Act in Japan. The types of treated cancer may reflect practical experience at the institutions and cooperation to other institutions. This study investigated the types treated at the institutions in rural communities of Japan. A questionnaire survey was conducted for 811 public rural institutions (clinics and small-to-middle-sized hospitals [< 200 beds]) in 2013. The survey's items included the types of treated cancer (14 categories: stomach, colon, breast, liver, biliary tract, pancreatic, prostate, esophageal, lung, renal, urinary tract, testicular, hematopoietic, and others) and the first five types were defined as major cancers. The data were analyzed between hospitals and clinics. The response rate was about 60%, and of 177 hospitals and 281 clinics, 54 hospitals (30%) and 10 clinics (3%) reported the types of cancer. The median number of cancer types in hospitals was significantly greater than that of clinics (4 [interquartile range 3.0-7.8]) vs. 1 [1.0-1.8], P < 0.01). The prevalence of hospitals treating at least one of five major cancers was significantly greater than that of clinics (96% vs. 30%, P < 0.01). The prevalence of clinics treating prostate cancer was significantly greater than that of hospitals (31% vs. 70%, P = 0.03). In conclusion, most types of cancer are treated at small-to-middle-sized hospitals, except for prostate cancer, providing basic information about cancer treatment in rural communities of Japan.

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Section: Introductionmentioning

confidence: 99%

Difference in the Types of Treated Cancer between Clinics and Small-to-Middle-Sized Hospitals in Rural Communities of Japan

Komatsu

Teraura

Yamaguchi

et al. 2019

Tohoku J. Exp. Med.

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“…In Japan, Toyabe [ 6 ] compared the Gini coefficient with other inequality indices such Atkinson index and Theil index to assess the distribution of physicians where all the indices generated relatively the same findings. Also in Japan, Ohba et al [ 8 ] determined that the inequality of radiotherapy health resources in Tokyo district is higher than in the Hokkaido-Tohoku by using the Gini coefficient. Furthermore, Matsumoto et al [ 7 ] used Gini coefficient to validate that primary care physicians’ distribution in Britain is relatively equal than in Japan.…”

Section: Methods and Datamentioning

confidence: 99%

“…Ohba et al [ 8 ] compared the geographical inequalities of radiotherapy resources in two districts of Japan, Hokkaido-Tohoku and Tokyo. Results demonstrated that the inequality is higher in the Tokyo district.…”

Section: Introductionmentioning

confidence: 99%

Bayesian estimation of the effect of health inequality in disease detection

Lope

Demirhan

Dolgun

2022

Int J Equity Health

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Background Measuring health inequality is essential to ensure that everyone has equal accessibility to health care. Studies in the past have continuously presented and showed areas or groups of people affected by various inequality in accessing the health resources and services to help improve this matter. Alongside, disease prevention is as important to minimise the disease burden and improve health and quality of life. These aspects are interlinked and greatly contributes to one’s health. Method In this study, the Gini coefficient and Lorenz curve are used to give an indication of the overall health inequality. The impact of this inequality in granular level is demonstrated using Bayesian estimation for disease detection. The Bayesian estimation used a two-component modelling approach that separates the case detection process and incidence rate using a mixed Poisson distribution while capturing underlying spatio-temporal characteristics. Bayesian model averaging is used in conjunction with the two-component modelling approach to improve the accuracy of estimates by incorporating many candidate models into the analysis instead of using fixed component models. This method is applied to an infectious disease, influenza, in Victoria, Australia between 2013 and 2016 and the corresponding primary health care of the state. Result There is a relatively equal distribution of health resources and services pertaining to general practitioners (GP) and GP clinics in Victoria, Australia. Roughly 80 percent of the population shares 70 percent of the number of GPs and GP clinics. The Bayesian estimation with model averaging revealed that access difficulty to health services impacts both case detection probability and incidence rate. Minimal differences are recorded in the observed and estimated incidence of influenza cases considering social deprivation factors. In most years, areas in Victoria’s southwest and eastern parts have potential under-reported cases consistent with their relatively lower number of GP or GP clinics. Conclusion The Bayesian model estimated a slight discrepancy between the estimated incidence and the observed cases of influenza in Victoria, Australia in 2013-2016 period. This is consistent with the relatively equal health resources and services in the state. This finding is beneficial in determining areas with potential under-reported cases and under-served health care. The proposed approach in this study provides insight into the impact of health inequality in disease detection without requiring costly and time-extensive surveys and relying mainly on the data at hand. Furthermore, the application of Bayesian model averaging provided a flexible modelling framework that allows covariates to move between case detection and incidence models.

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“…The GC is widely used to measure inequity in income distribution. Several research groups have applied this method to evaluate health resource distribution; for example, physicians or medical facilities [26–28]. We adopted the GC as an indicator to refer to regional maldistribution of physicians/specialists to aid evaluation of inequity of human resources by SMCA.…”

Section: Methodsmentioning

confidence: 99%

Forecasting maldistribution of human resources for healthcare and patients in Japan: a utilization-based approach

Ishikawa

Nakao

Fujiwara

et al. 2019

BMC Health Serv Res

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Background Hokkaido’s demographic trend of population decrease with aging population is remarkable even in Japan. Although healthcare policy decision-makers need to appropriately allocate resources while grasping regional demands, not much is available on whether medical demand would increase or not for future. In addition, little is known about what impact will current situation have on future demand-supply balance and equality by regions. This study aims to support decision-making in human resource planning for coping with changing population structure by forecasting future demand, and evaluation those regional maldistributions. Method We set patients with acute myocardial infarction or cerebral stroke, and all medical care as study subjects and analyzed for 2015, 2025, and 2035 in Hokkaido and each Secondary Medical Care Area. We used a utilization-based approach to estimate the healthcare supply–demand balance in the future. Moreover, we evaluated the regional maldistribution of demand-supply balance by calculating Herfindahl-Hirschman Index, Gini Coefficients, the number of physicians/specialists per patient. Moreover, we conducted sensitivity analysis to evaluation impact on aspects of demand-supply balance by uncertainty of utilization for future. Results Our results displayed that concentration of patients will progress, while regional distribution will shrink in all subject. However, from comparison based on all medical care, Gini Coefficients of acute myocardial infarction and cerebral stroke has always been high. This suggest that the resource allocation of them has room for improvement. In addition, our analysis showed the change in this balance will differ in each region in the future. Moreover, demographic change will not consistent with the number of patient change from 2015 to 2035. Conclusion These results suggest policy planners should use the number of patient by disease, by region as indicator of demand, instead of provider-to-population ratios being in use today. The result of our sensitivity analysis show two findings. First, the range of each indicator have possible for future. Second, increase of utilization, for instance lowing barrier in the use by development operation of patient transportation in AMI/CS, would improve maldistribution of opportunity for resident to get emergency medical services.

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Measuring the inequalities in radiotherapy health resources in Japan: comparison of the Hokkaido-Tohoku and Tokyo districts

Abstract: Geographical inequalities in radiotherapy health resources tended to be larger in the Tokyo district than in the Hokkaido-Tohoku district. It is expected that the radiotherapy system will be substantially improved by the Basic Plan to Promote Cancer Control Programs.

Cited by 7 publications

References 8 publications

Difference in the Types of Treated Cancer between Clinics and Small-to-Middle-Sized Hospitals in Rural Communities of Japan

Difference in the Types of Treated Cancer between Clinics and Small-to-Middle-Sized Hospitals in Rural Communities of Japan

Bayesian estimation of the effect of health inequality in disease detection

Forecasting maldistribution of human resources for healthcare and patients in Japan: a utilization-based approach

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