ArticleBMC health services research2019
Forecasting maldistribution of human resources for healthcare and patients in Japan: a utilization-based approach.
Article in BMC health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
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- Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model.Heliyon · 2024Article
- Inequality in the distribution of resources in the health sector before and after the Health Transformation Plan in Qazvin, Iran.Journal of health, population, and nutrition · 2024Article
- Regional Inequality and Associated Factors of Emergency Medicine Beds Distribution in China.International journal of public health · 2024Article
- Knowledge, attitudes, and practices of family caregivers for patients with cerebral infarction toward home-based care.Frontiers in public health · 2024Article
- Measuring inequality in the distribution of health human resources using the Hirschman-Herfindahl index: a case study of Qazvin Province.BMC health services research · 2022Article
- Current and Future Needs for Human Resources for Ethiopia's National Health Information System: Survey and Forecasting Study.JMIR medical education · 2022Article
- Regional Disparity of Reperfusion Therapy for Acute Ischemic Stroke in Japan: A Retrospective Analysis of Nationwide Claims Data from 2010 to 2015.Journal of the American Heart Association · 2021Article
- Projections of psychiatrists' distribution for patients in Japan: a utilization-based approach.Human resources for health · 2021Article
- Elucidating variations in outcomes among older end-stage renal disease patients on hemodialysis in Fukuoka Prefecture, Japan.PloS one · 2021Article
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6 authors.
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Abstract
backgroundHokkaido'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.
methodWe 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.
resultsOur 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.
conclusionThese 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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