Optimal allocation of physicians improves accessibility and workload disparities in stroke care.

BACKGROUND: Inequalities in access to stroke care and the workload of physicians have been a challenge in recent times. This may be resolved by allocating physicians suitable for the expected demand. Therefore, this study analyzes whether reallocation using an optimization model reduces disparities in spatial access to healthcare and excessive workload. METHODS: This study targeted neuroendovascular specialists and primary stroke centers in Japan and employed an optimization model for reallocating neuroendovascular specialists to reduce the disparity in spatial accessibility to stroke treatment and workload for neuroendovascular specialists in Japan. A two-step floating catchment area method and an inverted two-step floating catchment area method were used to estimate the spatial accessibility and workload of neuroendovascular specialists as a potential crowdedness index. Quadratic programming has been proposed for the reallocation of neuroendovascular specialists. RESULTS: The reallocation of neuroendovascular specialists reduced the disparity in spatial accessibility and the potential crowdedness index. The standard deviation (SD) of the demand-weighted spatial accessibility index improved from 125.625 to 97.625. Simultaneously, the weighted median spatial accessibility index increased from 2.811 to 3.929. Additionally, the SD of the potential crowdedness index for estimating workload disparity decreased from 10,040.36 to 5934.275 after optimization. The sensitivity analysis also showed a similar trend of reducing disparities. CONCLUSIONS: The reallocation of neuroendovascular specialists reduced regional disparities in spatial accessibility to healthcare, potential crowdedness index, and disparities between facilities. Our findings contribute to planning health policies to realize equity throughout the healthcare system.

Spatial-temporal analysis of cerebral infarction mortality in Hokkaido, Japan: an ecological study using a conditional autoregressive model.

BACKGROUND: Accessibility to stroke treatments is a challenge that depends on the place of residence. However, recent advances in medical technology have improved health outcomes. Nevertheless, the geographic heterogeneity of medical resources may increase regional disparities. Therefore, evaluating spatial and temporal influences of the medical system on regional outcomes and advanced treatment of cerebral infarction are important from a health policy perspective. This spatial and temporal study aims to identify factors associated with mortality and to clarify regional disparities in cerebral infarction mortality at municipality level. METHODS: This ecological study used public data between 2010 and 2020 from municipalities in Hokkaido, Japan. We applied spatial and temporal condition autoregression analysis in a Bayesian setting, with inference based on the Markov chain Monte Carlo simulation. The response variable was the number of deaths due to cerebral infarction (ICD-10 code: I63). The explanatory variables were healthcare accessibility and socioeconomic status. RESULTS: The large number of emergency hospitals per 10,000 people (relative risk (RR) = 0.906, credible interval (Cr) = 0.861 to 0.954) was associated with low mortality. On the other hand, the large number of general hospitals per 10,000 people (RR = 1.123, Cr = 1.068 to 1.178) and longer distance to primary stroke centers (RR = 1.064, Cr = 1.014 to 1.110) were associated with high mortality. The standardized mortality ratio decreased from 2010 to 2020 in Hokkaido by approximately 44%. Regional disparity in mortality remained at the same level from 2010 to 2015, after which it narrowed by approximately 5% to 2020. After mapping, we identified municipalities with high mortality rates that emerged in Hokkaido's central and northeastern parts. CONCLUSION: Cerebral infarction mortality rates and the disparity in Hokkaido improved during the study period (2010-2020). This study emphasized that healthcare accessibility through places such as emergency hospitals and primary stroke centers was important in determining cerebral infarction mortality at the municipality level. In addition, this study identified municipalities with high mortality rates that require healthcare policy changes. The impact of socioeconomic factors on stroke is a global challenge, and improving access to healthcare may reduce disparities in outcomes.

Potential crowdedness of mechanical thrombectomy and cerebral infarction mortality in Japan: Application of inverted two-step floating catchment area method.

OBJECTIVES: This study aimed to evaluate a stroke medical delivery system based on population coverage and the potential crowdedness index (PCI) of mechanical thrombectomy and investigate the relationship between PCI and cerebral infarction mortality in Japan. MATERIALS AND METHODS: This cross-sectional study defined 662 facilities and 1605 neurointerventionalists as supply, population aged 55 years or older as demand, and set the reachable area for demand as 120 min in driving time. Multiple regression analysis adjusted for spatial autocorrelation was used to examine the relationship between PCI and cerebral infarction mortality. RESULTS: In the 2020 data, 99% of the population aged 55 years or older had access to mechanical thrombectomy (≤120 min), and the PCI ranged from 5876 to 129838, with a median of 30426. From 2020 to 2035, the PCI is estimated to increase (30426 to 32510), decreasing after 2035 (32510 to 29469). The PCI distribution exhibited geographical heterogeneity. High PCI values emerged in eastern Japan. According to regression analysis, the increase in PCI by 1% led to an increase of 0.13% in standardized mortality ratio of cerebral infarction in men. However, PCI did not significantly correlate with cerebral infarction mortality in women. CONCLUSIONS: PCI for hospitals based on supply and demand was geographically heterogeneous in Japan. Optimization of PCI contributes equalization of mechanical thrombectomy provision system and may improve cerebral infarction mortality.

Differences in spatial patterns of long-term care depending on severity in Hokkaido, Japan.

The increasing demand for long-term care (LTC) among the ageing population is a serious problem worldwide, which has greatly increased also in Japan since the introduction of the LTC insurance system there. Since there is a difference between insurers with respect to the proportion of people needing LTC, this study aimed at clarifying the spatial patterns of LTC. Insurer (n=156) LTC data for the period 2012-2019 were obtained from Ministry of Health, Labour, and Welfare and those needing LTC were classified into three classes: total, mild and severe with ageand sex-adjusted proportions needing LTC. Global and local Moran’s I statistics were calculated for each 2-year period to clarify the trends of global and local spatial clusters. From 2012 to 2019, the mean proportion of mild class cases increased (10.6% to 11.6%), whereas that of severe class cases decreased slightly (5.9% to 5.7%). The spatial pattern of the proportion of each class revealed positive spatial autocorrelation. Based on analysis by local Moran’s I, differences in spatial patterns were emphasised between the mild and severe classes. In Hokkaido, High-High clusters of mild cases were identified in the central and southern parts and severe ones in the northern and southern parts. Spatial patterns differed depending on the LTC class. Some insurers had distinctly higher or lower certification rates than those of their neighbourhoods.

ERRATUM: Differences in spatial patterns of long-term care depending on severity in Hokkaido, Japan.

Due to a mistake, the authors' affiliations were incorrectly reported in this article, published in Geospatial Health in 2022 (DOI: 10.4081/gh.2022.1077 - PMID: 35579241). The correct affiliations appear above. Geospatial Health DOI: 10.4081/gh.2022.1137.