Forecasting the regional distribution and sufficiency of physicians in Japan with a coupled system dynamics-geographic information system model

Gender Inequality Improvement in Medical School Admissions in Japan

Purpose: To investigate the effects of gender discrimination in Japan's medical school admission process and to assess whether the situation has improved since the disclosure of such discrimination in 2018. Materials and Methods: A cross-sectional study was conducted using secondary data from the Ministry of Education, Culture, Sports, Science, and Technology. The proportions of male and female applicants vis-à-vis all successful candidates admitted from 2016 to 2021 were analyzed; four medical schools were found to be systematically guilty of discriminatory admission practices. Acceptance rate ratios (ARRs) were estimated, and difference-in-differences (DID) analysis was used to examine the differences in ARRs between the two groups-the 4 and 75 medical schools that were and were not reported, respectively-in the predisclosure (2016-2018) and postdisclosure (2019-2021) periods. Results: Female applicants were subjected to discriminatory admission practices at the four reported medical schools in the predisclosure period. However, postdisclosure, those four medical schools had higher female than male acceptance rates in all 3 years. DID analysis revealed a statistically significant estimated average treatment effect on the treated of 0.25148 (95% confidence interval [0.00455-0.49840]), indicating a 0.25-point increase in ARRs relative to the other 75 medical schools. Conclusions: Discriminatory practices against female applicants have decreased since the disclosure in 2018, with the acceptance rate of female students exceeding that of male students for the first time in 2021. In response to these findings, we propose recommendations to further promote gender equality in medicine.

Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model

Poverty, an intricate global challenge influenced by economic, political, and social elements, is characterized by a deficiency in crucial resources, necessitating collective efforts towards its mitigation as embodied in the United Nations' Sustainable Development Goals. The Gini coefficient is a statistical instrument used by nations to measure income inequality, economic status, and social disparity, as escalated income inequality often parallels high poverty rates. Despite its standard annual computation, impeded by logistical hurdles and the gradual transformation of income inequality, we suggest that short-term forecasting of the Gini coefficient could offer instantaneous comprehension of shifts in income inequality during swift transitions, such as variances due to seasonal employment patterns in the expanding gig economy. System Identification (SI), a methodology utilized in domains like engineering and mathematical modeling to construct or refine dynamic system models from captured data, relies significantly on the Nonlinear Auto-Regressive (NAR) model due to its reliability and capability of integrating nonlinear functions, complemented by contemporary machine learning strategies and computational algorithms to approximate complex system dynamics to address these limitations. In this study, we introduce a NAR Multi-Layer Perceptron (MLP) approach for brief term estimation of the Gini coefficient. Several parameters were tested to discover the optimal model for Malaysia's Gini coefficient within 1987-2015, namely the output lag space, hidden units, and initial random seeds. The One-Step-Ahead (OSA), residual correlation, and residual histograms were used to test the validity of the model. The results demonstrate the model's efficacy over a 28-year period with superior model fit (MSE: 1.14 × 10-7) and uncorrelated residuals, thereby substantiating the model's validity and usefulness for predicting short-term variations in much smaller time steps compared to traditional manual approaches.

Slack Is Needed to Solve the Shortage of Nurses

Healthcare systems are facing a shortage of nurses. This article identifies some of the major causes of this and the issues that need to be solved. We take a perspective derived from queuing theory: the patient-nurse relationship is characterized by a scarcity of time and resources, requiring comprehensive coordination at all levels. For coordination, we take an information-theoretic perspective. Using both perspectives, we analyze the nature of healthcare services and show that ensuring slack, meaning a less than exhaustive use of human resources, is a sine qua non to having a good, functioning healthcare system. We analyze what coordination efforts are needed to manage relatively simple office hours, wards, and home care. Next, we address the level of care where providers cannot themselves prevent the complexity of organization that possibly damages care tasks and job quality. A lack of job quality may result in nurses leaving the profession. Job quality, in this context, depends on the ability of nurses to coordinate their activities. This requires slack resources. The availability of slack that is efficient depends on a stable inflow and retention rate of nurses. The healthcare system as a whole should ensure that the required nurse workforce will be able to coordinate and execute their tasks. Above that, workforce policies need more stability.

Educational Strategies to Reduce Physician Shortages in Underserved Areas: A Systematic Review

The shortage of physicians in rural and underserved areas is an obstacle to the implementation of Universal Health Coverage (UHC). We carried out a systematic review to analyze the effectiveness of initiatives in medical education aimed to increase the supply of physicians in rural or underserved areas. We searched for studies published between 1999 and 2019 in six databases, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Interventional or observational controlled studies were defined as inclusion criteria. A total of 955 relevant unique records were selected for inclusion, which resulted in the identification of 17 articles for analysis. The admission of students from rural areas associated with a rural curriculum represented 52.95% of the interventions. Medical practice after graduation in rural or underserved areas was the most evaluated outcome, representing 12 publications (70.59%). Participants of these educational initiatives were more likely to work in rural or underserved areas or to choose family medicine, with significant differences between the groups in 82.35% of the studies. Educational strategies in undergraduate and medical residencies are effective. However, it is necessary to expand these interventions to ensure the supply of physicians in rural or urban underserved areas.

Body surface registration considering individual differences with non-rigid iterative closest point

PURPOSE

In telemedicine such as remote auscultation, patients themselves or non-medical people such as patient's parents need to place the stethoscope on their body surface in appropriate positions instead of the physicians. Meanwhile, as the position depends on the individual difference of body shape, there is a demand for the efficient navigation to place the medical equipment.

METHODS

In this paper, we have proposed a non-rigid iterative closest point (ICP)-based registration method for localizing the auscultation area considering the individual difference of body surface. The proposed system provides the listening position by applying the body surface registration between the patient and reference model with the specified auscultation area. Our novelty is that selecting the utilized reference model similar to the patient body among several types of the prepared reference model increases the registration accuracy.

RESULTS

Simulation results showed that the registration error increases due to deviations of the body shape between the targeted models and reference model. Experimental results demonstrated that the proposed non-rigid ICP registration is capable of estimating the auscultation area with average error 5-19 mm when selecting the most similar reference model. The statistical analysis showed high correlation between the registration accuracy and similarity of the utilized models.

CONCLUSION

The proposed non-rigid ICP registration is a promising new method that provides accurate auscultation area takes into account the individual difference of body shape. Our hypothesis that the registration accuracy depends on the similarity of both body surfaces is validated through simulation study and human trial.

Modelo dinámico para proyectar la necesidad de recursos humanos en salud: anestesistas en Uruguay

Objetivo Desarrollar un modelo dinámico para simular la oferta de médicos especialistas y estimar la brecha especto a la demanda/necesidad en anestesiología en el sistema de salud del Uruguay. Métodos Se desarrolló un modelo de simulación dinámico determinístico implementado en el programa libre R. Se analizaron las proyecciones en el período 2011-2050 y se estimó la brecha a partir de la situación de equilibrio o desequilibrio entre oferta y demanda/necesidad. Se evaluó la calidad del modelo comparando los valores simulados con los datos históricos, con indicadores de bondad de ajuste, como la raíz del error cuadrático medio relativo (rRMSE). Se realizó un análisis de sensibilidad con respecto a los cupos de ingreso a la especia- lidady la tasa de crecimiento de la necesidad de especialistas. Resultados Se proyectó la oferta y demanda de anestesistas para el período considerado. Se obtuvo un rRMSE menor a 0,1, lo que sugiere que el modelo propuesto reproduce adecuadamente la dinámica de la oferta real. Para el período proyectado la situación a mediano y largo plazo es de equilibrio. Conclusión El modelo simulado presenta buen ajuste, por lo que la proyección de la oferta de Recursos Humanos (RR. HH.) representa de forma precisa la disponibilidad futura de la fuerza de trabajo. Además, el modelo representa un insumo de interés para la gestión informada sobre la necesidad de recursos humanos y las políticas de salud, dado que permite evaluar las proyecciones bajo diferentes escenarios.

Geographic inequalities in non-acute healthcare supply: evidence from Ireland

Background: Recent reforms in Ireland, as outlined in Sláintecare, the report of the cross-party parliamentary committee on health, are focused on shifting from a hospital-centric system to one where non-acute care plays a more central role. However, these reforms were embarked on in the absence of timely and accurate information about the capacity of non-acute care to take on a more central role in the system. To help address this gap, this paper outlines the most comprehensive analysis to date of geographic inequalities in non-acute care supply in Ireland. Methods: Data on the supply of 10 non-acute services including primary care, allied health, and care for older people, were collated. Per capita supply for each service is described for 28 counties in Ireland (Tipperary and Dublin divided into North and South), using 2014 supply and population data. To examine inequity in the geographic distribution of services, raw population in each county was adjusted for a range of needs indicators. Results: The findings show considerable geographic inequalities across counties in the supply of non-acute care. Some counties had low levels of supply of several types of non-acute care. The findings remain largely unchanged after adjusting for need, suggesting that the unequal patterns of supply are also inequitable. Conclusions: In the context of population changes and the influence of non-need factors, the persistence of historical budgeting in Ireland has led to considerable geographic inequities in non-acute supply, with important lessons for Ireland and for other countries. Such inequities come into sharp relief in the context of COVID-19, where non-acute supply plays a crucial role in ensuring that acute services are preserved for treating acutely ill patients.

The health workforce demand: a systematic literature review

Understanding imbalances between the supply and demand of the human resour- ces for health (HRH) is essential for enhancing health outcomes. Addressing the HRH demand is particularly challenging, especially given the deficit of accurate data and surplus of unresolved methodological flaws. This study presents a systematic review of the literature surrounding HRH demand and answers the following key questions: How has HRH demand been addressed? What are the harms and barriers that accompany HRH demand modeling? This systematic review was performed following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) statement. Relevant keywords were used in a thorough search of the PubMed/MEDLINE, SCOPUS, and Web of Science databases. A total of 2,599 papers were retrieved and evaluated according to their title and abstract. Of these, the full-text of 400 papers was analyzed, 53 of which successfully met the inclusion criteria in our study. While the topic's relevance is widespread, it still lacks a validated approach to model HRH demand adequately. The main characteristics of the applied methods are presented, such as their application complexity by health policymakers. Opportunities and orientations for further research are also highlighted.

Environment, Business, and Health Care Prevail: A Comprehensive, Systematic Review of System Dynamics Application Domains

System dynamics, as a methodology for analyzing and understanding various types of systems, has been applied in research for several decades. We undertook a review to identify the latest application domains and map the realm of system dynamics. The systematic review was conducted according to the PRISMA methodology. We analyzed and categorized 212 articles and found that the vast majority of studies belong to the fields of business administration, health, and environmental research. Altogether, 20 groups of modeling and simulation topics can be recognized. System dynamics is occasionally supported by other modeling methodologies such as the agent-based modeling approach. There are issues related to published studies mostly associated with testing of validity and reasonability of models, leading to the development of predictions that are not grounded in verified models. This study contributes to the development of system dynamics as a methodology that can offer new ideas, highlight limitations, or provide analogies for further research in various research disciplines.

The need for home care physicians in Japan - 2020 to 2060

Background

Japan faces the most elderly society in the world, and the Japanese government has launched an unprecedented health plan to reinforce home care medicine and increase the number of home care physicians, which means that an understanding of future needs for geriatric home care is vital. However, little is known about the future need for home care physicians. We attempted to estimate the basic need for home care physicians from 2020 to 2060.

Methods

Our estimation is based on modification of major health work force analysis methods using previously reported official data. Two models were developed to estimate the necessary number of full-time equivalent (FTE) home care physicians: one based on home care patient mortality, the other using physician-to-patient ratio, working with estimated numbers of home and nursing home deaths from 2020 to 2060. Moreover, the final process considered and adjusted for future changes in the proportion of patients dying at home. Lastly, we converted estimated FTE physicians to an estimated head count.

Results

Results were concordant between our two models. In every instance, there was overlap of high- and low-estimations between the mortality method and the physician-to-patient method, and the estimates show highly similar patterns. Furthermore, our estimation is supported by the current number of physicians, which was calculated using a different method. Approximately 1.7 times (1.6 by head count) the current number of FTE home care physicians will be needed in Japan in the late 2030’s, peaking at 33,500 FTE (71,500 head count). However, the need for home care physicians is anticipated to begin decreasing by 2040.

Conclusion

The results indicate that the importance of home care physicians will rise with the growing elderly population, and that improvements in home care could partially suppress future need for physicians. After the late 2030’s, the supply can be reduced gradually, accounting for the decreasing total number of deaths after 2040. In order to provide sufficient home care and terminal care at home, increasing the number of home care physicians is indispensable. However, the unregulated supply of home care physicians will require careful attention in the future.

A System Dynamics Simulation Applied to Healthcare: A Systematic Review

In recent years, there has been significant interest in developing system dynamics simulation models to analyze complex healthcare problems. However, there is a lack of studies seeking to summarize the available papers in healthcare and present evidence on the effectiveness of system dynamics simulation in this area. The present paper draws on a systematic selection of published literature from 2000 to 2019, in order to form a comprehensive view of current applications of system dynamics methodology that address complex healthcare issues. The results indicate that the application of system dynamics has attracted significant attention from healthcare researchers since 2013. To date, articles on system dynamics have focused on a variety of healthcare topics. The most popular research areas among the reviewed papers included the topics of patient flow, obesity, workforce demand, and HIV/AIDS. Finally, the quality of the included papers was assessed based on a proposed ranking system, and ways to improve the system dynamics models' quality were discussed.

Characteristics of Type-2 Diabetics Who are Prone to High-Cost Medical Care Expenses by Bayesian Network

Objective: This study aims to determine the characteristics of Type 2 diabetic patients who are more likely to cause high-cost medical expenses using the Bayesian network model. Methods: The 2011-2015 receipt data of Iwamizawa city, Japan were collected from the National Health Insurance Database. From the record, we identified patients with Type 2 diabetes with the following items: age, gender, area, number of days provided medical services, number of diseases, number of medical examinations, annual healthcare expenditures, and the presence or absence of hospitalization. The Bayesian network model was applied to identify the characteristics of the patients, and four observed values were changed using a model for patients who paid at least 3607 USD a year for medical expenses. The changes in the conditional probability of the annual healthcare expenditures and changes in the percentage of patients with high-cost medical expenses were analyzed. Results: After changing the observed value, the percentage of patients with high-cost medical expense reimbursement increased when the following four conditions were applied: the patient "has ever been hospitalized", "had been provided medical services at least 18 days a year", "had at least 14 diseases listed on medical insurance receipts", and "has not had specific health checkups in five years". Conclusions: To prevent an excessive rise in healthcare expenditures in Type 2 diabetic patients, measures against complications and promoting encouragement for them to undergo specific health checkups are considered as effective.

Towards Evaluating Proactive and Reactive Approaches on Reorganizing Human Resources in IoT-Based Smart Hospitals

Hospitals play an important role on ensuring a proper treatment of human health. One of the problems to be faced is the increasingly overcrowded patients care queues, who end up waiting for longer times without proper treatment to their health problems. The allocation of health professionals in hospital environments is not able to adapt to the demands of patients. There are times when underused rooms have idle professionals, and overused rooms have fewer professionals than necessary. Previous works have not solved this problem since they focus on understanding the evolution of doctor supply and patient demand, as to better adjust one to the other. However, they have not proposed concrete solutions for that regarding techniques for better allocating available human resources. Moreover, elasticity is one of the most important features of cloud computing, referring to the ability to add or remove resources according to the needs of the application or service. Based on this background, we introduce Elastic allocation of human resources in Healthcare environments (ElHealth) an IoT-focused model able to monitor patient usage of hospital rooms and adapt these rooms for patients demand. Using reactive and proactive elasticity approaches, ElHealth identifies when a room will have a demand that exceeds the capacity of care, and proposes actions to move human resources to adapt to patient demand. Our main contribution is the definition of Human Resources IoT-based Elasticity (i.e., an extension of the concept of resource elasticity in Cloud Computing to manage the use of human resources in a healthcare environment, where health professionals are allocated and deallocated according to patient demand). Another contribution is a cost-benefit analysis for the use of reactive and predictive strategies on human resources reorganization. ElHealth was simulated on a hospital environment using data from a Brazilian polyclinic, and obtained promising results, decreasing the waiting time by up to 96.4% and 96.73% in reactive and proactive approaches, respectively.

Inequalities in healthcare resources and outcomes threatening sustainable health development in Ethiopia: panel data analysis

OBJECTIVE

To measure inequalities in the distributions of selected healthcare resources and outcomes in Ethiopia from 2000 to 2015.

DESIGN

A panel data analysis was performed to measure inequalities in distribution of healthcare workforce, infrastructure, outcomes and finance, using secondary data.

SETTING

The study was conducted across 11 regions in Ethiopia.

PARTICIPANTS

Regional population and selected healthcare workforce.

OUTCOMES MEASURED

Aggregate Theil and Gini indices, changes in inequalities and elasticity of healthcare resources.

RESULTS

Despite marked inequality reductions over a 16 year period, the Theil and Gini indices for the healthcare resources distributions remained high. Among the healthcare workforce distributions, the Gini index (GI) was lowest for nurses plus midwives (GI=0.428, 95% CI 0.393 to 0.463) and highest for specialist doctors (SPDs) (GI=0.704, 95% CI 0.652 to 0.756). Inter-region inequality was the highest for SPDs (95.0%) and the lowest for health officers (53.8%). The GIs for hospital beds, hospitals and health centres (HCs) were 0.592(95% CI 0.563 to 0.621), 0.460(95% CI 0.404 to 0.517) and 0.409(95% CI 0.380 to 0.439), respectively. The interaction term was highest for HC distributions (47.7%). Outpatient department visit per capita (GI=0.349, 95% CI 0.321 to 0.377) and fully immunised children (GI=0.307, 95% CI 0.269 to 0.345) showed inequalities; inequality in the under 5 years of age mortality rate increased overtime (P=0.048). Overall, GI for government health expenditure (GHE) was 0.596(95% CI 0.544 to 0.648), and the estimated relative GHE share of the healthcare workforce and infrastructure distributions were 46.5% and 53.5%, respectively. The marginal changes in the healthcare resources distributions were towards the advantaged populations.

CONCLUSION

This study revealed high inequalities in healthcare resources in favour of the advantaged populations which can hinder equal access to healthcare and the achievements of healthcare outcomes. The government should strengthen monitoring mechanisms to address inequalities based on the national healthcare standards.