Measuring the acceptability of EQ-5D-3L health states for different ages: a new adaptive survey methodology

Background Acceptable health and sufficientarianism are emerging concepts in health resource allocation. We defined acceptability as the proportion of the general population who consider a health state acceptable for a given age. Previous studies surveyed the acceptability of health problems separately per EQ-5D-3L domain, while the acceptability of health states with co-occurring problems was barely explored. Objective To quantify the acceptability of 243 EQ-5D-3L health states for six ages from 30 to 80 years: 1458 health state–age combinations (HAcs), denoted as the acceptability set of EQ-5D-3L. Methods In 2019, an online representative survey was conducted in the Hungarian general population. We developed a novel adaptive survey algorithm and a matching statistical measurement model. The acceptability of problems was evaluated separately per EQ-5D-3L domain, followed by joint evaluation of up to 15 HAcs. The selection of HAcs depended on respondents’ previous responses. We used an empirical Bayes measurement model to estimate the full acceptability set. Results 1375 respondents (female: 50.7%) were included with mean (SD) age of 46.7 (14.6) years. We demonstrated that single problems that were acceptable separately for a given age were less acceptable when co-occurring jointly (p < 0.001). For 30 years of age, EQ-5D-3L health states of ‘11112’ (11.9%) and ‘33333’ (1%), while for 80 years of age ‘21111’ (93.3%) and ‘33333’ (7.4%) had highest and lowest acceptability (% of population), respectively. Conclusion The acceptability set of EQ-5D-3L quantifies societal preferences concerning age and disease severity. Its measurement profiles and potential role in health resource allocation needs further exploration.

Fairness of the Distribution of Public Medical and Health Resources

The fairness of health services is an important indicator of the World Health Organization's performance evaluation of health services, and the fairness of health resource allocation is the prerequisite for the fairness of health services. The research in this article aims to explore how to use health and medical resources fairly and effectively to allocate health resources in different fields, populations and projects, in order to achieve the maximization of social and economic benefits of health and medical resources. In the study of the distribution and equity of public health and medical resources, we comprehensively apply Gini coefficient, Theil index, Lorentz curve and difference index, based on the theory of health resource allocation and the theory of health equity, the province's health service resources have been researched and evaluated, combined with regional health planning theories and public health theories, a variety of scientific methods were used to analyze community health service resources at all levels across the country. At the same time, we reviewed the journal literature about the treatment of patients and children, and analyzed the patients admitted to medical institutions in various regions. The research in this paper found that from 2016 to 2020, the Gini coefficient of the province's health institutions according to population distribution has been fluctuating between 0.14 and 0.17. During this 5-year period, the Gini coefficient of the distribution of medical and health expenditures by population shows a downward trend year by year. From 2019, reach below 0.1, this shows that the fairness of the allocation of health resources according to population has a clear trend of improvement.

Equity and Efficiency of Medical and Health Resource Allocation in Western China Based on Health Resources Agglomeration Degree and Malmquist Index

Background: There is unequal distribution and low utilization efficiency of medical and health resources among regions in China for regional inequality social and economic development. The social and economic development in western China is relatively backward nationwide. The quantity and quality of medical and health resources have become a social problem in western China. This study aims to evaluate the equity and efficiency of health resource allocation in western China. Methods: The research data are extracted from China Statistical Yearbook ( 2009 – 2019 ). We choose the health resource agglomeration degree ( HRAD ) theory and Malmquist index to evaluate the equity and efficiency of health resource allocation in western China. The HRAD shows the impact of demographic and geographic factors on health resource aggregation. Results: From the latest data in 2019, the equity of medical and health resources allocation based on geographical area in Inner Mongolia, Tibet, Qinghai and Xinjiang is poor. The equity of medical and health resources allocation based on population allocation in Yunnan, Tibet, Gansu, Qinghai, Ningxia and Xinjiang is poor. From 2009 to 2019, the equity of health resource allocation in western China are poor nationwide. The total factor productivity of Tibet, Qinghai, Ningxia and Xinjiang was less than 1, which were 0.994, 0.984, 0.974 and 0.994, respectively. The allocation of medical and health resources in western China is unfair. Conclusion: The government should pay attention to the horizontal flow of medical and health resources when investing in medical and health resources. Population and geographical factors should be taken into account when allocating health resources. The total factor productivity in the western region is greatly affected by the technological progress rate. We should increase investment in medical and health technology, and effectively optimize the equity and efficiency of medical and health resource allocation.

Equity of Health Resources Allocation in Rural Guangxi from 2016 to 2019: An Empirical Analysis

Background: Since 2009, the main task of the new health reform in China is to increase the equity of health resources allocation in primary health care institutions. Health policies and strategies have been established to increase the capacity of PHC services, with improved equity as the most important goal. The objective of this study is to analyze the status quo and equity of health resources distribution in rural Guangxi from 2016 to 2019.Methods: Descriptive statistics analysis was used to analyze the status quo of health resource allocation in rural health center in Guangxi from 2016 to 2019. Lorenz curve, Gini coefficient and Theil index were used to evaluate the equity of health resource allocation in rural health center in Guangxi from 2016 to 2019, from three dimensions of population, geography and economy. Results: From 2016 to 2019, the total amount of health resources in rural health center in Guangxi was increased, but the professional title and education background of health workers is still low. In 2019, the Gini coefficient was 0.085-0.217 geographically, 0.080-0.367 demographically and 0.135-0.340 economically. The total Theil index was 013-0.211, and the majority of the contribution rate of within regions was greater than the between regions. Conclusion: From 2016 to 2019, the distribution of health resources in rural Guangxi was uneven among regions, and with great differences within regions.

Health Resource Allocation in Western China from 2014 to 2018

Background: Health equity has persistently been a global concern. As a basic material guarantee to ensure health equity, how to allocate the health resources in a fair and reasonable way has always been one of the research hotspots. The coronavirus 2019 (COVID-19) pandemic has also prompted a rethinking of the topic. Based on the previous research, western China is a relatively backward region, coupled with climate, geography, and other factors, which leading the inconvenient transportation and difficult resource allocation. However, the fairness of health resource allocation in western China has received relatively little attention. Methods: Lorentz curve, Gini coefficient and Theil index were used to analyse the health resources allocation in the western China. The indexes include number of beds, medical (assistant) practitioners, registered nurses from 2014 to 2018 through population and geography dimensions. Results: The total health resources shows an increasing trend from 2014 to 2018; The Lorentz curve in the population dimension had a smaller curvature than in the geography dimension. The Gini coefficients for health resources in the population dimension were ranged from 0.057 to 0.129, and in geography dimension the Gini coefficients ranged between 0.605 and 0.647. This shows that the distribution of Health resources is fair basing on population dimension. Furthermore, in two dimensions, the intra-group contribution rate of the Theil index was higher than in the inter-group, and the allocation of practicing (assistant) practitioners and registered nurses show a significant inequity in intra-group. This result indicated that the inequity of health resources allocation were mainly came from intra-group, namely the provinces (autonomous regions and municipalities) in western China.Conclusions: In recent years, China’s various measures have improved the total amount of health resources and its equity of health resources in western China. However, the fairness of the health resources allocation in western China were remind poor. Although the fairness of human resources allocation has been alleviated in population dimension, the inequity of human resources distribution in provinces (autonomous regions and municipalities) are still obvious. In addition, the accessibility of health resources in western China must be further improved.

Equity of Health Resources Allocation in Rural Guangxi from 2016 to 2019: An Empirical Analysis

Background: Since 2009, the main task of the new health reform in China is to increase the equity of health resources allocation in primary health care institutions. Health policies and strategies have been established to increase the capacity of PHC services, with improved equity as the most important goal. The objective of this study is to analyze the status quo and equity of health resources distribution in rural Guangxi from 2016 to 2019.Methods: Descriptive statistics analysis was used to analyze the status quo of health resource allocation in rural health center in Guangxi from 2016 to 2019. Lorenz curve, Gini coefficient and Theil index were used to evaluate the equity of health resource allocation in rural health center in Guangxi from 2016 to 2019, from three dimensions of population, geography and economy. Results: From 2016 to 2019, the total amount of health resources in rural health center in Guangxi was increased, but the professional title and education background of health workers is still low. In 2019, the Gini coefficient was 0.085-0.217 geographically, 0.080-0.367 demographically and 0.135-0.340 economically. The total Theil index was 013-0.211, and the majority of the contribution rate of within regions was greater than the between regions. Conclusion: From 2016 to 2019, the distribution of health resources in rural Guangxi was uneven among regions, and with great differences within regions.

Taiwan makes itself a COVID-19 safe zone without draconian measures: lessons and caveats

Purpose The coronavirus disease 2019 (COVID-19) pandemic has helped Taiwan gain widespread recognition and commendation. Taiwan's low infection rate is praiseworthy not merely because it was once considered a high-risk region but because it has weathered the COVID-19 storm without resorting to draconian measures. The purpose of this paper is thus an effort to understand and explain how Taiwan has been able to achieve a fine balance between disease containment and everyday life. Design/methodology/approach According to the COVID-19 Government Response Event Dataset, Taiwan’s actions focus mainly on the management of health resource allocation, external border restrictions, quarantine of high-risk cases and the establishment of a centralized crisis task force. On this basis, the authors highlight and discuss the critical factors for Taiwan’s success against COVID-19. Caveats are also detailed to caution some aspects of the lessons to be drawn from it. Findings Setting clear goals, effective leadership, active community participation and innovative solutions are four pillars of Taiwan’s success against COVID-19. The island believes that once stringent border controls are strictly executed, virus-free citizens can relax inside. However, those who would like to learn from Taiwan’s experience should be mindful of the likelihood of asymptomatic spread of the disease as well as the unique geographical and social characteristics that contribute to Taiwan’s approach to COVID-19. Originality/value The authors’ analysis of Taiwan adds anecdotes to the scholarly discussion on public health emergency management, suggesting that anti-COVID-19 policy would get its intended outcomes only if government leaders and community stakeholders collaborate to set clear goals ahead and implement them with innovative solutions.

Differences in regional distribution and inequality in health-resource allocation on institutions, beds, and workforce: a longitudinal study in China

Background The distribution of health-care resources is foundational to achieving fairness and having access to health service. China and its local Shanghai’s government have implemented measures to allocate health-care resources with the equity as one of the major goals since 2009-health-care reform. The aim of this study was to analyze differences in regional distribution and inequality in health-resource allocation on institutions, beds, and workforce in Shanghai over 7 years. Methods The study was conducted using 2010–2016 data to analyze health-resource allocation on institutions, beds, and workforce in Shanghai, China. The annual growth rate (AGR) was used to evaluate the time trends of health-care resource from 2010 to 2016, and Theil index was calculated to measure inequality of five indicators of health-care resource allocation during this study period. Results All quantities of health-care resources per 1000 people increased across Shanghai districts from 2010 to 2016. Compared with suburban districts, the central districts had higher ratios on five health-care resource indicators, and faster average growth in the bed and nurse indicator. The Theil of the indicators, except for doctors in hospitals, all exhibited downward time trends. Conclusions Regional difference between urban and rural areas and inequality between institution and workforce, especially for doctors, still existed. Some targeted measures including but not limited to income raising, facilitation of transportation conditions, investment of more fiscal funds, enhancement of health-care service provision for rural residents should be fully considered to narrow resource distribution gap between urban and rural districts and mitigate the inequality of health-care resource allocation.

High-resolution age-specific mapping of the two-week illness prevalence rate based on the National Health Services Survey and geostatistical analysis: a case study in Guangdong province, China

Background The two-week illness prevalence rate is an important and comparable indicator of health service needs. High-spatial-resolution, age-specific risk mapping of this indicator can provide valuable information for health resource allocation. The age-prevalence relationships may be different among areas of the study region, but previous geostatistical models usually ignored the spatial-age interaction. Methods We took Guangdong province, the province with the largest population and economy in China, as a study case. We collected two-week illness data and other potential influencing predictors from the fifth National Health Services Survey in 2013 and other open-access databases. Bayesian geostatistical binary regression models were developed with spatial-age structured random effect, based on which, high-resolution, age-specific two-week illness prevalence rates, as well as number of people reporting two-week illness, were estimated. The equality of health resource distribution was further evaluated based on the two-week illness mapping results and the health supply data. Results The map across all age groups revealed that the highest risk was concentrated in the central (i.e., Pearl River Delta) and northern regions of the province. These areas had a two-week illness prevalence > 25.0%, compared with 10.0–20.0% in other areas. Age-specific maps revealed significant differences in prevalence between age groups, and the age-prevalence relationships also differed across locations. In most areas, the prevalence rates decrease from age 0 to age 20, and then increase gradually. Overall, the estimated age- and population-adjusted prevalence was 16.5% [95% Bayesian credible interval (BCI): 14.5–18.6%], and the estimated total number of people reporting illness within the two-week period was 17.5 million (95% BCI: 15.5–19.8 million) in Guangdong Province. The Lorenz curve and the Gini coefficient (resulted in 0.3526) showed a moderate level of inequality in health resource distribution. Conclusions We developed a Bayesian geostatistical modeling framework with spatial-age structured effect to produce age-specific, high-resolution maps of the two-week illness prevalence rate and the numbers of people reporting two-week illness in Guangdong province. The methodology developed in this study can be generalized to other global regions with available relevant survey data. The mapping results will support plans for health resource allocation.

Translating evidence into practice: a longitudinal qualitative exploration of allied health decision-making

Background Health policy and management decisions rarely reflect research evidence. As part of a broader randomized controlled study exploring implementation science strategies we examined how allied health managers respond to two distinct recommendations and the evidence that supports them. Methods A qualitative study nested in a larger randomized controlled trial. Allied health managers across Australia and New Zealand who were responsible for weekend allied health resource allocation decisions towards the provision of inpatient service to acute general medical and surgical wards, and subacute rehabilitation wards were eligible for inclusion. Consenting participants were randomized to (1) control group or (2) implementation group 1, which received an evidence-based policy recommendation document guiding weekend allied health resource allocation decisions, or (3) implementation group 2, which received the same policy recommendation document guiding weekend allied health resource allocation decisions with support from a knowledge broker. As part of the trial, serial focus groups were conducted with a sample of over 80 allied health managers recruited to implementation group 2 only. A total 17 health services participated in serial focus groups according to their allocated randomization wave, over a 12-month study period. The primary outcome was participant perceptions and data were analysed using an inductive thematic approach with constant comparison. Thematic saturation was achieved. Results Five key themes emerged: (1) Local data is more influential than external evidence; (2) How good is the evidence and does it apply to us? (3) It is difficult to change things; (4) Historically that is how we have done things; and (5) What if we get complaints? Conclusions This study explored implementation of strategies to bridge gaps in evidence-informed decision-making. Results provide insight into barriers, which prevent the implementation of evidence-based practice from fully and successfully occurring, such as attitudes towards evidence, limited skills in critical appraisal, and lack of authority to promote change. In addition, strategies are needed to manage the risk of confirmation biases in decision-making processes. Trial registration This trial is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR) (ACTRN12618000029291). Universal Trial Number (UTN): U1111-1205-2621.