Evaluating the accessibility to healthcare facilities under the Chinese hierarchical diagnosis and treatment system.

An accurate assessment of current healthcare resource allocations is essential to address existing inequities in the hierarchical diagnosis and treatment system introduced in China. The data come from statistical reports of local governments and the developer platform of Amap, a Chinese mobile map. The data were analysed using the hierarchical two-step floating catchment area method. By spatial accessibility analysis, the distribution of accessibility to hierarchical healthcare facilities in Zhongshan City, Guangdong Province was found to be uneven, with clustered high accessibility in the central, north-western and southern parts of the city. To enhance the capacity of healthcare services, the government should allocate healthcare resources rationally to better associate with population densities.

Efficiency of health resource utilisation in primary-level maternal and child health hospitals in Shanxi Province, China: a bootstrapping data envelopment analysis and truncated regression approach.

BACKGROUND: District- and county-level maternal and child health hospitals (MCHHs) are positioned to provide primary maternal and child healthcare in rural and urban areas of China. Their efficiencies and productivity largely affect the equity and accessibility of maternal and child health care. This study aimed to assess the efficiency of district- and county-level MCHHs in China and identify their associated factors. METHODS: Thirty-three district- and 84 county-level MCHHs were selected from Shanxi Province in 2017. At the first stage, bootstrapping data envelopment analysis (DEA) models were established to calculate the technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) of district- and county-level hospitals. At the second stage, the estimated efficiency scores were regressed against external and internal hospital environmental factors by using bootstrap truncated regression to identify their determinants. RESULTS: The average TE, PTE and SE scores for district-level MCHHs were 0.7433, 0.8633 and 0.9335, respectively. All hospitals were found to be weakly efficient, although more than 50% of the hospitals performed with efficient SE (SE scores≥100%). As for county-level MCHHs, their average TE, PTE and SE scores were 0.5483, 0.6081 and 0.9329, respectively. The hospitals with TE and PTE scores less than 0.7 accounted for more than 60%, and no hospital was observed to operate effectively. Truncated regressions suggested that the proportion of health professionals, including doctors, nurses, pharmacists, inspection technician and image technician (district level: ß = 0.57, 95% CI = 0.30-0.85; county level: ß = 0.33, 95% CI = 0.15-0.52), and the number of health workers who received job training (district level: ß = 0.67, 95% CI = 0.26-1.08; county level: ß = 0.34, 95% CI = 0.14-0.54) had a positive association with efficiency scores. The amount of financial subsidy (ß = 0.07, 95% CI = 0.05-0.09) was found to be directly proportional to the productive efficiency of the county-level MCHHs. CONCLUSION: The operational inefficiency of district- and county-level MCHHs in Shanxi Province is severe and needs to be substantially improved, especially in terms of TE and PTE. Hiring additional medical personnel and ensuring the stability of the workforce should be prioritised. The Chinese government must provide sufficient financial subsidy to compensate for service costs.

Evaluation of resource utilization efficiency in obstetrics and gynecology units in China: A three-stage data envelopment analysis of the Shanxi province.

In China, health care resources for expectant mothers and children are still not utilized to full efficiency, with health requirements still not being met. The purpose of this study is to critically examine the efficiency of gynecology and obstetrics hospital (OB/GYN) units in Shanxi province of China, with the overarching objective of exploring methods for improving their efficiency. We employ the three-stage data envelopment analysis (DEA) model to measure the efficiency of 134 OB/GYN units in Shanxi. The results show that the technical efficiency and scale efficiency scores of the sample units were low (0.48 and 0.54, respectively). The efficiency of the OB/GYN units varies by region, city, and county and by type of unit. We conclude that the main reason for the low efficiency of OB/GYN units in Shanxi province lies in the unreasonable scale. The government should, therefore, allocate health resources more reasonably, improving the efficiency of different regions, cities, and counties, as well as different types of OB/GYN units.

General practice for the poor and specialist services for the rich: inequality evidence from a cross-sectional survey on Hangzhou residents, China.

BACKGROUND: Inequalities in health care services are becoming an increasing concern in the world including in China. This study measured the income-related inequalities of residents in Hangzhou of China in access to general practice and specialist care and identified socioeconomic factors associated with such inequalities. METHODS: A cross-sectional questionnaire survey was conducted on 1048 residents in ten urban communities in Hangzhou, China. The percentage and frequency of respondents visiting general practice (GP) and hospital specialist clinics over the past four weeks prior to the survey were estimated. Income-related inequalities in access to these services were measured by the concentration index. Logistic regression and Poisson regression models were established to decompose the contributions of socioeconomic factors (residency, income, education, marital status, and social health insurance) to the inequalities in the probability and frequency of accessing these services, respectively, after adjustment for the needs factors (age, sex and illness conditions). RESULTS: The GP services were in favor of the poor, with a concentration index of - 0.0464 and - 0.1346 for the probability and frequency of GP visits, respectively. In contrast, the specialist services were in favor of the rich, with a concentration index of 0.1258 and 0.1279 for the probability and frequency of specialist visits, respectively. Income is the biggest contributor to the inequalities, except for the frequency of visits to specialists in which education played the greatest role. CONCLUSIONS: Income-related inequalities in GP and specialist care are evident in China. Policy interventions should pay increasing attention to the emergence of a two-tier system, potentially enlarging socioeconomic disparities in health care services.

Hospital volume and outcomes for inpatients with acute myocardial infarction in Shanxi, China: A cross-sectional study.

In this cross-sectional study, we assessed the relationship between hospital volume and clinical outcomes for inpatients with acute myocardial infarction (AMI) in tertiary A hospitals in Shanxi, China (N = 12 931). In-hospital mortality, length of stay (LOS), and total cost were measured. The crude in-hospital mortality rate was 1.69%. Adjusted in-hospital mortality was significantly lower for medium-volume hospitals (odds ratio (OR) = 0.605, 95% confidence interval (CI) = 0.411-0.900) compared with low-volume hospitals. LOS in medium- and high-volume hospitals were 0.915 (95% CI = 0.880-0.951) and 1.069 (95% CI = 1.041-1.098) days longer than in low-volume hospitals, respectively. The cost of inpatients attending low- and high-volume hospitals (OR = 1.180, 95% CI = 1.140-1.221) was higher than that of medium-volume hospitals (OR = 0.897, 95% CI = 0.868-0.926). These results inform health care policy in countries with strained medical resources.

Does Hospital Competition Harm Inpatient Quality? Empirical Evidence from Shanxi, China.

This study aimed to determine whether hospital competition is associated with improved in-hospital mortality in Shanxi, China. We included a total of 46,959 hospitalizations for acute myocardial infarction (AMI) and 44,063 hospitalizations for pneumonia from 2015 to 2017. Hospital competition was measured as Herfindahl⁻Hirschman Index based on the patient predicted flow approach. Two-level random-intercept logistic models were applied to explore the effects of hospital competition on quality for both AMI and pneumonia diagnoses. Hospital competition exerts negative or negligible effects on inpatient quality of care, and the pattern of competition effects on quality varies by specific diseases. While hospital competition is insignificantly correlated with lower AMI in-hospital mortality (odds ratio (OR): 0.94, 95% confidence interval (CI): 0.77⁻1.11), high hospital competition was, in fact, associated with higher in-hospital mortality for pneumonia patients (OR: 1.99, 95% CI: 1.51⁻2.64). Our study suggests that simply encouraging hospital competition may not provide effective channels to improve inpatient quality of health care in China's current health care system.

Bootstrapping data envelopment analysis of efficiency and productivity of county public hospitals in Eastern, Central, and Western China after the public hospital reform.

China implemented the public hospital reform in 2012. This study utilized bootstrapping data envelopment analysis (DEA) to evaluate the technical efficiency (TE) and productivity of county public hospitals in Eastern, Central, and Western China after the 2012 public hospital reform. Data from 127 county public hospitals (39, 45, and 43 in Eastern, Central, and Western China, respectively) were collected during 2012-2015. Changes of TE and productivity over time were estimated by bootstrapping DEA and bootstrapping Malmquist. The disparities in TE and productivity among public hospitals in the three regions of China were compared by Kruskal-Wallis H test and Mann-Whitney U test. The average bias-corrected TE values for the four-year period were 0.6442, 0.5785, 0.6099, and 0.6094 in Eastern, Central, and Western China, and the entire country respectively, with average non-technical efficiency, low pure technical efficiency (PTE), and high scale efficiency found. Productivity increased by 8.12%, 0.25%, 12.11%, and 11.58% in China and its three regions during 2012-2015, and such increase in productivity resulted from progressive technological changes by 16.42%, 6.32%, 21.08%, and 21.42%, respectively. The TE and PTE of the county hospitals significantly differed among the three regions of China. Eastern and Western China showed significantly higher TE and PTE than Central China. More than 60% of county public hospitals in China and its three areas operated at decreasing return scales. There was a considerable space for TE improvement in county hospitals in China and its three regions. During 2012-2015, the hospitals experienced progressive productivity; however, the PTE changed adversely. Moreover, Central China continuously achieved a significantly lower efficiency score than Eastern and Western China. Decision makers and administrators in China should identify the causes of the observed inefficiencies and take appropriate measures to increase the efficiency of county public hospitals in the three areas of China, especially in Central China.

Insurance status, inhospital mortality and length of stay in hospitalised patients in Shanxi, China: a cross-sectional study.

OBJECTIVES: To determine insurance-related disparities in hospital care for patients with acute myocardial infarction (AMI), heart failure (HF) and pneumonia. SETTING AND PARTICIPANTS: A total of 22 392 patients with AMI, 8056 patients with HF and 17 161 patients with pneumonia were selected from 31 tertiary hospitals in Shanxi, China, from 2014 to 2015 using the International Classification of Diseases, Tenth Revision codes. Patients were stratified by health insurance status, namely, urban employee-based basic medical insurance (UEBMI), urban resident-based basic medical insurance (URBMI), new cooperative medical scheme (NCMS) and self-payment. OUTCOME MEASURES: Inhospital mortality and length of stay (LOS). RESULTS: The highest unadjusted inhospital mortality rate was detected in NCMS patients independent of medical conditions (4.7%, 4.4% and 11.1% for AMI, HF and pneumonia, respectively). The lowest unadjusted inhospital mortality rate and the longest LOS were observed in UEBMI patients. After controlling patient-level and hospital-level covariates, the adjusted inhospital mortality was significantly higher for NCMS and self-payment among patients with AMI, for NCMS among patients with HF and for URBMI, NCMS and self-payment among patients with pneumonia compared with UEBMI. The LOS of the URBMI, NCMS and self-payment groups was significantly shorter than that of the UEBMI group. CONCLUSION: Insurance-related disparities in hospital care for patients with three common medical conditions were observed in this study. NCMS patients had significantly higher adjusted inhospital mortality and shorter LOS compared with UEBMI patients. Policies on minimising the disparities among different insurance schemes should be established by the government.

Selecting the optimal healthcare centers with a modified P-median model: a visual analytic perspective.

BACKGROUND: In a conventional P-median model, demanding points are likely assigned to the closest supplying facilities, but this method exhibits evident limitations in real cases. METHODS: This paper proposed a modified P-median model in which exact and approximate strategies are used. The first strategy aims to enumerate all of the possible combinations of P facilities, and the second strategy adopts simulated annealing to allocate resources considering capacity constraint and spatial compactness constraint. These strategies allow us to choose optimal locations by applying visual analytics, which is rarely employed in location allocation planning. RESULTS: This model is applied to a case study in Henan Province, China, where three optimal healthcare centers are selected from candidate cities. First, the weighting factor in spatial compactness constraint is visually evaluated to obtain a plausible spatial pattern. Second, three optimal healthcare centers, namely, Zhengzhou, Xinxiang, and Nanyang, are identified in a hybrid transportation network by performing visual analytics. Third, alternative healthcare centers are obtained in a road network and compared with the above solution to understand the impacts of transportation network types. CONCLUSIONS: The optimal healthcare centers are visually detected by employing an improved P-median model, which considers both geographic accessibility and service quality. The optimal solutions are obtained in two transportation networks, which suggest high-speed railways and highways play a significant role respectively.