Associations of Annual Hospital and Surgeon Volume with Patient Outcomes After Gastrectomy: A Systematic Review and Meta-analysis.

BACKGROUND: Procedural volume is an important determinant of outcomes in cancer surgery. There is a lack of a comprehensive and updated assessment of hospital and surgeon volumes in relation to short- and long-term outcomes after gastrectomy for cancer. METHODS: The PubMed and Embase databases were searched on January 2021. We conducted meta-analyses and meta-regressions assuming a random effects model to assess the associations of procedural volumes with outcomes after gastrectomy. Effect sizes included hazard ratios (HRs), odds ratios (ORs), and standardized mean differences (SMDs). Heterogeneity was evaluated with the I2 statistic and explored by subgroup analyses. The risk of publication bias, risk of bias, and certainty of evidence were also assessed. RESULTS: We identified 53 primary publications on the effect of hospital (n = 48) or surgeon (n = 11) volume on 11 gastrectomy outcomes. Patients operated on in high-volume centers had better overall survival (HR 0.82, 95% confidence interval [CI] 0.75-0.90), lower short-term mortality (OR 0.66, 95% CI 0.58-0.75), more adequate lymphadenectomy (OR 2.14, 95% CI 1.76-2.59), and shorter length of stay (SMD - 0.08, 95% CI - 0.12 to - 0.04). The meta-analysis showed no significant associations of hospital volume with surgical complications, R0 or negative margin resection, or disease-free survival (all p > 0.05). A higher surgeon volume was associated with lower 30-day mortality (OR 0.94, 95% CI 0.90-0.97). CONCLUSIONS: The current study suggested with high confidence that gastric cancer patients operated on in high-volume centers had better overall survival. Centralization of gastrectomy in high-volume centers might lead to an overall improvement in other outcomes, but more studies, especially on surgeon volume, are needed.

Associations of centralization with health care quality for gastric cancer patients receiving gastrectomy in China.

OBJECTIVE: Limited evidence is available regarding the associations of centralization with gastric cancer patients' quality of care in high surgical volume settings. The current study aimed to explore the effects of hospital volume and the Herfindahl-Hirschman index (HHI) on in-hospital mortality, total cost, and length of stay for Chinese gastrectomy patients in a nationwide database. METHODS: We extracted data on gastrectomy for gastric cancer from the Hospital Quality Monitoring System Database between 2013 and 2018. Hospital volume was divided into 4 quartiles: low (1-83 cases per year), medium (84-238 cases), high (239-579 cases), and very high (580-1,193 cases). The HHI was divided into 3 categories: highly concentrated (>2,500), moderately concentrated (1,500-2,500), and unconcentrated (<1,500). We used mixed-effects models to analyze the data while accounting for data clustering. RESULTS: We analyzed 125,683 patients in 515 institutions. In the multivariable analyses, hospital volume was significantly associated with in-hospital mortality [medium vs. low: odds ratio (OR)=0.61, 95% confidence interval (95% CI)=0.43-0.84, P=0.003; high: OR=0.57, 95% CI=0.38-0.87, P=0.009; and very high: OR=0.33, 95% CI=0.18-0.61, P<0.001) and length of stay (highvs. low: ß=-0.036, 95% CI=-0.071--0.002, P=0.039) but not with total cost. Hospitals located in unconcentrated provinces had higher in-hospital mortality (OR=1.52, 95% CI=1.03-2.26, P=0.036) and longer lengths of stay (ß=0.024, 95% CI=0.001-0.047, P=0.041) than hospitals located in highly concentrated provinces. CONCLUSIONS: Centralization of gastrectomy, measured by hospital volume and the HHI, was associated with decreased in-hospital mortality and shortened length of stay without increasing total cost. These results support the strategy of centralizing gastrectomy in high-volume settings.

[Determinants of household healthcare expenditure of rural floating population in Beijing: a Tobit model approach].

OBJECTIVE: To explain the household healthcare expenditure among the rural floating population in Beijing and analyze the determinants of a household total healthcare consumption. METHODS: The data came from the special investigation about rural floating population in Beijing which is part of The Fourth National Health Service Investigation of China. A total of 4 698-native rural migrants (2,728 families) in Beijing were chosen as subjects and a Tobit model was used to analyze the data. Base on the censored characteristics, we use the censored least absolute deviations (CLAD) method to estimate the parameters. RESULTS: Compared with the general urban population, the population under investigation has a high proportion of male and unmarried, but low educated group of young people. The average household healthcare expenditure per month was 21.26 Yuan, and about 74% of the households had made no healthcare expenditure 3 months preceding the survey. The household healthcare expenditure was influenced by the household's education level, household's income level, household size, Engel's coefficient, head's choice of medical institutions and so on. CONCLUSION: The level of household healthcare expenditure is low with the determinants in the floating population, such as the household's economic circumstances and so on. We should make and develop relevant policies and improve the healthcare utilization of the floating population.

Hospitals' responsibility in response to the threat of infectious disease outbreak in the context of the coronavirus disease 2019 (COVID-19) pandemic: Implications for low- and middle-income countries.

The WHO declared the coronavirus disease 2019 (COVID-19) outbreak as a public health emergency of international concern on January 30, 2020, and then a pandemic on March 11, 2020. COVID-19 affected over 200 countries and territories worldwide, with 25,541,380 confirmed cases and 852,000 deaths associated with COVID-19 globally, as of September 1, 2020.1 While facing such a public health emergency, hospitals were on the front line to deliver health care and psychological services. The early detection, diagnosis, reporting, isolation, and clinical management of patients during a public health emergency required the extensive involvement of hospitals in all aspects. The response capacity of hospitals directly determined the outcomes of the prevention and control of an outbreak. The COVID-19 pandemic has affected almost all nations and territories regardless of their development level or geographic location, although suitable risk mitigation measures differ between developing and developed countries. In low- and middle-income countries (LMICs), the consequences of the pandemic could be more complicated because incidence and mortality might be associated more with a fragile health care system and shortage of related resources.2, 3 As evidenced by the situation in Bangladesh, India, Kenya, South Africa, and other LMICs, socioeconomic status (SES) disparity was a major factor in the spread of disease, potentially leading to alarmingly insufficient preparedness and responses in dealing with the COVID-19 pandemic.4 Conversely, the pandemic might also bring more unpredictable socioeconomic and long-term impacts in LMICs, and those with lower SES fare worse in these situations. This review aimed to summarize the responsibilities of and measures taken by hospitals in combatting the COVID-19 outbreak. Our findings are hoped to provide experiences, as well as lessons and potential implications for LMICs.