Does supplemental private health insurance impact health care utilization and seeking behavior of residents covered by social health insurance? Evidence from China National Health Services Survey.

BACKGROUND: Supplemental private health insurance (PHI) plays a crucial role in complementing China's social health insurance (SHI). However, the effectiveness of incorporating PHI as supplementary coverage lacks conclusive evidence regarding its impact on healthcare utilization and seeking behavior among SHI-covered individuals. Therefore, investigating the effects of supplementary PHI on health care utilization and seeking behavior of residents covered by social health insurance is essential to provide empirical evidence for informed decision-making within the Chinese healthcare system. METHODS: Data from the 2018 China National Health Services Survey were analyzed to compare outpatient and inpatient healthcare utilization and choices between PHI purchasers and non-purchasers across three SHI schemes: urban employee-based basic medical insurance (UEBMI), urban resident-based basic medical insurance (URBMI), and the new rural cooperative medical scheme (NRCMS). Using the Andersen Healthcare Services Utilization Behavior Model as the theoretical framework,binary logistic regression and multinomial logistic regression (MNL) models were employed to assess the impact of PHI on healthcare utilization and provider preferences. RESULTS: Among UEBMI, URBMI, and NRCMS participants with PHI, outpatient visit rates were 17.9, 19.8, and 21.7%, and inpatient admission rates were 12.4, 9.9, and 12.9%, respectively. Participants without PHI exhibited higher rates for outpatient visits (23.6, 24.3, and 25.6%) and inpatient admissions (15.2, 12.8, and 14.5%). Binomial logistic regression analyses revealed a higher probability of outpatient visits and inpatient admissions among UEBMI participants with PHI (p < 0.05). NRCMS participants with PHI showed a lower probability of outpatient visits but a higher probability of inpatient admissions (p < 0.05). Multinomial logistic regression indicated that NRCMS participants with PHI were more likely to choose higher-level hospitals, with a 17% increase for county hospitals and 27% for provincial or higher-level hospitals compared to primary care facilities. CONCLUSION: The findings indicate that the possession of PHI correlated with increased utilization of outpatient and inpatient healthcare services among participants covered by UEBMI. Moreover, for participants under the NRCMS, the presence of PHI is linked to a proclivity for seeking outpatient care at higher-level hospitals and heightened utilization of inpatient services. These results underscore the nuanced influence of supplementary PHI on healthcare-seeking behavior, emphasizing variations across individuals covered by distinct SHI schemes.

Improvement of Cancer Prevention and Control: Reflection on the Role of Emerging Information Technologies.

Cancer has become an important public health problem affecting the health of Chinese residents, as well as residents all over the world. With the improvement of cancer prevention and treatment, the growth of the mortality rate of cancers has slowed down gradually, but the incidence rate is still increasing rapidly, and cancers still impose heavy disease and economic burdens. Cancer screening and early cancer diagnosis and treatment are important ways to reduce the burden of cancer-related diseases. At present, various projects for early cancer diagnosis and treatment have been implemented in China. With the expansion of the coverage of these projects, the problems related to project implementation, operation, and management have emerged gradually. In recent years, emerging information technologies have been applied in the field of health and have facilitated health management and clinical decision-making. Meanwhile, China announced multiple policies to encourage and promote the application of information technologies in the field of health. Therefore, combined with the analysis of major problems in cancer prevention and control projects, this paper probes into how to apply information technologies such as biological information mining, artificial intelligence, and electronic information collection technology to various stages of cancer prevention and control. Information technologies realize the integrated management of prevention and control processes, for example, mobilization and preliminary identification, high-risk assessment, clinical screening, clinical diagnosis and treatment, tracking and follow-up, and biological sample management of high-risk groups, and promote the efficient implementation of cancer prevention and control projects in China.

Case fatality rates of COVID-19 during epidemic periods of variants of concern: A meta-analysis by continents.

OBJECTIVES: To calculate the case fatality rates (CFR) of COVID-19 during epidemic periods of different variants of concern (VOC) by continents. METHODS: We systematically searched five authoritative databases (Web of Science, PubMed, Embase, Cochrane Library, and MedRxiv) for epidemiological studies on the CFR of COVID-19 published between January 1, 2020, and March 31, 2023. After identifying the epidemic trends of variants, we used a random-effects model to calculate the pooled CFRs during periods of different VOCs. This meta-analysis was conducted following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and registered with PROSPERO (CRD42023431572). RESULTS: There were variations in the CFRs among different variants of COVID-19 (Alpha: 2.62%, Beta: 4.19%, Gamma: 3.60%, Delta: 2.01%, Omicron: 0.70%), and disparities in CFRs also existed among continents. On the whole, the CFRs of COVID-19 in Europe and Oceania were slightly lower than in other continents. There was a statistically significant association between the variant, HDI value, age distribution, coverage of full vaccination of cases, and the CFR. CONCLUSIONS: The CFRs of COVID-19 varied across the epidemic periods of different VOCs, and disparities existed among continents. The CFR value reflected combined effects of various factors within a certain context. Caution should be exercised when comparing CFRs due to disparities in testing capabilities and age distribution among countries, etc.