Dataset Information

Understanding Healthcare Utilization In China Through The Andersen Behavioral Model: Review Of Evidence From The China Health And Nutrition Survey.

ABSTRACT: Introduction:Factors influencing healthcare utilization in China have been frequently analyzed and discussed from various angles, based upon different objectives. However, few studies have attempted to categorize and summarize key determinants of healthcare utilization in China. Methods:To fill this gap, we reviewed all empirical studies that made use of data from the China Health and Nutrition Survey (CHNS), a longitudinal survey covering nine Chinese provinces for nearly three decades. The review was guided by Andersen's behavioral model, a conceptual framework widely used to analyze determinants of healthcare utilization. Results:Our review discovered many strong and consistent predictors of healthcare utilization at the individual level, including predisposing factors (e.g., marriage status and education), enabling factors (e.g., income and wealth), and need factors (e.g., illness severity and health status); in contrast, contextual factors (e.g., employment rates and population health indices) have rarely been examined. Our review also revealed a few factors whose impacts differ from expectations in many studies (e.g., employment status and health insurance coverage). While several factors explored in the reviewed studies (e.g., urbanization and industrialization) are not part of Andersen's model, some factors specified in the model (e.g., values and knowledge about health and health services) remain unexplored in the context of China. Conclusion:Individual-level factors received much more attention than contextual-level factors in the reviewed studies. It leads to an inadequate understanding of the roles played by contextual factors. Among the individual-level factors that have been extensively examined, enabling variables affect healthcare utilization more than predisposing and need factors.

SUBMITTER: Zhang S

PROVIDER: S-EPMC6857654 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Understanding Healthcare Utilization In China Through The Andersen Behavioral Model: Review Of Evidence From The China Health And Nutrition Survey.

Zhang Shu S Chen Qihui Q Zhang Bo B

Risk management and healthcare policy 20191111

<h4>Introduction</h4>Factors influencing healthcare utilization in China have been frequently analyzed and discussed from various angles, based upon different objectives. However, few studies have attempted to categorize and summarize key determinants of healthcare utilization in China.<h4>Methods</h4>To fill this gap, we reviewed all empirical studies that made use of data from the China Health and Nutrition Survey (CHNS), a longitudinal survey covering nine Chinese provinces for nearly three d ...[more]

PMID: 31807101

Similar Datasets

Project description:BackgroundA growing need and focus on preventing and controlling the diseases and promoting a healthier lifestyle is more evident at global, regional, and national levels. In this respect, it is well-known the positive association between physical activity and population's health, but also its negative association with the demand of healthcare, which could lead to lower spending on healthcare systems. In France, a lack of physical activity, a high prevalence of sedentary behaviours, and a continuous deterioration of these behaviours are observed since 2006. Therefore, promoting and increasing physical activities could contribute to major societal issues. Within this context, the study aims to analyse how the use of different healthcare services are related to physical activity in a nationally representative sample of French population.MethodsThe data used was retrieved from the second wave of the EHIS-ESPS 2014. The relationship between physical activity and healthcare utilization, controlled by a set of socioeconomic, demographic, and health behaviour factors, was explored both at the level of the entire population and separately for two age groups (less than 65 years, 65 years and older), employing probit and recursive multivariate probit models.ResultsOur findings underline that the relation between healthcare utilization and physical activity depends on the type of healthcare services and age group. In this respect, only among adult respondents, we observe a significant negative association between physical activity and prescribed medicines consumption and day hospitalization, while preventive services use is positively related to physical activity. Common to both age groups, the positive association of physical activity with general physician services and non-prescribed medicines reveal that moderately and highly active adults and elders may be more health conscious and therefore may seek referrals to generalist and other prevention measures more frequently than their inactive counterparts. This explanation is also sustained by the negative association between physical activity and overnight hospitalization or home healthcare services.ConclusionsThis study highlights the double role of physical activity on health as preventive measure and treatment and thus support the implementation of public health policies aimed at increasing the level of physical activity in French population.

Project description:BackgroundChina established the Tiered-network Healthcare Delivery System (THDS) in 2015 to address the disproportionate number of patients attending tertiary hospitals relative to primary- or secondary-care institutions. Although the reported number of outpatients visiting tertiary hospitals is slowly decreasing, numerous patients choose to visit them regardless of their disease's severity. To effectively implement the THDS, this article explored the relationship between patients' sociodemographic and belief characteristics and their healthcare-seeking behavioral decision-making in China.MethodsData obtained through questionnaires were analyzed using decision tree and logistic regression models to explore outpatients' characteristics and medical decision-making using comprehensive feature data. Moreover, further statistical analyses were conducted on the outpatient data obtained from the regional population health platform in Jiaxing, China.ResultsThe decision tree model revealed that whether outpatients have medical insurance is the primary factor guiding their healthcare-seeking behaviors, with those without medical insurance more likely to choose primary or secondary hospitals to treat minor diseases. For those with medical insurance, profession is the main factor, with industrial workers more inclined to choose primary or secondary hospitals for minor diseases. The logistic regression analyses revealed that outpatients without insurance and who were not freelancers or individual owners were more likely to choose primary or secondary hospitals for minor diseases. Further statistical analysis of the data from the Jiaxing population health platform showed that, for minor or general diseases, outpatients without medical insurance and employed as farmers tended to choose primary and secondary hospitals over tertiary hospitals.ConclusionThe three analyses yielded consistent results: in China, medical insurance and patients' profession are the most important factors guiding outpatients' healthcare-seeking behaviors. Accordingly, we propose that the government should focus on economic reforms to increase outpatients' visits to primary and secondary hospitals and diagnosis-related groups' payment of medical insurance to decrease the admittance of patients with minor diseases in large tertiary hospitals. Meanwhile, the government should correct patients' belief prejudice about selecting hospitals through corresponding publicity.

Dataset Information

Understanding Healthcare Utilization In China Through The Andersen Behavioral Model: Review Of Evidence From The China Health And Nutrition Survey.

Publications

Understanding Healthcare Utilization In China Through The Andersen Behavioral Model: Review Of Evidence From The China Health And Nutrition Survey.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets