Medical expenditure and its influencing factors of patients with hypertension in Shanxi Province, China: a study based on 'System of Health Accounts 2011' and multiple-layer perceptron neural network

Influencing factors of hospitalization cost of hypertension patients in traditional Chinese medicine hospitals

Objectives

This study aimed to analyze the influencing factors of hospitalization cost of hypertensive patients in TCM (traditional Chinese medicine, TCM) hospitals, which can provide a scientific basis for hospitals to control the hospitalization cost of hypertension.

Methods

In this study, 3,595 hospitalized patients with a primary diagnosis of tertiary hypertension in Tianshui City Hospital of TCM, Gansu Province, China, from January 2017 to June 2022, were used as research subjects. Using univariate analysis to identify the relevant variables of hospitalization cost, followed by incorporating the statistically significant variables of univariate analysis as independent variables in multiple linear regression analysis, and establishing the path model based on the results of the multiple linear regression finally, to explore the factors influencing hospitalization cost comprehensively.

Results

The results showed that hospitalization cost of hypertension patients were mainly influenced by length of stay, age, admission pathways, payment methods of medical insurance, and visit times, with length of stay being the most critical factor.

Conclusion

The Chinese government should actively exert the characteristics and advantages of TCM in the treatment of chronic diseases such as hypertension, consistently optimize the treatment plans of TCM, effectively reduce the length of stay and steadily improve the health literacy level of patients, to alleviate the illnesses pain and reduce the economic burden of patients.

Health care costs of cardiovascular disease in China: a machine learning-based cross-sectional study

Background

Cardiovascular disease (CVD) causes substantial financial burden to patients with the condition, their households, and the healthcare system in China. Health care costs for treating patients with CVD vary significantly, but little is known about the factors associated with the cost variation. This study aims to identify and rank key determinants of health care costs in patients with CVD in China and to assess their effects on health care costs.

Methods

Data were from a survey of patients with CVD from 14 large tertiary grade-A general hospitals in S City, China, between 2018 and 2020. The survey included information on demographic characteristics, health conditions and comorbidities, medical service utilization, and health care costs. We used re-centered influence function regression to examine health care cost concentration, decomposing and estimating the effects of relevant factors on the distribution of costs. We also applied quantile regression forests-a machine learning approach-to identify the key factors for predicting the 10th (low), 50th (median), and 90th (high) quantiles of health care costs associated with CVD treatment.

Results

Our sample included 28,213 patients with CVD. The 10th, 50th and 90th quantiles of health care cost for patients with CVD were 6,103 CNY, 18,105 CNY, and 98,637 CNY, respectively. Patients with high health care costs were more likely to be older, male, and have a longer length of hospital stay, more comorbidities, more complex medical procedures, and emergency admissions. Higher health care costs were also associated with specific CVD types such as cardiomyopathy, heart failure, and stroke.

Conclusion

Machine learning methods are useful tools to identify determinants of health care costs for patients with CVD in China. Findings may help improve policymaking to alleviate the financial burden of CVD, particularly among patients with high health care costs.