Healthcare preferences of the general Chinese population in the hierarchical medical system: A discrete choice experiment

The association between internet use and the choice of medical institution among Chinese older adults

BACKGROUND

As older people have complex medical needs and still encounter challenges in accessing online health information, the relationship between Internet use and the choice of medical institution made by them is unclear, and we aimed to examine this relationship.

METHODS

Data from the newly released 2020 China Family Panel Survey database were used. Furthermore, we used descriptive statistics to analyze the background characteristics of the sample and a logistic regression model to estimate the impact of Internet use on the choice of medical institution made by older adults. We conducted a stratified analysis to explore the influence of different characteristics on the relationship between Internet use and the choice of medical institution.

RESULTS

Totally 4,948 older adults were included. Multivariate logistic regression showed that, compared to non-Internet users, Internet users were less likely to choose community health service centers over general hospitals (P < 0.001, OR = 0.667, 95CI%: 0.558-0.797). The subgroup analyses found that Internet use only had an impact on the choice of medical institution in older adults aged 65-69 years, those with partners, those with primary or secondary education, those residing in urban areas, those without medical insurance, those with a self-rated health status as average or healthy, those with unchanged or better health trend, and those without chronic disease. The effect of Internet use on the choice of medical institution did not differ by sex, satisfaction, or trust in doctors.

CONCLUSION

Internet use may significantly affect older adults' tendency to choose general hospitals to meet their daily medical needs. The subgroup analyses indicated that different characteristics of older people affected this association.

Rapid growth of private hospitals in China: emerging challenges and opportunities to health sector management

China's private hospital market has experienced rapid growth over the last decade, with private hospitals now outnumbering public hospitals by a factor of two. This policy analysis uses available data and existing literature to analyze China's rapidly changing hospital market, identify key challenges resulting from rapid private hospital growth, and present recommendations to ensure future sustainable private hospital development in the country. Our analysis shows that while private hospitals outnumber public hospitals, outpatient visits and hospitalizations remain higher among public hospitals, while per-patient expenditure remains higher among private hospitals. Key challenges to private hospital development include limited government financial support, high tax burdens, difficulty in workforce recruitment and retainment, poor government regulation and oversight, and dissipating public trust. Recommendations to address these challenges include opening government contract bidding to private hospitals, creating a system that allows private hospitals to enter national health insurance schemes, reducing tax pressure on private hospitals, defining a legal system for market entry and exit of private hospitals, improving a system of supervision, and monitoring and evaluation of private hospital operation and performance.

Choices of medical institutions and associated factors in older patients with multimorbidity in stabilization period in China: A study based on logistic regression and decision tree model

Background

As China's population ages, its disease spectrum is changing, and the coexistence of multiple chronic diseases has become the norm with respect to the health status of its elderly population. However, the health institution choices of older patients with multimorbidity in stabilization period remains underresearched. This study investigate the factors influencing the choices of older patients with multimorbidity to provide references for the rational allocation of healthcare resources.

Methods

A multistage, stratified, whole-group random-sampling method was used to select eligible older patients from September to December of 2022 who attended the Community Health Service Center of Guangdong Province. We adopted a self-designed questionnaire to collect patients' general, disease-related, social-support information, their intention to choose a healthcare provider. A binary logistic regression and decision tree model based on the Chi-squared automatic interaction detector algorithm were implemented to analyze the associated factors involved.

Results

A total of 998 patients in stabilization period were included in the study, of which 593 (59.42%) chose hospital and 405 (40.58%) chose primary care. Our binary logistic regression results revealed that age, sex, individual average annual income, educational level, self-reported health status, activities of daily living, alcohol consumption, family doctor contracting, and family supervision of medication or exercise were the principal factors influencing the choice of medical institutions for older patients with multimorbidity (p < 0.05). The decision-tree model reflected three levels and 11 nodes, and we screened a total of four influencing factors: activities of daily living, age, a family doctor contract, and patient sex. The data showed that the logistic regression model possessed an accuracy of 72.9% and that the decision tree model exhibited an accuracy of 68.7%. Prediction using the binary logistic regression was thus statistically superior to the categorical decision-tree model based on the Chi-squared automatic interaction detector algorithm (Z = 3.238, p = 0.001).

Conclusion

More than half of older patients with multimorbidity in stabilization period chose hospitals for healthcare. Efforts should be made to improve the quality of healthcare services and increase the medical contracting rate and recognition of family doctors so as to attract older patients with multimorbidity to primary medical institutions.

Valuing Chinese medicine quality of life-11 dimensions (CQ-11D) health states using a discrete choice experiment with survival duration (DCETTO)

OBJECTIVE

To explore generating a health utility value set for the Chinese medicine Quality of life-11 Dimensions (CQ-11D), a utility instrument designed to assess patients' health status while receiving TCM treatment, among the Chinese population.

METHODS

The study was designed to recruit at least 2400 respondents across mainland China to complete one-to-one, face-to-face interviews. Respondents completed ten discrete choice experiment with survival duration (DCETTO) tasks during interviews. The conditional logit models were used to generate the health utility value set for the CQ-11D using the DCETTO data.

RESULTS

A total of 2,586 respondents were invited to participate in the survey and 2498 valid interviews were completed (a completion rate of 96.60%). The modified conditional logit model with combing logically inconsistent levels was ultimately selected to construct the health utility value set for the CQ-11D instrument. The range of the measurable health utility value was -0.868 ~ 1.

CONCLUSION

The study provides the first utility value set for the CQ-11D among the Chinese population. The CQ-11D and corresponding utility value set can be used to measure the health utility values of patients undergoing traditional Chinese medicine interventions, and further facilitate relevant cost-utility analyses. The application of the CQ-11D can support TCM resource allocation in China.

Preferences of patients with diabetes mellitus for primary healthcare institutions: a discrete choice experiment in China

OBJECTIVES

To quantify the preference of patients with diabetes mellitus (DM) for primary healthcare (PHC) institutions in China to redirect the patient flow and improve health outcomes.

DESIGN

Cross-sectional study. Discrete choice experiment (DCE) surveys asked patients with DM to choose between hypothetical institutions that differed in the medical service capacity, out-of-pocket (OOP) medical costs per month, travel time, the attitude of medical staff and the availability of diabetes drugs.

SETTING

Shandong province, China.

PARTICIPANTS

The participants were 887 patients with DM from 36 urban communities and 36 rural villages in Shandong province. One participant did not provide any DCE answers and a further 57 patients failed the internal consistency test. 829 fully completed surveys were included in the final data analysis.

MAIN OUTCOMES AND MEASURES

A mixed logit model was used to calculate the willingness to pay and predict choice probabilities for PHC institution attributes. Preference heterogeneity was also investigated.

RESULTS

All five attributes were associated with the preferences of patients with DM. The OOP medical costs and the medical service capacity were the most influential attributes. Improvements simultaneously in the attitude of medical staff, drug availability and travel time increased the likelihood of a patient's PHC institution choice. Preferences differed by region, annual household income and duration of diabetes.

CONCLUSIONS

Our patient preference data may help policymakers improve health services and increase acceptance of choosing PHC institutions. The OOP medical costs and medical service capacity should be regarded as a priority in decision-making.