研究目的：

基于健康需求理论与价值医疗理念，旨在评估职工医保门诊统筹政策对参保人医疗服务利用及医疗费用的影响，检验政策实施效果，探讨不同保障水平与社会经济背景下的差异性反应，为完善我国门诊共济保障机制提供实证依据和政策建议。

研究方法：

使用中国健康与养老追踪调查（CHARLS）2015年与2018年数据，利用描述性分析方法介绍样本基本情况，包括样本的省份、地区、性别、婚姻状况、受教育水平、家庭收入、工作状态、健康状况等分布情况；采用倾向得分匹配双重差分法（PSM-DID），在控制人口学特征、健康状况及社会经济等变量的基础上，评估门诊统筹政策对参保人门诊与住院服务利用、医疗总费用、自付医疗费用等指标的政策效应，并进行不同保障水平与收入分组的异质性分析。

研究结果：

采用倾向得分匹配双重差分法（PSM-DID）分析发现，职工医保门诊统筹政策实施后，参保人一个月内门诊就医概率提高4.8个百分点，过去一年住院率下降4.1个百分点，验证了政策通过降低门诊服务经济门槛释放潜在需求、减少不合理住院替代行为的机制。医疗费用方面，政策推动门诊费用增长14%，但住院费用下降26%，医疗总费用减少16%，自付医疗费用降低21%，表明政策通过优化服务结构实现了费用负担的整体缓解。政策效应呈现显著的群体与区域异质性。低收入群体和慢性病患者受益更为突出：其门诊利用率提升幅度分别比高收入群体高3.3和2.4个百分点，住院率降幅高2.1个百分点，自付医疗费用减少比例高7.8个百分点，凸显政策在促进健康公平中的作用。“保障水平较好”（无封顶线/高封顶线/无起付线）的政策效果显著优于“保障水平一般”，门诊利用率提升幅度和住院费用降幅均更优，印证了保障水平设计对政策效应的关键影响。

研究结论：

一是职工医保门诊统筹政策显著提高了门诊服务利用率，促进疾病早期干预；且政策对住院服务利用具有一定替代效应，缓解了医保基金压力。二是门诊统筹显著降低了参保人医疗总费用与自付费用。三是在保障水平较高的地区，政策效果更明显，门诊服务利用率更高，住院费用下降幅度更大；此外，低收入群体在费用负担缓解方面获益相对更显著。

研究建议：

优化门诊统筹报销结构，强化门诊替代住院的政策导向；因地制宜提高门诊统筹保障水平，增强政策控费能力与保障作用；政策向弱势群体倾斜，完善分层分类保障机制；统筹考虑区域发展差异，推动门诊统筹政策协同实施；加强医保绩效评价与数据联通，提升政策动态调整能力。

Objective:

Based on the health needs theory and the concept of value-based healthcare, this study aims to evaluate the impact of the employee medical insurance outpatient pooling policy on the utilization of medical services and medical expenses of insured individuals, examine the policy implementation effect, explore the differential responses under different protection levels and socio-economic backgrounds, and provide empirical evidence and policy recommendations for improving the outpatient mutual aid guarantee mechanism in China.

Methods:

Using the data from the China Health and Retirement Longitudinal Study (CHARLS) in 2015 and 2018, descriptive analysis methods are employed to introduce the basic characteristics of the sample, including the distribution of provinces, regions, gender, marital status, education level, family income, employment status, and health status. The propensity score matching difference-in-differences method (PSM-DID) is adopted to assess the policy effect of the outpatient pooling policy on the utilization of outpatient and inpatient services, total medical expenses, and out-of-pocket medical expenses of insured individuals, while controlling for demographic characteristics, health status, and socio-economic variables. Heterogeneity analysis is conducted based on different protection levels and income groups.

Results:

The application of the propensity score matching difference-in-differences method (PSM-DID) reveals that after the implementation of the employee medical insurance outpatient pooling policy, the probability of outpatient visits within a month for insured individuals increased by 4.8 percentage points, and the hospitalization rate over the past year decreased by 4.1 percentage points. This validates the mechanism by which the policy reduces the economic threshold for outpatient services to release potential demand and reduce unreasonable hospitalization substitution behaviors. Regarding medical expenses, the policy led to a 14% increase in outpatient expenses, but a 26% decrease in inpatient expenses, resulting in a 16% reduction in total medical expenses and a 21% decrease in out-of-pocket medical expenses. This indicates that the policy has achieved an overall alleviation of the financial burden through the optimization of service structure. The policy effects exhibit significant heterogeneity across different groups and regions. Low-income groups and patients with chronic diseases benefit more prominently: their outpatient utilization rate increased by 3.3 and 2.4 percentage points respectively compared to high-income groups, the decline in hospitalization rate was 2.1 percentage points higher, and the reduction in out-of-pocket medical expenses was 7.8 percentage points greater, highlighting the policy's role in promoting health equity. Policies with "better protection levels" (no cap/ high cap/ no deductible) have significantly better effects than those with "average protection levels", with better improvements in outpatient utilization rates and greater reductions in inpatient expenses, confirming the crucial impact of protection level design on policy effects.

Conclusion:

First, the outpatient pooling policy of the employee medical insurance has significantly increased the utilization rate of outpatient services, promoting early intervention of diseases; and the policy has a certain substitution effect on inpatient service utilization, alleviating the pressure on medical insurance funds. Second, the outpatient pooling has significantly reduced the total medical expenses and out-of-pocket expenses of insured individuals. Third, in regions with higher guarantee levels, the policy effect is more obvious, the utilization rate of outpatient services is higher, and the decline in inpatient expenses is greater; in addition, low-income groups benefit relatively more in terms of alleviating the burden of expenses.

Recommendations:

Optimize the reimbursement structure of outpatient pooling, strengthen the policy orientation of outpatient services replacing inpatient services; increase the protection level of outpatient pooling based on local conditions to enhance the policy's cost control ability and protection effect; tilt policies towards vulnerable groups and improve the stratified and classified protection mechanism; consider regional development differences and promote the coordinated implementation of outpatient pooling policies; strengthen the performance evaluation of medical insurance and data connectivity to enhance the dynamic adjustment ability of policies.