Evaluating the Zero-Markup Drug Policy's Effects on Financial Burden and Pharmaceutical Channel Migration: A...

This study evaluates the impact of China's zero-markup drug policy (ZMDP) on patients' financial burden and pharmaceutical purchasing channel migration, using Yichang City in Hubei Province as a case study.

We analyzed data from 108 hospitals (January 2016 - December 2019) and monthly medical insurance reimbursement records. Structural variation analysis (SVA) and interrupted time series analysis (ITSA) with month-of-year fixed effects and counterfactual predictions were employed to assess changes in outpatient costs, inpatient costs, and pharmacy purchase outcomes (total expenditure, purchase volume, and average cost per purchase) before and after the policy implementation (August 2017).

Drug cost proportions declined from 41.67% to 37.14% for outpatient and from 34.97% to 27.60% for inpatient services. ITSA revealed a marginally significant immediate outpatient cost reduction (β₂ = -4.431, p = 0.094) and a significant monthly inpatient cost decline (β₃ = -49.144, p = 0.031). However, diagnostic and procedural costs increased, with limited shift toward professional fees. Pharmacy data showed a coherent pattern: total expenditure significantly decreased (β₂ = -953.507 thousand ¥, p = 0.024), purchase volume increased (β₃ = 1353.214, p = 0.034), and average cost per purchase declined (β₃ = -0.291, p < 0.001) - indicating successful price reduction with expanded pharmacy access.

The ZMDP effectively reduced hospital drug expenditures but triggered cost substitution toward diagnostic services and pharmaceutical channel migration to retail pharmacies. For healthcare leaders, these findings suggest that vertical price regulation without horizontal integration across care settings may simply relocate costs. Future reforms should incorporate integrated prescription monitoring and complementary pricing reforms to achieve sustainable financial protection.

This study has several strengths. The use of ITSA with month-of-year fixed effects and counterfactual predictions controls for seasonal patterns and quantifies policy effect magnitudes. Structural variation analysis complements this by measuring expenditure redistribution across service categories. Placebo tests further support the robustness of findings for most outcomes. Limitations include the single-group ITSA design without a concurrent control group and the single-city setting, which limit causal attribution and generalizability. The study period ends in 2019 due to the COVID-19 pandemic, constraining long-term observation.