Bridging the rural logistics penalty: quantifying structural costs and designing policy mechanisms for home TCM delivery to older adults with chronic respiratory diseases.

backgroundEquitable access to prescribed therapies remains challenging for older adults with chronic respiratory diseases (CRDs) in rural China. Liquid Traditional Chinese Medicine (TCM) decoctions are widely used in respiratory care, but their large volume, thermal sensitivity, and need for temperature-controlled handling make home delivery particularly difficult in geographically dispersed rural settings. The structural and cost implications of this rural cold-chain delivery burden remain insufficiently quantified.

methodsWe developed a four-stage calibrated simulation framework linking CHARLS 2018 microdata with external facility-density statistics, interpretable machine learning, parameterized micro-costing, and policy scenario modelling. The analytic sample included 11,045 adults aged ≥ 60 years, including 2,351 participants with chronic lung disease or asthma. Because CHARLS does not provide patient-level geocoded coordinates or observed residence-to-facility routes, Stage I generated simulation-derived distance distributions rather than observed travel distances, and no patient-level geocoded empirical validation was possible. Stage II used an IADL-based XGBoost-SHAP model to characterize functional vulnerability more directly relevant to medication access and home-delivery prioritization, with ADL retained as a sensitivity outcome. Stage III estimated cold-chain delivery costs under alternative assumptions for consolidation, route tortuosity, and willingness to pay. Stage IV examined cooperation dynamics across subsidy scenarios.

resultsThe calibrated simulation preserved the facility-density-driven rural-urban contrast by design rather than empirically discovering patient routes. Mean modeled distance was 10.61 km for rural residents versus 2.85 km for urban residents, and 10.8% of rural simulated observations exceeded 15 km. The IADL-based XGBoost model achieved an AUC of 0.668 and an accuracy of 0.631; rural residence ranked eighth and was not the leading predictor in the service-vulnerability model. Rural delivery costs exceeded urban benchmarks under all modeled scenarios, with the rural 95th percentile ranging from 34.28 RMB at η = 10 to 77.63 RMB at η = 3. Higher subsidy, willingness to pay, and consolidation efficiency increased cooperation levels, but no scanned condition produced stable three-party cooperation within the 35-55 RMB subsidy range.

conclusionsThis study provides a transparent calibrated-simulation stress test rather than an empirically validated route-reconstruction or subsidy-threshold study. Under the current assumptions, the findings do not support a single transferable subsidy threshold and instead indicate that local pilot calibration, observed route-cost data, and realistic payoff inputs are required before implementation claims can be made.