Are smart older adult care devices “cost-reducing and efficiency-enhancing” or “demand-activating”?—Empirical evidence from Chinese older adult households

Background: Against the backdrop of global aging and the growing burden of chronic diseases, Smart Health Devices (SHD) are regarded as important tools for health management. However, there is a theoretical controversy between "technological substitution" and "technological expansion" regarding their economic consequences: Does SHD reduce medical expenditures through prevention, or push up costs by detecting hidden diseases? Currently, there is a lack of systematic empirical evidence based on large-scale microdata. Methods: = 7,426), this study constructed dual indicators of household health and care expenditure (HCE) and its share in total consumption. Ordinary Least Squares (OLS), quantile regression, and the Heckman two-step method were employed to examine the robust association between SHD use and medical expenditure, and the Discacciati four-way decomposition method was used to reveal its intrinsic mechanism. Results: The study found that the use of SHD was significantly associated with higher absolute household health and care expenditure (by approximately 101%) and a larger share in total consumption (by 1.0 percentage points), supporting the "medical demand activation" hypothesis. Mechanism analysis revealed a unique "dual path": on the one hand, device use exhibited a positive correlation with total expenditure, likely linked to a higher detection rate of chronic diseases and increased attention to pain (discovery effect); on the other hand, it showed a marginal negative association with cost levels, potentially reflecting improved disease management efficiency (management effect). Heterogeneity analysis showed that "rigid care devices" represented by smart wheelchairs were strongly associated with a heavier dual burden, while "preventive management devices" represented by smart wristbands were significantly correlated with a lower share of medical expenditure. In addition, highly educated and urban groups exhibited stronger expenditure sensitivity, indicating potential digital health inequality. Conclusion: At the current stage, smart devices mainly act as a "health radar," corresponding to the explicit manifestation of potential health risks into medical consumption. Policymakers should implement a classified subsidy strategy: include rigid care devices in long-term care insurance payment to prevent catastrophic expenditure, and promote preventive devices through incentive mechanisms to achieve an economic transformation from "passive medical care" to "active health."