Effect of e-health on medical expenditures of outpatients with lifestyle-related diseases.

We analyzed the effect of e-health on medical expenditures in Nishi-aizu Town, Fukushima Prefecture, Japan, using panel data of medical expenditures for about 400 residents from 2002 to 2006. The Nishi-aizu Town system was introduced in 1994 and is still successfully operating as one of the longest running implementations of e-health in Japan. The town office maintains a register of receipts for medical expenditures paid by the National Health Insurance system and provides data on e-health users, allowing users and nonusers of e-health and their respective costs to be distinguished. Here, we focus on patients with lifestyle-related diseases such as high blood pressure, diabetes, stroke, heart failure, etc. This article postulates that e-health reduces medical expenditures via two mechanisms, decreasing travel expenses and preventing symptoms from worsening. The former implies that e-health monitoring allows patients at home to visit medical institutions less frequently, and the latter that the symptoms experienced by e-health users are less severe than those experienced by nonusers. We termed these the travel cost effect and opportunity cost effect, respectively. Chronic conditions tend not to occur singly, and many patients have more than one; for example, patients with high blood pressure or diabetes also likely have heart disease at the same time. This multiplicity of conditions hampers cost analysis. Among methodological issues, a number of recent empirical health analyses have focused on the endogenous problem of explanatory variables. Here, we solved this problem using the generalized method moments (GMM) system, which allows treatment of not only the endogenous problem of explanatory variables but also the dynamic relationship among variables, which arise due to the chronic time-lagged effect of lifestyle-related diseases on patients. We also examined a second important methodological problem related to reverse correlation between the medical expenditures of an outpatient and e-health and took sampling biases into consideration. We concluded that this control of endogeneity through system GMM confirms that the relationship between the medical expenditures of an outpatient and e-health shows causation rather than simple correlation and that e-health use, duration of e-health use, and frequency of e-health use can reduce outpatient medical expenditures for lifestyle-related diseases.