Regional differences in electronic medical record adoption in Japan: A nationwide longitudinal ecological study

Regional differences in the adoption of electronic medical records (EMR) are a major problem, yet little is known about these differences internationally. We analyzed regional differences in EMR adoption in Japan and evaluated factors associated with these differences.

This nationwide ecological study used secondary data from all secondary medical service areas (SMSAs) in fiscal years 2008 (n = 348) and 2014 (n = 344). For each SMSA we collected the following information from a Japanese national database: the number of medical facilities that had adopted EMR, the population density, the average per capita income, the number of working doctors per 1000 people, and the proportion of interns to all working doctors. To adjust for medical facility characteristics in each SMSA, such as number of beds, public versus private hospital, and hospital type (psychiatric or other), we estimated the standardized adoption ratio (SAR) for EMR adoption, modeled on the standardized mortality ratio. We calculated Moran's I for the SAR and investigated whether the SAR had spatial autocorrelations. We evaluated the association between the SAR and regional factors with a conditional autoregressive model. We compared these results in 2008 and 2014, for both hospitals and clinics.

While the EMR adoption rate in SMSAs increased, Moran's I of the SAR in hospitals was close to 1 in both 2008 and 2014, and Moran's I of the SAR in clinics increased from 2008 to 2014. For hospitals, there was a significant association between the proportion of interns to all working doctors and the SAR only in 2008. For clinics, average income in the SMSA was positively associated with the SAR, whereas the number of working doctors was negatively associated with the SAR in both 2008 and 2014. Population density was positively associated with the SAR only in 2014.

From 2008 to 2014, EMR adoption in Japan generally increased, but geographical differences did not improve. Regional factors associated with the SAR were different for hospitals than for clinics. Therefore, the government should take different approaches for clinics and hospitals to improve regional differences in EMR adoption, especially in providing financial and technical support.