Factors influencing health information technology adoption in Thailand's community health centers: Applying the UTAUT model

BACKGROUND One of the most important factors for the success of health information technology (IT) implementation is users' acceptance and use of that technology. Thailand has implemented the national universal healthcare program and has been restructuring the country's health IT system to support it. However, there is no national data available regarding the acceptance and use of health IT in many healthcare facilities, including community health centers (CHCs). This study employed a modified Unified Theory of Acceptance and Use of Technology (UTAUT) structural model, to understand factors that influence health IT adoption in community health centers in Thailand and to validate this extant IT adoption model in a developing country health care context. METHODS An observational research design was employed to study CHCs' IT adoption and use. A random sample of 1607 regionally stratified CHC's from a total of 9806 CHCs was selected. Data collection was conducted using a cross-sectional survey by means of self-administered questionnaire with an 82% response rate. The research model was applied using the partial least squares (PLS) path modeling. RESULTS The data showed that people who worked in CHCs exhibited a high degree of IT acceptance and use. The research model analyses suggest that IT acceptance is influenced by performance expectancy, effort expectancy, social influence and voluntariness. Health IT use is predicted by previous IT experiences, intention to use the system, and facilitating conditions. CONCLUSIONS Health IT is pervasive and well adopted by CHCs in Thailand. The study results have implications for both health IT developmental efforts in Thailand and health informatics research. This study validated the UTAUT model in the field context of a developing country's healthcare system and demonstrated that the PLS path modeling works well in a field study and in exploratory research with a complex model.