Big data in healthcare: Investigation of factors affecting the use of mobile health applications with an Extended Technology Acceptance Model

Big Data and Analytics Systems (BDAS) enable the storage, real-time analysis and visualization of large amounts of data and a wide range of structures. BDAS transforms our society and lives and promises more and more change. The use of mobile health (m-health) applications integrated with BDAS is important for promoting and improving health. The aim of the research is to expand the technology adoption literature by investigating impact of information systems integrated with BDAS's m-health applications on consumer adoption behavior. A new model was developed by integrating planned behavior theory, technology acceptance model and information systems success model. Examples of the study are life fits home (LFH) users over the age of 18 living in Istanbul. During the collection of research data, the e-survey method was preferred and the sampling method was applied easily. SPSS 24 was used for basic statistical analyses of 400 survey data obtained and the data were tested with structural equality model. According to the research findings, subjective norm, perceived behavioral control, perceived information quality, perceived system quality, perceived benefit and perceived ease of use have been found to have a positive effect on the intention of use within the scope of M-health applications integrated with BDAS. In addition, the perceived ease of use has been found to have a positive effect on the perceived benefit. Research contributes to the literature of technology adoption and can help the healthcare industry restructure its business models.