Degree Name

Doctor of Philosophy


School of Computing and Information Technology


Healthcare providers in Australia are currently facing a number of challenges, including the increasing size of the aging population, a shortage of healthcare workers, patient demands for increased access to health information and participation in healthcare decision making and rising health care costs. As a response to these challenges, consumer e-Health is emerged as a potential solution to the problems of accessibility, quality and costs of delivering public healthcare services to patients. Although the potential of consumer e-Health is acknowledged in academia, as well as among certain health care professional groups, it still remains unclear if patients are willing and able to accept and use this innovative service. Academia has recognized the importance of research on e-Health adoption. However, to date, the main focus is on measuring health care outcomes from health care providers’ point of view, knowledge needs to be developed in regards to the consumer acceptance and its underlining reason. Therefore, the aim of this research is to study the factors influencing patients’ acceptance and usage of consume re-Health innovations. A simple but typical consumer e-health innovation – an e-appointment scheduling service – was developed and implemented in a primary health care clinic in a regional town in Australia.

A longitudinal case study was undertaken for 29 months after system implementation. The major factors influencing patients’ acceptance and use of the e-appointment service were examined through the theoretical lens of Rogers’ innovation diffusion theory. Data were collected from the computer log records of 25,616 patients who visited the medical centre in the entire study period, and from in-depth, semi-structured interviews with 125 patients after system implementation.

The study results show that the overall adoption rate of the e-appointment service increased slowly from 1.5% at 3 months after implementation, to 4% at 29 months, which means only the ‘innovators’ in the patient population had adopted this new service. The majority of patients did not adopt this innovation.