Mobile technology is an integral part of the modern healthcare environment. The mobile user interface (MUI) serves as the bridge between the application and healthcare professionals. It is important that the physician be able to easily express his needs on the MUI and correctly interpret the information displayed. However, there are many challenges that face the designer in designing and developing context-sensitive MUIs in this environment. The adaptability of the MUI is considered to be one of the most important issues to address. According to the World Health Organization (WHO), MUI adaptability is a major problem in the healthcare context. For the designer, the hope is that new technologies will be developed, such as mobile devices adaptable to different environments, to enable customization of the application to the user’s context.
In this thesis, we propose a new methodology for designing a context-based adaptable MUI for healthcare applications. This methodology offers a new approach to automated MUI context adaptation, and provides a solution for both the provider (designer) of the healthcare application and the consumer (physician). New techniques for adapting MUIs offer new opportunities for the MUI designer to maximize the benefits of mobile health technology by providing the best possible way for healthcare professionals to perform their tasks efficiently and effectively.
The proposed methodology is based on research contributions in four areas: (1) a new quality-in-use measurement model for validation purposes; (2) user stereotype modeling with a set of context descriptors, which formalize the domain expertise of the users; (3) context information modeling; and (4) use of the decision table technique to adapt the MUI features based on the context and the user stereotypes. The proposed quality-in-use model is inspired by the ISO/IEC 25010 and ISO/IEC 25022 international standards and adapted to healthcare applications. The first contribution is used in validating the quality-in-use of a software product developed according to the CON-INFO methodology, and the last three contributions are linked to form a methodology for development. The MUI features adapted to the needs of healthcare professionals have been implemented on the iPhone™ for validation purposes.
An example of software for medical application is the Phoenix Health Information System (PHIS), which is in use at King Abdulaziz University Hospital (KAUH). PHIS2 is an updated desktop version developed based on Human-Computer Interaction (HCI) principles. A new mobile-based version of PHIS2 (PHIS2-M) has since been introduced, to make PHIS accessible from a mobile-based platform. The proposed context-based and rule-based approach for MUI feature adaptability resulted in a new version of PHIS2-M – PHIS2-MA (MA stands for mobile adaptation).
This thesis validates the proposed methodology and clearly demonstrates its usefulness, providing details of the four empirical studies conducted with the end-users (physicians) in a real environment at the KAUH.
The results of the formal studies reveal that our CON-INFO methodology for designing an adaptable MUI led to improvements to the current application and allowed researchers to test successive versions of the ‘final’ application
