Traditional software development life cycle (SDLC) have long been acknowledged as a practical framework for building and managing software systems. However, when it comes to developing digital twin (DT) in the healthcare domain, the traditional SDLC approach faces significant challenges due to the dynamic nature of healthcare ecosystems and rapid technological developments. This paper proposes augmented SDLC as a methodology for DT development and customises it with additional techniques, technologies, and practices to meet DT characteristics.

A virtual mirrored replica of the real-world, has become a new trend in recent years with the advent of Industry 4.0, shows how intelligent digital twins (DT) can unlock busi-ness value. The implementation of DT requires various types of technologies, including the Internet of Things (IoT), cloud computing, artificial intelligence, and others. Today, DTs can be used in various fields, including manufacturing, smart cities and healthcare. It can be used to monitor the real environment, predict its future, control its behavior, and improve its overall performance. Despite the aforementioned advantages of DTs, if not protected, they can also be considered as an open environment for attackers. If attackers take over a DT, they may end up owning the real environment controlled by the DT. This can result in damaging consequences. This paper explores the potential security and privacy threats that may be brought in through DTs. It proposes and presents a threat meta-model of DTs that identifies key security aspects of concern.

A hospital is an ecosystem that includes real-time services that require high human interaction on both resources level (doctor, nurses, etc.) and entities level (patients). Designing, planning, improving and controlling this system can be very challenging due to the system complexity governed by several subjective factors that affect the hospital interrelated functions or services. However, continuously changing health care needs that consistently face hospitals require them to keep continuously improving the efficiency of these services as demand increases and as new services are added. This paper proposes a new methodology that uses the concept of Digital Twin (DT) of hospital services based on Discrete Event Simulation (DES) integrated with health care information systems and Internet of things (IoT) devices. It develops a predictive decision support model that employs real-time services data drawn from these systems and devices. This model enables assessing the efficiency of existing health care delivery systems and evaluating the impact of changes in services without disrupting daily activities of the hospital. The developed model, a digital twin (or a virtual replica of the hospital), simulates a number of key hospital health delivery services, based on relevant data retrieved in real-time. Although the model simulates four key services, initially as a proof of concept, but it proposes a general framework, which can be expanded to include other services. The demonstrated proof-of-concept shows that it achieves better planning and improvement of usage of resources, and thus enabling both practitioners and management to examine any model changes to foresee the effectiveness or efficiency of services before they are applied in reality.