Smart wards in healthcare: a taxonomy and systematic review with meta-analysis

A systematic review with meta-analysis was conducted to examine the current landscape of Smart Wards and their associated technologies. A total of 55 peer-reviewed studies, published between 2000 and 2023, were included. We introduced a two-sided taxonomy categorizing Smart Wards by technological domain (sensors, assistant devices, robotics, tracking, integrated units, and extended reality) and by intended user groups such as patients, doctors, nurses, administrators, and relatives. This structured framework allows for a systematic mapping of existing use cases and illustrates how specific technologies interact with user groups across clinical contexts. The review further identifies the medical specialties in which technologies are predominantly employed. General wards, geriatrics, and surgical wards emerged as the primary specialties. Technologies such as physiological data sensors and agitation monitoring systems are particularly prevalent in geriatrics, while surgical wards often employ systems for continuous wireless monitoring and early warning. We further discussed the parts a Smart Ward is composed of in detail and provided real world examples of systems that have already been tested in clinical environments. The subsequent meta-analysis compared traditional temperature measurement methods with smart thermometry devices. The analysis, based on three prospective studies with 676 participants, revealed a slight, though not statistically significant, trend towards lower temperature readings by smart devices. Overall, the findings indicate that Smart Ward technologies offer measurable improvements in patient safety, workflow efficiency, and the personalization of care. Nevertheless, significant implementation challenges persist, notably regarding system interoperability, data security, inconsistent device standardization, and clinical staff acceptance of emerging technologies. These limitations highlight the necessity for additional research on scalable integration approaches, the long-term success of these systems, and the development of robust frameworks for ethical data handling. In particular, the combined deployment of multiple technologies within integrated Smart Ward environments remains understudied, particularly regarding their impact on clinical decision-making and the overall quality of care delivery.