This chapter presents a practical implementation of an integrated telemedicine server developed by the University Hospital Olomouc (UHO) within a project co-financed by the Olomouc Region, as a response to the deteriorating availability of qualified personnel in home care. As part of the pilot project, a system was created to centralize certain clinical consultations from the field and transmit them to a specialized hospital department via a secure digital platform. The solution was tested in collaboration with the home care agency eSestřička and focused on managing complications related to wounds, invasive inputs, and other nursing procedures for elderly and other patients. The key motivation behind the project is the current and future shortage of qualified professionals in the field. This trend is evident across the Czech Republic and on a European scale. At the same time, demographic data indicate a rapidly ageing population and a growing number of clients who will require intensive home care. This imbalance between rising demand and the limited capacity of healthcare staff creates pressure for effective tools that enable rapid expert support remotely without the need for the physical presence of a doctor or specialist. The integration server addresses this issue with a simple architecture: a field healthcare professional uses a software application for mobile devices called “ZUNI” to take a photo of a medical issue, adds a brief report, and sends a consultation request. A specialist at UHO receives the report in real time and can immediately contact the home care nurse by phone, provide recommendations, and record the solution in the system. This model supports continuity of care, can reduce the number of transports, and provides decision-making support for less experienced staff. From the perspective of nursing practice in home care, this approach brings a fundamental shift: it eliminates the isolation of individual providers, strengthens clinical confidence, and saves both time and costs. It also contributes to the education of field workers, as feedback can be immediate, factual, and professionally grounded. At the same time, it is possible to build a time-distributed image database for educational purposes or clinical studies to monitor the progression of conditions over time and the response of wounds to treatment. This opens the door to future use of artificial intelligence training, such as developing a “suggestion tool” that could, in some cases, replace a specialist for initial consultations. Photos of patients at home who require hospitalization can ease triage at emergency intake without the need to expose the wound, as the doctor can view it beforehand. In the future, it is expected that such integrated systems will become a standard part of home care. This is not just a technological upgrade, but a necessary response to structural changes in society and the distribution of the workforce. This chapter demonstrates how combining digital tools, inter-institutional cooperation, and practical needs can create a functional and scalable model for sustainable care, especially for the elderly.