Healthcare systems worldwide are confronted with major economic, organizational and logistical challenges. Historic evolution of health care has led to significant healthcare sector fragmentation, resulting in systemic inefficiencies and suboptimal resource exploitation. To attain a sustainable healthcare model, fundamental, system-wide improvements that effectively network, and ensure fulfilment of potential synergies between sectors, and include and facilitate coherent strategic planning and organisation of healthcare infrastructure are needed. Critically, they must be specifically designed to sustainably achieve peak performance within the current policy environment for cost-control, and efficiency and quality improvement for service delivery. We propose creation of a new healthcare cluster, to be embedded in existing healthcare systems. It consists of (i) local 24/7 walk-in virtually autonomous do-it-yourself Digital Medical Centres performing routine diagnosis, monitoring, prevention, treatment and standardized documentation and health outcome assessment/reporting, which are online interfaced with (ii) regional 24/7 eClinician Centres providing on-demand clinical supervision/assistance to Digital Medical Centre patients. Both of these are, in turn, online interfaced with (iii) the National Clinical Informatics Centre, which houses the national patient data centre (cloud) and data analysis units that conduct patient- and population-level, personalized and predictive(-medicine) intervention optimization analyses. The National Clinical Informatics Centre also interfaces with biomedical research and prioritizes and accelerates the translation of new discoveries into clinical practice. The associated Health Policy Innovation and Evaluation Centre rapidly integrates new findings with health policy/regulatory discussions. This new cluster would synergistically link all health system components in a circular format, enable not only access by all arms of the health service to latest patient data, but also automatic algorithm analysis and prediction of clinical development of individual patients, reduce bureaucratic burden on medical professionals by enabling a greater level of focus of their expertise on non-routine medical tasks, lead to automatic translation of aggregate patient data/new knowledge into medical practice, and orient future evolution of health systems towards greater cohesion/integration and hence efficiency. A central plank of the proposed concept is increased emphasis on reduction of disease incidence and severity, to diminish both patient suffering and treatment costs. This will be achieved at the individual and population levels, through (i) significantly improved access to medical services, (ii) stronger focus on primary and secondary prevention and early treatment measures, and disease susceptibility prediction via personalized medicine, involving inter alia genome analysis at birth and periodic analysis of microbiomes and biomarkers, and integration with other patient health and epidemiology parameters, (iii) improved surveillance and (iv) intervention outcome benchmarking. The dMCs will become drivers of innovation and integrative evolution in health systems, of disease reduction and efficiency gains, and thus major contributors to development of sustainability of health care.