Healthcare Digital Twins Across Scales: A Narrative Review and Five-Level Conceptual Framework

Abstract

Background/Objectives: Healthcare digital twins are being developed at scales ranging from individual organs to regional health systems. However, the literature at these different scales has largely evolved independently. This narrative review examines how the concept changes as the represented object grows, and proposes a five-level framework: physiological, patient, care-delivery, hospital and health-system twins proposed by the authors as an analytical framework. Methods: Web of Science, Scopus, PubMed and Google Scholar were searched between June and July 2026 for English-language records published from January 2022 onwards. Sources were eligible if they described a virtual representation of an identified physical counterpart in healthcare, updated from that counterpart’s own data and used to produce decision-relevant predictions. Editorials, abstract-only records, static models and work outside healthcare were excluded. The included literature was examined to identify recurring patterns in the representation and application of healthcare digital twins. These patterns informed the development of the authors’ proposed five-level conceptual framework. As no formal quality appraisal was undertaken, conclusions regarding evidence maturity and implementation should be interpreted cautiously. Results: Forty-four publications form the evidence base: 10 original studies, 26 reviews and 8 conceptual or consensus papers. Patient-specific applications were described primarily at the physiological and patient levels, particularly in cardiology and oncology. External validation remained uncommon, and prospective evaluation was rare across all five levels. Care-delivery twins were reported mainly in critical care, emergency and perioperative settings, whereas hospital and health-system applications were largely limited to prototypes and simulations. Conclusions: This review suggests that the challenges associated with healthcare digital twins evolve as applications move from physiological models to health-system settings. Beyond technical complexity, interoperability, organisational, governance and equity considerations become increasingly important. Prospective evidence of patient benefit, operational effectiveness and system-level impact remains limited across all five levels.