Designing evaluation rubrics for the development of virtual human twins in healthcare

Abstract Objectives Smart healthcare innovations driven by Virtual Human Twin (VHT) technology enable continuous patient monitoring. However, standards to assess their stage of development or a unified framework for performance comparisons are still lacking. This study aims to quantitatively analyze VHT-related studies, evaluate their development levels, and align them to the VHT roadmap. Materials and methods A systematic review guided by the PRISMA methodology was conducted, in which 26 studies representing different stages of VHT development were systematically analyzed. Articles were evaluated against an established 5-level roadmap and classified according to their closest alignment with black box, grey box, or surrogate VHTs. Results A rubric system was developed to assess VHT models to date, and their maturity was analyzed relative to the established roadmap. Among the 26 studies, all 5 roadmap levels were represented. Level 2 (Deductive stage) was the most frequently represented. Levels 4 and 5 (Evolutionary and Explainable stages) were represented only in 3 studies each. Discussion Among the included studies, VHT development appears fragmented, with significant hurdles in building VHTs with advanced functionality. Conclusion The proposed rubric system may serve as an assessment tool to evaluate progress, encourage discussion, and improve experimental approaches for future VHTs, helping address challenges in advancing VHT development along the established roadmap.