Complexity of healthcare improvement - a comparative analysis of frameworks for improvement science

This study aims to critically compare and analyze relevant frameworks used in improvement science in order to examine how they address complexity as well as the contextual, social, and relational mechanisms that shape healthcare improvement. The study adopts a qualitative approach and is based on a comparative analysis of ten frameworks: KTA, CAIMeR, SHIFT, CAF, CAMM, CFIR, HPCM, IMQSE, NASSS and LHS. These frameworks were examined through a conceptual lens informed by theories of complexity as well as contextual, social, and relational mechanisms that shape healthcare improvement in practice. The findings reveal a fragmented conceptual landscape within improvement science, demonstrating substantial variation in how the frameworks address complexity and the contextual, social and relational mechanisms. A key observation is that most frameworks only partially and implicitly capture the complexity of healthcare systems, without clearly articulating how complexity influences improvement processes. This pattern is reflected in the overall results. One possible explanation is that many of the frameworks originate from fields such as Implementation Science and Health Informatics. However, this origin has implications when viewed from a Quality 3.0 perspective. Notably, Co-production in healthcare is largely absent from the analyzed frameworks. In addition, limited attention is given to the interactions between micro-, meso- and macro perspectives, which challenges the fundamental system perspective in healthcare improvement. In conclusion, the analyzed frameworks do not fully reflect the complexity of healthcare systems. Although many frameworks acknowledge contextual factors, fewer explicitly address the relational and social mechanisms through which healthcare improvement is enacted in practice.