Measuring the health systems impact of disease control programmes: a critical reflection on the WHO building blocks framework

The WHO health systems Building Blocks framework has become ubiquitous in health systems research. However, it was not developed as a research instrument, but rather to facilitate investments of resources in health systems. In this paper, we reflect on the advantages and limitations of using the framework in applied research, as experienced in three empirical vaccine studies we have undertaken.

We argue that while the Building Blocks framework is valuable because of its simplicity and ability to provide a common language for researchers, it is not suitable for analysing dynamic, complex and inter-linked systems impacts. In our three studies, we found that the mechanical segmentation of effects by the WHO building blocks, without recognition of their interactions, hindered the understanding of impacts on systems as a whole. Other important limitations were the artificial equal weight given to each building block and the challenge in capturing longer term effects and opportunity costs. Another criticism is not of the framework per se, but rather how it is typically used, with a focus on the six building blocks to the neglect of the dynamic process and outcome aspects of health systems.

We believe the framework would be improved by making three amendments: integrating the missing “demand” component; incorporating an overarching, holistic health systems viewpoint and including scope for interactions between components. If researchers choose to use the Building Blocks framework, we recommend that it be adapted to the specific study question and context, with formative research and piloting conducted in order to inform this adaptation.

As with frameworks in general, the WHO Building Blocks framework is valuable because it creates a common language and shared understanding. However, for applied research, it falls short of what is needed to holistically evaluate the impact of specific interventions on health systems. We propose that if researchers use the framework, it should be adapted and made context-specific.