Assessing public health policy approaches to level-up the gradient in health inequalities: the Gradient Evaluation Framework

Objectives

This paper seeks to introduce and analyse the development of the Gradient Evaluation Framework (GEF) to facilitate evaluation of policy actions for their current or future use in terms of their ‘gradient friendliness’. In particular, this means their potential to level-up the gradient in health inequalities by addressing the social determinants of health and thereby reducing decision-makers' chances of error when developing such policy actions.

Study design

A qualitative developmental study to produce a policy-based evaluation framework.

Methods

The scientific basis of GEF was developed using a comprehensive consensus-building process. This process followed an initial narrative review, based on realist review principles, which highlighted the need for production of a dedicated evaluation framework. The consensus-building process included expert workshops, a pretesting phase, and external peer review, together with support from the Gradient project Scientific Advisory Group and all Gradient project partners, including its Project Steering Committee.

Results

GEF is presented as a flexible policy tool resulting from a consensus-building process involving experts from 13 European countries. The theoretical foundations which underpin GEF are discussed, together with a range of practical challenges. The importance of systematic evaluation at each stage of the policy development and implementation cycle is highlighted, as well as the socio-political context in which policy actions are located.

Conclusions

GEF offers potentially a major contribution to the public health field in the form of a practical, policy-relevant and common frame of reference for the evaluation of public health interventions that aim to level-up the social gradient in health inequalities. Further research, including the need for practical field testing of GEF and the exploration of alternative presentational formats, is recommended.