Cost-effectiveness of a domestic violence and abuse training and support programme in primary care in the real world: updated modelling based on a MRC phase IV observational pragmatic implementation study

Abstract

Background: Primary care clinicians often struggle to identify women who experience domestic violence and abuse (DVA) and are uncertain about how to respond when DVA is disclosed. The Identification and Referral to Improve Safety (IRIS) randomised controlled trial tested the effectiveness of a primary care training and support intervention to improve the response to women experiencing DVA, and found it to be cost-effective. As a result, the IRIS programme has been implemented across the UK, generating data on costs and effectiveness outside a trial context. Aim: To evaluate the cost-effectiveness of the implementation of the IRIS programme using up-to-date real-world information on costs and effectiveness from routine clinical practice. Design and Setting: Cost–utility analysis in UK general practices, including data from six sites which have been running IRIS for at least two years across England. Method: A Markov model was constructed to estimate mean costs and quality-adjusted life-years (QALYs) of IRIS versus usual care per woman registered at a general practice from a societal and health service perspective with a ten-year time horizon. Results: The IRIS programme saved £14 per woman aged 16 or older registered in general practice (95% CI [-£151; £37]) and produced QALY gains of 0.001 per woman (95% CI [-0.005; 0.006]). The incremental net monetary benefit was positive both from a societal and NHS perspective (£42 and £22 respectively) and the IRIS programme was cost-effective in 61% of simulations using real life data when the cost-effectiveness threshold was £20 000 per QALY gained as advised by NICE. Conclusion: The IRIS programme is likely to be cost-effective and cost-saving from a societal perspective in the UK and cost effective from a health service perspective, though there is considerable uncertainty surrounding these results, reflected in the large confidence intervals.