Abstract
OBJECTIVES: To evaluate the cost-effectiveness of the implementation of the Identification and Referral to Improve Safety (IRIS) programme using up-to-date real-world information on costs and effectiveness from routine clinical practice. 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 10-year time horizon.
DESIGN AND SETTING: Cost-utility analysis in UK general practices, including data from six sites which have been running IRIS for at least 2 years across England.
PARTICIPANTS: Based on the Markov model, which uses health states to represent possible outcomes of the intervention, we stipulated a hypothetical cohort of 10 000 women aged 16 years or older.
INTERVENTIONS: The IRIS trial was a randomised controlled trial that tested the effectiveness of a primary care training and support intervention to improve the response to women experiencing domestic violence and abuse, 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.
RESULTS: The IRIS programme saved £14 per woman aged 16 years or older registered in general practice (95% uncertainty interval -£151 to £37) and produced QALY gains of 0.001 per woman (95% uncertainty interval -0.005 to 0.006). The incremental net monetary benefit was positive both from a societal and National Health Service 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 National Institute for Health and Care Excellence.
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, although there is considerable uncertainty surrounding these results, reflected in the large uncertainty intervals.
| Original language | English |
|---|---|
| Article number | e021256 |
| Number of pages | 10 |
| Journal | BMJ Open |
| Volume | 8 |
| Issue number | 8 |
| Early online date | 29 Aug 2018 |
| DOIs | |
| Publication status | Published - Aug 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 5 Gender Equality
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SDG 16 Peace, Justice and Strong Institutions
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Professor Gene S Feder
- Bristol Medical School (PHS) - Professor of Primary Care
- Bristol Population Health Science Institute
- Centre for Academic Primary Care
Person: Academic , Member
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