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Deirdre O ’ Brien , Research Fellow, Health Economics Unit

Can paying for outcomes be effective in target subgroups? A cluster controlled study of smoking cessation pilots in the NHS. Deirdre O ’ Brien , Research Fellow, Health Economics Unit Co-Authors: Hugh McLeod, Steven Wyatt, Mohammed A. Mohammed Date: 26.06.2013. NHS Stop Smoking Services.

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Deirdre O ’ Brien , Research Fellow, Health Economics Unit

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  1. Can paying for outcomes be effective in target subgroups? A cluster controlled study of smoking cessation pilots in the NHS Deirdre O’Brien, Research Fellow, Health Economics Unit Co-Authors: Hugh McLeod, Steven Wyatt, Mohammed A. Mohammed Date: 26.06.2013

  2. NHS Stop Smoking Services • Effective & cost-effective • Provide behavioural & pharmaceutical support • Widely rolled out since 2001 • Help reduce health inequalities • Commissioned through fixed contracts • Currently undersupplied: • Only accessed by 6% of smokers & 5% of pregnant smokers

  3. Rational for change

  4. The Intervention • First tariff of this kind in the NHS • All income linked to outcomes • Enhanced tariffs for target populations • No income cap • Introduced Any Qualified Provider (AQP) Regulation • Encourage new market entrance

  5. Tariffs for reported Quits • Higher tariffs when prescribing charges incurred • In pregnancy, standard tariffs apply after 24th week

  6. Implementation

  7. Research Question Can paying for outcomes be effective in target subgroups? • Effective at aggregate level • Led to two-fold increase in quits/population • Examine effect on non-white British smokers • Smoking rates < 30% in black Caribbean, Bangladeshi & Chinese males • Examine effect on pregnant women • High risk of poor maternal & infant outcomes • Smoking rates vary between 4% -30%

  8. Design: Matched cluster controlled study Intervention • 8 volunteer PCTs Intervention • 64 control PCTs Control 2010 • Difference in rate of change in 4 week quits: • non-white British populations • Pregnant women Outcome measures Control • Routine NHS SSS data • ONS population statistics Data Sources • Mixed effect Poisson regression models • Incident rate ratio (IRR) Analysis

  9. Controls derived using ONS clusters Rational: • Similar local population demographics • 1000 population used as a denominator

  10. NWB and pregnant women represent a small proportion of quits 4 week quits in intervention PCTs in 2011/12

  11. Results at Aggregate Level (submitted for publication) • Two-fold increase in the change in 4 week quits per 1000 population • 11% per year in intervention PCTs, compared to 5% per year in controls • Incident rate ratio 1.056, p=0.006, CI 1.016 to 1.098

  12. Non-white British smokers

  13. Non-white British smokers • Outcome similar to aggregate results • Positive effect on NWB smokers • 26% per year in intervention PCTs • 14% per year in controls • Incident rate ratio 1.104, p=0.093, CI 0.983 to 1.240

  14. Pregnant Women

  15. Pregnant Women • Little difference for pregnant women • 13% per year in intervention PCTs, • 11% per year in controls • Incident rate ratio 1.019, p=0.784, CI 0.888 to 1.170

  16. Enhanced tariffs had different effects on the two target subgroups • Appeared to increase supply & effectiveness of NHS SSS in NWB smokers • No evidence of effect in pregnant women 16

  17. Possible explanations Non-white British • Better Reporting • Enhanced tariffs incentivised targeting • Any Qualified Provider regulation • New providers able to reach niche groups Pregnant women • Outcome measured did not capture full effect • Stage of pregnancy & if sustained • Barriers to market entry • Enhanced tariffs not high enough • Targeting of this group in controls

  18. Opportunities for further research.. • Change in other outcomes • 12 week quits • Effects on other target groups • Pregnant women • Exploring reasons for lack of effect • Quits in first & second trimesters • Quits sustained until birth

  19. Questions

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