Title: Can%20paying%20for%20outcomes%20be%20effective%20in%20target%20subgroups?%20%20A%20cluster%20controlled%20study%20of%20smoking%20cessation%20pilots%20in%20the%20NHS
1Can paying for outcomes be effective in target
subgroups? A cluster controlled study of
smoking cessation pilots in the NHS
- Deirdre OBrien, Research Fellow, Health
Economics Unit - Co-Authors Hugh McLeod, Steven Wyatt, Mohammed
A. Mohammed - Date 26.06.2013
2NHS 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
3Rational for change
4The 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
5Tariffs for reported Quits
Standard Tariffs Standard Tariffs Tariff for pregnant women before 24 weeks Tariff for pregnant women before 24 weeks
Non-Target Target Non-Target Target
4 week No Prescribing Costs 94 136 216 425
12 week No Prescribing Costs 129 271 395 566
- Higher tariffs when prescribing charges incurred
- In pregnancy, standard tariffs apply after 24th
week
6Implementation
7Research 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 lt 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
8Design Matched cluster controlled study
Intervention
Intervention
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
9Controls derived using ONS clusters
ONS subgroup Cluster No of control PCTs No of Intervention PCTs
Centres with industry A 1 9 2
Centres with industry B 2 7 1
Industrial Hinterland A 3 14 1
Manufacturing Towns A 4 13 1
Prospering Smaller Towns B 5 12 1
Prospering Smaller Towns C 6 9 2
- Rational
- Similar local population demographics
- 1000 population used as a denominator
10NWB and pregnant women represent a small
proportion of quits
4 week quits in intervention PCTs in 2011/12
11Results 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, p0.006, CI 1.016 to
1.098
12Non-white British smokers
13Non-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, p0.093, CI 0.983 to
1.240
14Pregnant Women
15Pregnant Women
- Little difference for pregnant women
- 13 per year in intervention PCTs,
- 11 per year in controls
- Incident rate ratio 1.019, p0.784, CI 0.888 to
1.170
16Enhanced 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
17Possible 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
18Opportunities 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
19Questions