Are financial incentives cost‐effective to support smoking cessation during pregnancy?. (11th November 2015) - Boyd, Kathleen A.; Briggs, Andrew H.; Bauld, Linda; Sinclair, Lesley; Tappin, David
Abstract: Aims: To investigate the cost‐effectiveness of up to £400 worth of financial incentives for smoking cessation in pregnancy as an adjunct to routine health care. Design: Cost‐effectiveness analysis based on a Phase II randomized controlled trial (RCT) and a cost–utility analysis using a life‐time Markov model. Setting: The RCT was undertaken in Glasgow, Scotland. The economic analysis was undertaken from the UK National Health Service (NHS) perspective. Participants: A total of 612 pregnant women randomized to receive usual cessation support plus or minus financial incentives of up to £400 vouchers (US 609), contingent upon smoking cessation. Measurements: Comparison of usual support and incentive interventions in terms of cotinine‐validated quitters, quality‐adjusted life years (QALYs) and direct costs to the NHS. Findings: The incremental cost per quitter at 34–38 weeks pregnant was £1127 (1716).This is similar to the standard look‐up value derived from Stapleton & West's published ICER tables, £1390 per quitter, by looking up the Cessation in Pregnancy Incentives Trial (CIPT) incremental cost (£157) and incremental 6‐month quit outcome (0.14). The life‐time model resulted in an incremental cost of £17 [95% confidence interval (CI) = –£93, £107] and a gain of 0.04 QALYs (95% CI = –0.058, 0.145), giving an ICER of £482/QALY (734/QALY). Probabilistic sensitivity analysis indicates uncertainty in these results, particularly regarding relapse after birth. The expected value of perfect information was £30 million (at a willingness to pay of £30 000/QALY), so given current uncertainty, additional research is potentially worthwhile. Conclusion: Financial incentives for smoking cessation in pregnancy are highly cost‐effective, with an incremental cost per quality‐adjusted life years of £482, which is well below recommended decision thresholds.