Keywords: propensity score, inverse probablility treatment weight, selection bias
The goal of this project is to understand potential selection bias in a non-randomized smoking cessation intervention by evaluating three methods. METHODS: A hospital-based tobacco dependence treatment service (TDTS) was implemented to provide bedside and phone follow-up consultations. Thirty-day readmission was compared using: 1) regression with covariate adjustment, 2) inverse probability of treatment weighted (IPTW) propensity score regression with no adjustment and 3) IPTS score regression with covariate adjustment. RESULTS: 1640 received TDTS and 1441 smokers did not. When using method 1, TDTS was significant with a 25% reduction in odds of readmission (p=.015) compared to no intervention. After method 2 results remained significant with a 21% lower odds (p= .043). However, after method 3 the statistical significance approached the a-level with no effect size change (21%, p= .048). CONCLUSION: The use of IPTW indicated that there appeared to be selection bias between those that received TDTS service and those that did not. Even when controlling for the probability of receiving service, without also controlling for potential confounders, treatment effect can be inflated.