OBJECTIVES: To reduce recruitment bias in an observational study by the propensity score (PS) matching method. METHODS: PREMISS is a prospective, multicentric pre-post study aiming at the evaluation of drotrecogin alfa (DA) in the treatment of severe sepsis with multiple organ failure. In observational studies, there is a need to control for recruitment bias. We decided to improve patient comparability by performing a PS optimal matching. PS was estimated using logistic regression after performing multiple imputation to handle missing patient characteristics. Each control was matched to a DA patient so that the sum of the PS distances was minimal. Three PS models were estimated and their performance compared: the first included all patient characteristics, the second only those being unbalanced, the third completed the second with interaction terms. RESULTS: A total of 1096 patients were retained in the whole sample, with strong evidence of recruitment bias. Forty-six initial characteristics were measured. A total of 22.8% of the patients had at least one missing characteristic. Once matched, respectively 76.6%, 79.4%, and 68.2% of patients were retained in the sample for PS models n° 1, 2, and 3. The first PS model performed better in reducing recruitment bias, only two indicators being slightly unbalanced (versus 4 and 5 indicators in the second and third models). In the resulting matched sample, adjusting for organ dysfunction (i.e. the LODS quartiles), survival estimates were similar, at the cost of multiple adjustments, to those obtained in the whole sample. CONCLUSION: Despite the growing popularity of the PS approach, the best method to estimate it remains unclear. In this particular study, simply including all patient characteristics, with no interaction terms, yielded the best results. More complicated processes, implying variable selection and interaction terms, were counterproductive.