ObjectivesCommunity-Based Rehabilitation (CBR) is a multi-sectoral approach working to equalise opportunities and include people with disabilities in all aspects of life. The complexity of CBR and often limited resources lead to challenges when attempting to quantify its effectiveness, with randomisation and longitudinal data rarely possible. Statistical methods, such as propensity score matching (PSM), offer an alternative approach to evaluate a treatment when randomisation is not feasible. The aim of this study is to examine whether PSM can be an effective method to facilitate evaluations of results in CBR when data are cross-sectional.DesignCross-sectional survey.Setting and participantsData were collected using the WHO’s CBR Indicators in Vietnam, with treatment assignment (participating in CBR or not) determined by province of residence. 298 participants were selected through government records.ResultsPSM was conducted using one-to-one nearest neighbour method on 10 covariates. In the unmatched sample, significant differences between groups were found for six of the 10 covariates. PSM successfully adjusted for bias in all covariates in the matched sample (74 matched pairs). A paired t-test compared the outcome of ‘community inclusion’ (a score based on selected indicators) between CBR and non-CBR participants for both the matched and unmatched samples, with CBR participants found to have significantly worse community inclusion scores (mean=17.86, SD=6.30, 95% CI 16.45 to 19.32) than non-CBR participants (mean=20.93, SD=6.16, 95% CI 19.50 to 22.35); t(73)=3.068, p=0.001. This result did not differ between the matched and unmatched samples.ConclusionPSM successfully reduced bias between groups, though its application did not affect the tested outcome. PSM should be considered when analysing cross-sectional CBR data, especially for international comparisons where differences between populations may be greater.