Our aim was to examine whether the length of stay, hospital charges and in-hospital mortality attributable to healthcare- and community-associated infections due to antimicrobial-resistant bacteria were higher compared with those due to susceptible bacteria in the Lebanese healthcare settings using different methodology of analysis from the payer perspective . We performed a multi-centre prospective cohort study in ten hospitals across Lebanon. The sample size consisted of 1289 patients with documented healthcare-associated infection (HAI) or community-associated infection (CAI). We conducted three separate analysis to adjust for confounders and time-dependent bias: (1) Post-HAIs in which we included the excess LOS and hospital charges incurred after infection and (2) Matched cohort, in which we matched the patients based on propensity score estimates (3) The conventional method, in which we considered the entire hospital stay and allocated charges attributable to CAI. The linear regression models accounted for multiple confounders. HAIs and CAIs with resistant versus susceptible bacteria were associated with a significant excess length of hospital stay (2.69 days 95% CI,1.5-3.9; p < 0.001) and (2.2 days 95% CI,1.2-3.3; p < 0.001) and resulted in additional hospital charges ($1807 95% CI, 1046-2569; p < 0.001) and ($889 95% CI, 378-1400; p = 0.001) respectively. Compared with the post-HAIs analysis, the matched cohort method showed a reduction by 26 and 13% in hospital charges and LOS estimates respectively. Infections with resistant bacteria did not decrease the time to in-hospital mortality, for both healthcare- or community-associated infections. Resistant cases in the post-HAIs analysis showed a significantly higher risk of in-hospital mortality (odds ratio, 0.517 95% CI, 0.327-0.820; p = 0.05). This is the first nationwide study that quantifies the healthcare costs of antimicrobial resistance in Lebanon. For cases with HAIs, matched cohort analysis showed more conservative estimates compared with post-HAIs method. The differences in estimates highlight the need for a unified methodology to estimate the burden of antimicrobial resistance in order to accurately advise health policy makers and prioritize resources expenditure.