OBJECTIVES: To compare efficacy, safety and consumption of low-molecular-weight heparins (LMWHs) in Lithuania and to develop pharmacoeconomic decision model based on meta-analysis data.   METHODS: Review and meta-analysis of published randomized control trials which directly compared the safety and efficacy of low molecular weight heparins (LMWH) i.e. Nadroparin, Enoxaparin, Dalteparin, was conducted by two independent reviewers using inclusion/exclusion criteria based on the objectives of research. Statistical software MedCalc was used to perform the estimations of the following values. We calculated the value of fixed effects and random effects odds ratio (95% confidence interval (CI)) for each trial for the composite end point. Afterwards, pharmacoeconomic decision modelling was implemented, which was based on meta-analysis data. Cost-minimization assay was accomplished using reference pricing methodology. RESULTS: Enoxaparin vs. Dalteparin: 4 studies, involving 471 patients, were eligible (fixed effects odds ratio 1.447 [95% CI 0.957 – 2.281]). Nadroparin vs. Enoxaparin: 3 studies, involving 1118 patients, were involved (fixed effects odds ratio 1.360 [95% CI 1.050 – 1.762]). Dalteparin vs. Nadroparin: 2 studies, involving 294 patients, were eligible (fixed effects odds ratio 0.577 [95% CI 0.337 – 0.988]). None of low-molecular-weight heparins demonstrated significant superiority when compared with each other, so group of LMWHs was suitable for pharmacoeconomic analysis and reference pricing implementation. Dalteparin single DDD price was set as reference price, as it was the least expensive option. Introducing the reference pricing for low-molecular-weight heparins would result in total savings of 1,830-2,070 thousand LTL in Lithuania yearly. The implementation of reference pricing would enable to decrease the total expenditures on LMWHs by 29.28% - 31.98%. CONCLUSIONS: In the accomplished meta-analysis, none of low-molecular-weight heparins demonstrated significant superiority when compared with each other. Meta-analysis results could be applied to support pharmacoeconomic decision-modelling and that would allow decreasing health-care expenditures in the whole country.