Background Cochrane aims to make high-quality health information accessible for users worldwide (Chandler et al. 2017). To this end, contributors simplify Systematic Reviews into Plain Language Summaries (PLS), which are translated (Cochrane Community 2016). Simplification and translation may represent onerous and time-consuming tasks when conducted without assistance from technology. Contributors produce PLS by manually implementing a written set of guidelines (Cochrane Methods 2013) and translations are mainly produced by volunteers (Cochrane Community 2016). Cochrane is considering using machine translation (MT) systems and controlled language (CL) checkers (Birch 2017; Von Elm et al. 2013). A CL is a set of rules adopted to make a text more comprehensible and translatable. A CL checker is the software that checks for adherence to those rules (O’Brien 2010). The adoption of a CL at the authoring stage can increase machine translatability and reduce the effort required to correct the MT outputs (Allen 2003). Objectives This study investigated if introducing a CL checker called Acrolinx in the authoring process of PLS increases the quality of the Spanish translations of PLS produced by Google Translate, a freely available MT system. Method and Materials The experimental materials were: a corpus of 12 PLS authored by manually implementing Cochrane guidelines and their Spanish MT translations; and a corpus of 12 PLS authored with assistance from Acrolinx and their Spanish MT translations. 41 Spanish native speakers conducted the MT evaluation task. Each evaluator was given two PLS (one per corpus) and their Spanish MT outputs. Evaluators assigned scores to the Spanish outputs on fluency and adequacy, commonly employed in MT quality evaluation (Castilho et al. 2017). Results and Conclusions There was little difference in fluency and adequacy scores between the two corpora of PLS, possibly because neither approach to simplification had been developed with MT quality in mind. Moreover, fluency and adequacy scores were relatively high, suggesting that the MT system produced reasonably good translations. While human validation/correction of the MT output is needed for accuracy, the high adequacy and fluency scores for Spanish indicate that integrating MT in the translation workflow might be a viable option. Further studies should be conducted on other language pairs.