Despite the rich history of research into medical translation, there is a notable lack of empirical studies on the best workflow for this task, especially in a modern translation setting involving post-editing of machine translation. This pilot study was conducted in preparation for a large translation project of medical guidelines for laypeople from Dutch into French. It is meant to shed light on how medical post-editing is best handled. How do medical specialists (doctors) versus language specialists (translators) perform on this task? How can their respective strengths lead to the highest quality translation? To gain more insight into these questions, errors in the machine translation output of medical guidelines were annotated and labelled. Based on these annotations, the product of doctors' and translators' post-editing could be analysed and classified into necessary changes (mistakes that were correctly solved), under-revisions (mistakes that were not corrected during post-editing), over-revisions (new errors introduced during post-editing) and hyper-revisions (preferential changes made by the post-editor). The results of this small-scale research illustrate the complexity of the task and reveal some surprising findings (e.g., doctors sometimes struggle with domain-specific terminology, and translators appear to be less efficient because they introduce many hyper-revisions).