Process Mining (PM) is a relatively new field which provides techniques to analyze business processes in different areas. In the field of Medicine, PM seeks to infer clinical processes from the data routinely collected during healthcare activities. In most frameworks, workflows are used to represent the results obtained by PM techniques. A problem with these workflows is that their structure is complex and not always easy to understand and hence to exploit by the clinician. A different problem, related to Clinical Practice Guidelines (CPGs), is that their development is mostly manual. We posit that workflows inferred by PM techniques could be improved and enriched by providing interactive tools to support their structuring and semantic annotation by clinicians. We also postulate that these improved and enriched models can be used to facilitate the development of CPGs. In this paper we describe our approach to the interactive discovery of clinical processes as well as an implementation to support it within the PMApp PM tool.