The Chilean Waiting List Corpus

Referrals from the waiting list for several specialty consultations in Chilean public hospitals were used to create a de-identified clinical corpus. A subset of 900 referrals was manually annotated with entities, attributes, and relations with clinical relevance. A trained medical doctor annotated these referrals, and then together with other three researchers, consolidated each of the annotations. The annotated corpus has nested entities, with 32.2% of entities embedded in other entities. 
In this work we describe the Waiting List Corpus, the annotation process, and preliminary results for Named Entity Recognition (NER). The best results were obtained using a biLSTM-CRF architecture using word embeddings trained over  Spanish Wikipedia together with clinical embeddings computed by the group. NER models applied to this corpus can leverage statistics of diseases and pending procedures within the waiting list. This work constitutes the first annotated corpus using clinical narratives from Chile, and one of the few for the Spanish language. The annotated corpus, the clinical word embeddings, and the annotation guidelines are freely released to the research community.