Search

Building high-quality annotated clinical corpora is necessary for developing statistical Natural Language Processing (NLP) models to unlock information embedded in clinical text, but it is also time consuming and expensive. Consequently, it important to identify factors that may affect annotation time, such as syntactic complexity of the text- to-be-annotated and the vagaries of individual user behavior. However, limited work has been done to understand annotation of clinical text. In this study, we aimed to investigate how factors inherent to the text affect annotation time for a named entity recognition (NER) task. We recruited 9 users to annotate a clinical corpus and recorded annotation time for each sample. Then we defined a set of factors that we hypothesized might affect annotation time, and fitted them into a linear regression model to predict annotation time. The linear regression model achieved an R(2) of 0.611, and revealed eight time-associated factors, including characteristics of sentences, individual users, and annotation order with implications for the practice of annotation, and the development of cost models for active learning research.

Interruptions are an often lamented and frequently studied aspect of clinical practice. However, some interruptions, such as updates on patient care decisions and notifications of detrimental patient lab values, are in fact necessary to the work process. In this paper, we explore the interruptions as an emergent feature of communication in teams. Looking beyond the frequency of interruptions, we consider the source and intent of interruptions with the goal of discovering the functions served by such communications. Furthermore, in this study of an emergency department, we classify interruptions into those activities that support required work and those interruptions that create unnecessary breaks in workflow. The intent of our larger body of work is to develop health information technology systems that support team efforts including the functions currently served by interruptions.

Online courses will play a key role in the high-volume Informatics education required to train the personnel that will be necessary to fulfill the health IT needs of the country. Online courses can cause feelings of isolation in students. A common way to address these feelings is to hold synchronous online “chats” for students. Conventional chats, however, can be confusing and impose a high extrinsic cognitive load on their participants that hinders the learning process. In this paper we present a qualitative analysis that shows the causes of this high cognitive load and our solution through the use of a moderated chat system.