Poor usability of health information systems has been described to cause frustration and contribute to patient safety incidents. Yet, the impact of such features on usability remains unclear.

Some systems utilised automated reasoning (AR) to enable more intelligent task management functionalities, such as automated task allocation. Presented as a combination of synthesis of ideas and past works, proposals for future research, and our perspectives on technical, social, and ethical considerations, this paper is meant to help revitalize the interest and future work in task-based IR.Įlectronic clinical task management systems (ECTMSs) have been developed and adopted by care providers to improve care coordination.

To ground ongoing and future research in this area, we present a new framing device for tasks using a tree-like structure and various moves on that structure that allow different interpretations and applications. In addition to covering relevant literature, the paper provides a synthesis of historical and current perspectives on understanding, extracting, and addressing task-focused search.

In this paper, we provide various perspectives on where the state-of-the-art is with regard to tasks in IR, what are some of the bottlenecks in deriving and using task information, and how do we go forward from here. With emerging areas of conversational agents and proactive IR, understanding and addressing users' tasks has become more important than ever before. But for the most part, the IR community has been too focused on query processing and assuming a search task to be a collection of user queries, often ignoring if or how such an assumption addresses the users accomplishing their tasks. For decades, scholars made a case for the role that a user's task plays in how and why that user engages in search and what a search system should do to assist. The importance of tasks in information retrieval (IR) has been long argued for, addressed in different ways, often ignored, and frequently revisited.

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