1. Clinical questions and information needs

Automatically extracting information needs from complex clinical questions

OBJECTIVE Clinicians pose complex clinical questions when seeing patients, and identifying the answers to those questions in a timely manner helps improve the quality of patient care. We report here on two natural language processing models, namely, automatic topic assignment and keyword identification, that together automatically and effectively extract information needs from ad hoc clinical q...

Automatically Extracting Information Needs from Ad Hoc Clinical Questions

Automatically extracting information needs from ad hoc clinical questions is an important step towards medical question answering. In this work, we first explored supervised machine-learning approaches to automatically classify an ad hoc clinical question into general topics. We then evaluated different methods for automatically extracting keywords from an ad hoc clinical question. Our methods ...

Bundles: meeting clinical information needs.

Asking questions: information needs in a surgical intensive care unit

Even in the information-rich environment of hospitals, health-care providers face challenges in addressing their various information needs. Through a study of a patient-care team in a tertiary care Surgical Intensive Care Unit (SICU), we expanded our understanding of health-care providers' information needs in two important ways. First, the study focused on a patient-care team instead of indivi...

Three Questions About Clinical Information Retrieval

Electronic Medical Records (EMRs) have greatly expanded the potential for the evidence-based improvement of clinical practice by providing a data source for computable medical information. The Text REtrieval Conference 2012 Medical Records Track (TREC-med) explored how information retrieval may support clinical research by providing an efficient means to identify cohorts for clinical studies. A...