Bmc Med Inform Decis
-
Bmc Med Inform Decis · Jul 2019
Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department.
Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, emergency department encounters in order to deliver appropriate care and referrals. Unfortunately, falls are difficult to identify without manual chart review, a time intensive process infeasible for many applications including surveillance and quality reporting. Here we describe a pragmatic NLP approach to automating fall identification. ⋯ Our pragmatic NLP algorithm was able to identify falls in ED notes with excellent precision and recall, comparable to that of more labor-intensive manual abstraction. This finding offers promise not just for improving research methods, but as a potential for identifying patients for targeted interventions, quality measure development and epidemiologic surveillance.
-
Bmc Med Inform Decis · Jul 2019
Correction to: The past, present and future of opioid withdrawal assessment: a scoping review of scales and technologies.
Following publication of the original article [1], the authors reported an error in one of the authors' names. In this Correction the incorrect and correct author name are shown. The original publication of this article has been corrected.