Abstract
Time-motion (TM) studies are often considered the gold-standard for measurements of the impact of computer systems on task flow and duration. However, in many clinical environments tasks occur too rapidly and have too short of a duration to be captured with conventional paper-based TM methods. Observers may also with to categorize caregiver activities along multiple axes simultaneously. This multi-axial characteristic of clinical activity has been modeled as multiple, parallel finite-state sets and implemented in three computerized data collection tools. Radiology reporting is a domain in which tasks can be characterized by multiple attributes. A radiologist may also switch among multiple tasks in a single minute. The use of these tools to measure the impact of an Automated Speech Recognition (ASR) system on Radiology reporting is presented.
Original language | English (US) |
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Pages (from-to) | 833-837 |
Number of pages | 5 |
Journal | Proceedings / AMIA ... Annual Symposium. AMIA Symposium |
State | Published - 2000 |
ASJC Scopus subject areas
- General Medicine