FEATURE ARTICLERadiofrequency Identification: Exploiting an Old Technology for Measuring Nurse Time and MotionJONES, TERRY L. PhD, RNAuthor Information Author Affiliation: Assistant Professor, The University of Texas at Austin. This manuscript was supported by grant UL1RR024982, entitled “North and Central Texas Clinical and Translational Science Initiative” (Milton Packer, MD, principal investigator), from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH) and NIH Roadmap for Medical Research. The contents of this article are solely the responsibility of the author and do not necessarily represent the official view of the NCRR or NIH. Information on NCRR is available at http://www.ncrr.nih.gov/. Information on Re-engineering the Clinical Research Enterprise can be obtained from http://nihroadmap.nih.gov/clinicalresearch/overview-translational.asp. The author has disclosed that she has no significant relationship with, or financial interest in, any commercial companies pertaining to this article. Corresponding author: Terry L. Jones, PhD, RN, 1700 Red River Austin, TX 78701 (email@example.com). CIN: Computers, Informatics, Nursing: September 2012 - Volume 30 - Issue 9 - p 463-472 doi: 10.1097/NXN.0b013e3182545418 Buy Take the CE Test Metrics Abstract A national campaign is underway to increase the amount of time staff nurses spend at the bedside of hospitalized patients through redesign of the work environment. This kind of work redesign requires robust data depicting what nurses do and how they spend their time. Historically, these kinds of data have been difficult, costly, and time consuming to collect. Wireless capture of data on the movement of humans within the work environment (ie, time and motion) is now possible through radiofrequency identification technology. When small tracking devices the size of a quarter are affixed to their clothing, the movement of nurses throughout a patient care unit can be monitored. The duration and frequency of patient interaction are captured along with the duration of time spent in other locations of interest to include nurses’ station, supply room, medication room, doctors’ station, electronic documentation stations, family waiting rooms, and the hallway. Patterns of nurse movement and time allocation can be efficiently identified, and the effects of staffing practices, workflows, and unit layout evaluated. Integration of radiofrequency identification time and motion data with other databases enables nurse leaders to link nursing time to important cost and quality outcomes. Nurse leaders should explore the usefulness of radiofrequency identification technology in addressing data needs for nurse time and motion. © 2012 Lippincott Williams & Wilkins, Inc.