Smart medical environment at the point of care: Auto-tracking clinical interventions at the bed side using RFID technology

  • Authors:
  • Kumiko Ohashi;Sakiko Ota;Lucila Ohno-Machado;Hiroshi Tanaka

  • Affiliations:
  • Department of General Medicine, Brigham and Women's Hospital, Harvard Medical School, 1620 Tremont Street, Boston, MA 02120-1613, USA and Tokyo Medical and Dental University, Graduate School of Bi ...;Tokyo Medical and Dental University, Graduate School, Tokyo, Japan;Division of Biomedical Informatics, University of California, San Diego, CA, USA;Tokyo Medical and Dental University, Graduate School of Biomedical Science, Tokyo, Japan

  • Venue:
  • Computers in Biology and Medicine
  • Year:
  • 2010

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Abstract

We developed a wireless auto-tracking system for tracking clinical intervention such as drug administrations and blood tests at the patient bedside. The system can not only authenticate patients and nurses, but also confirm medications and provide relevant information, depending on the clinical situation and personnel location. We conducted a feasibility experiment and examined whether or not the system could work as a patient safety measure in terms of reducing misidentifications of patients and medical errors including wrong medication type, dose, time, and route. Also, the duration of clinical interventions in the system were measured to compare with the BCMA system. Moreover, we conducted a qualitative evaluation with nurses and received feedback clarifying their perceptions of the system. The results showed that the system correctly recognized medical staff, patient ID, and medication data in real time. With regards to workflow time, a significant reduction of time of clinical interventions was observed, when compared to a bar-coding system. In addition, on the nurses' evaluation, we received mostly positive comments although they also clarified some issues to consider with regards to operability and privacy issues. We concluded that the system had great potential for reducing medical errors and nurse workload with high efficiency.