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Improving Clinic Operational Efficiency and Utilization with RTLS

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Journal J Med Syst
Date 2019 Feb 1
PMID 30701407
Citations 12
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Abstract

New sources of operational data are leading to novel healthcare delivery system design and opportunities to support operational planning and decision-making. Technologies such as real time locating systems (RTLS) provide a unique view and understanding of how healthcare delivery settings behave and respond to operational design changes. In this paper RTLS data from an outpatient clinical setting is leveraged to identify the appropriate number of scheduled providers in order to improve the utilization of the clinical space while balancing the negative effects of clinic congestion. The approaches presented pair historical utilization rates for the clinical space with scheduled provider and patient volumes to support scheduling decisions in an operationally flexible clinic design. These historical data are augmented with clinic staff observation logs to identify target utilization rates as well as high congestion levels. Results are presented for two approaches: one where utilization of clinical space is a key performance metric and another where the decision-maker may be risk averse toward the use of provider time and use a probabilistic approach to determine provider staffing levels.

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References
1.
Ostbye T, Lobach D, Cheesborough D, Lee A, Krause K, Hasselblad V . Evaluation of an infrared/radiofrequency equipment-tracking system in a tertiary care hospital. J Med Syst. 2003; 27(4):367-80. DOI: 10.1023/a:1023709421380. View

2.
Chen C, Liu C, Li Y, Chao C, Liu C, Chen C . Pervasive Observation Medicine: The Application of RFID to Improve Patient Safety in Observation Unit of Hospital Emergency Department. Stud Health Technol Inform. 2005; 116:311-5. View

3.
Wicks A, Visich J, Li S . Radio frequency identification applications in hospital environments. Hosp Top. 2006; 84(3):3-8. DOI: 10.3200/HTPS.84.3.3-9. View

4.
Rohleder T, Bischak D, Baskin L . Modeling patient service centers with simulation and system dynamics. Health Care Manag Sci. 2007; 10(1):1-12. DOI: 10.1007/s10729-006-9001-8. View

5.
Booth P, Frisch P, Miodownik S . Application of RFID in an integrated healthcare environment. Conf Proc IEEE Eng Med Biol Soc. 2007; 2006:117-9. DOI: 10.1109/IEMBS.2006.259389. View