June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
Designing a portable automated system for continuously measuring patient wait times, a quality improvement approach to improving glaucoma care
Author Affiliations & Notes
  • John Albert Musser
    Glaucoma, University of Michigan - Kellogg Eye Center, Livonia, Michigan, United States
  • Amitava Shee
    Glaucoma, University of Michigan - Kellogg Eye Center, Livonia, Michigan, United States
  • Long Zhang
    Glaucoma, University of Michigan - Kellogg Eye Center, Livonia, Michigan, United States
  • Leslie M Niziol
    Glaucoma, University of Michigan - Kellogg Eye Center, Livonia, Michigan, United States
  • Abhilash Rao
    Glaucoma, University of Michigan - Kellogg Eye Center, Livonia, Michigan, United States
  • David Burke
    Glaucoma, University of Michigan - Kellogg Eye Center, Livonia, Michigan, United States
  • Nish Patel
    Glaucoma, University of Michigan - Kellogg Eye Center, Livonia, Michigan, United States
  • Shivani Kamat
    Glaucoma, University of Michigan - Kellogg Eye Center, Livonia, Michigan, United States
  • Manjool Shah
    Glaucoma, University of Michigan - Kellogg Eye Center, Livonia, Michigan, United States
  • Steve Gendler
    Glaucoma, University of Michigan - Kellogg Eye Center, Livonia, Michigan, United States
  • Amy Cohn
    Glaucoma, University of Michigan - Kellogg Eye Center, Livonia, Michigan, United States
  • Paula Anne Newman-Casey
    Glaucoma, University of Michigan - Kellogg Eye Center, Livonia, Michigan, United States
  • Footnotes
    Commercial Relationships   John Musser, None; Amitava Shee, None; Long Zhang, None; Leslie Niziol, None; Abhilash Rao, None; David Burke, None; Nish Patel, None; Shivani Kamat, None; Manjool Shah, None; Steve Gendler, None; Amy Cohn, None; Paula Anne Newman-Casey, Blue Health Intelligence (C)
  • Footnotes
    Support  National Institute of Health 1K23EY025320, Research to Prevent Blindness
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 5045. doi:
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      John Albert Musser, Amitava Shee, Long Zhang, Leslie M Niziol, Abhilash Rao, David Burke, Nish Patel, Shivani Kamat, Manjool Shah, Steve Gendler, Amy Cohn, Paula Anne Newman-Casey; Designing a portable automated system for continuously measuring patient wait times, a quality improvement approach to improving glaucoma care. Invest. Ophthalmol. Vis. Sci. 2017;58(8):5045.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Nearly 50% of glaucoma patients are noncompliant with their medications. Inadequate patient education and poor attendance at follow up visits have been associated with noncompliance. 75% of glaucoma patients stated that long wait times were a significant barrier for attending return visits. We designed a radio frequency identification (RFID) continuous monitoring system to identify ideal times for integrating glaucoma education sessions into the patient visit and to advise process changes to decrease wait times.

Methods : ThingMagic Astra-Ex Ultra High Frequency (UHF, 865 MHz-960 MHz) RFID readers were tested with Impinj Monza 4QT UHF RFID tags worn on lanyards. A management software interface was designed to monitor the status of each RFID reader via discrete internet protocol connections. RFID tag data, including signal strength (dBm) and time, was buffered into a MySQL relational database prior to transfer into a network file system. Tests were performed to obtain a better understanding of tag signal strength at different distances from the RFID reader (up to 9 feet, as in an exam lane between patient and provider), sampling settings of the readers, and environments mimicking a patient visit to the glaucoma clinic.

Results : Clinic room RFID reader testing with no line of sight obstacles at 1, 2, 4, 6, and 9 feet yielded an average (n=5 trials) signal strength of -27 [+/- 0.75], -33 [+/- 1.38], -44 [+/- 0.98], -46 [+/- 2.06], and -53 [+/- 2.13] dBm respectively for a 0.5s sampling rate and -28 [+/0 1.90], -34 [+/- 1.08], -44 [+/- 0.74], -46 [+/- 1.49], and -51 [+/- 2.92] for a max sampling rate (approximately 10 times per second). The signal strength was not meaningfully different between the two sampling rates. The signal strength of a tag decreased the further away it was from the RFID reader. The slit lamp caused interference with signal strength. At 9 feet, it attenuated the strength for 0.5s sampling from an average of -53 dBm to an average of -67 dBm. A tag read outside the clinic door exhibited an average signal strength (n=5 trials) of -68.5 dBm for 0.5s sampling and -68.9 dBm at max sampling rate.

Conclusions : UHF RFID technology has the capability to determine patient-provider presence in the clinical setting using signal strength when protocols are optimized to allow for equipment interference.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

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