Paula Anne Newman-Casey1, John Musser2, Leslie M Niziol2, Kerby Shedden3, David Burke4, Amy Cohn5. 1. Department of Ophthalmology & Visual Sciences, University of Michigan Medical School, MI, United States. Electronic address: panewman@med.umich.edu. 2. Department of Ophthalmology & Visual Sciences, University of Michigan Medical School, MI, United States. 3. Department of Statistics, University of Michigan, Ann Arbor, MI, United States. 4. Department of Human Genetics, University of Michigan Medical School, MI, United States. 5. Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI, United States.
Abstract
OBJECTIVE: Outpatient clinics lack infrastructure to easily measure and understand patient wait times. Our objective was to design a low-cost, portable passive real time locating system within an outpatient clinic setting to measure patient wait times and patient-provider interactions. MATERIALS AND METHODS: Direct observation was used to determine workflow in an outpatient glaucoma clinic at the University of Michigan. We used off-the shelf, antenna-integrated ultra-high frequency (UHF) RFID readers (ThingMagic, Astra-Ex, Woburn, MA) and UHF re-useable passive RFID tags (Zebra Impinj Monza 4QT, Seattle, WA). We designed a custom RFID management application in the Java programming language that was equipped with 'live' device administration to collect time and location data from patients and providers. These hardware choices enabled low cost system installation. Hidden Markov Modeling (HMM) was used to smooth patient and provider location data. Location data were validated against direct observations and EHR evaluation. RESULTS: The HMM smoothed RFID system data accurately predicted patient location 80.6% of the time and provider location 79.1% of the time, compared to direct observation locations, an improvement over the raw RFID location data (65.0% and 77.9% accurate, respectively). Patient process time was on average 42.8 min (SD = 27.5) and wait time was 47.9 min (SD = 33.1). The installation and recurring capital costs of the system are approximately 10% of available commercially-supplied patient/provider tracking systems. DISCUSSION: Passive RFID time study systems can enable real-time localization of people in clinic, facilitating continuous capture of patient wait times and patient-provider interactions. The system must be tailored to the clinic to accurately reflect patient and provider movement. CONCLUSIONS: Capturing wait time data continuously and passively can empower continuous clinical quality improvement initiatives to enhance the patient experience.
OBJECTIVE:Outpatient clinics lack infrastructure to easily measure and understand patient wait times. Our objective was to design a low-cost, portable passive real time locating system within an outpatient clinic setting to measure patient wait times and patient-provider interactions. MATERIALS AND METHODS: Direct observation was used to determine workflow in an outpatientglaucoma clinic at the University of Michigan. We used off-the shelf, antenna-integrated ultra-high frequency (UHF) RFID readers (ThingMagic, Astra-Ex, Woburn, MA) and UHF re-useable passive RFID tags (Zebra Impinj Monza 4QT, Seattle, WA). We designed a custom RFID management application in the Java programming language that was equipped with 'live' device administration to collect time and location data from patients and providers. These hardware choices enabled low cost system installation. Hidden Markov Modeling (HMM) was used to smooth patient and provider location data. Location data were validated against direct observations and EHR evaluation. RESULTS: The HMM smoothed RFID system data accurately predicted patient location 80.6% of the time and provider location 79.1% of the time, compared to direct observation locations, an improvement over the raw RFID location data (65.0% and 77.9% accurate, respectively). Patient process time was on average 42.8 min (SD = 27.5) and wait time was 47.9 min (SD = 33.1). The installation and recurring capital costs of the system are approximately 10% of available commercially-supplied patient/provider tracking systems. DISCUSSION: Passive RFID time study systems can enable real-time localization of people in clinic, facilitating continuous capture of patient wait times and patient-provider interactions. The system must be tailored to the clinic to accurately reflect patient and provider movement. CONCLUSIONS: Capturing wait time data continuously and passively can empower continuous clinical quality improvement initiatives to enhance the patient experience.
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