Designing and validating a low-cost real time locating system to continuously assess patient wait times

Newman-Casey, Paula Anne; Musser, John A; Niziol, Leslie M.; Shedden, Kerby; Burke, David T.; Cohn, Amy M.

doi:10.1016/j.jbi.2020.103428

Cited by 12 publications

(11 citation statements)

References 14 publications

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“…The RTLS system development process is described in greater technical detail in a previous publication [ 19 ]. To summarize, the RTLS uses passive radiofrequency identification (RFID) tags and sensors to achieve high reliability and localization accuracy at a low cost [ 19 ].…”

Section: Methodsmentioning

confidence: 99%

“…Hidden Markov Modelling was used to reduce noise from the data. The Hidden Markov Modeling smoothed RFID system data had an accuracy of 80.6% for patient location and 79.1% for provider location compared to direct observations [ 19 ].…”

Section: Methodsmentioning

confidence: 99%

“…The system should also be capable of providing granular workflow data, including non-EHR captured activities, in real-time to allow for rapid clinical optimization [ 9 , 17 , 18 ]. In the Kellogg Eye Center glaucoma clinic, we designed and validated a real-time locating system (RTLS) that automatically conducts continuous time-and-motion studies to assess wait and process times [ 19 ]. The RTLS provides detailed real-time workflow information for EHR and non-EHR captured activities at a fraction of the cost of manual observation [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

“…In the Kellogg Eye Center glaucoma clinic, we designed and validated a real-time locating system (RTLS) that automatically conducts continuous time-and-motion studies to assess wait and process times [ 19 ]. The RTLS provides detailed real-time workflow information for EHR and non-EHR captured activities at a fraction of the cost of manual observation [ 19 ]. The described study had two objectives: 1) develop a lean-analysis guided policy change to improve clinical workflow, and 2) use the RTLS system to measure the impact of that policy change.…”

Section: Introductionmentioning

confidence: 99%

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Measuring impact of a quality improvement initiative on glaucoma clinic flow using an automated real-time locating system

et al. 2022

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Background Lean methodology helps maximize value by reducing waste, first by defining what value and waste are in a system. In ophthalmology clinics, value is determined by the number of patients flowing through the clinic for a given time. We aimed to increase value using a lean-methodology guided policy change, then assessed its impact on clinic flow using an automated radiofrequency identification (RFID) based real-time locating system (RTLS). Methods A total of 6813 clinical visits occurred at a single academic institution’s outpatient glaucoma clinic between January 5, 2018 to July 3, 2018. Over that period, 1589 patients comprising 1972 (29%) of visits were enrolled, with 1031 clinical visits occurring before and 941 visits after a policy change. The original policy was to refract all patients that improved with pinhole testing. The policy change was not to refract patients with a visual acuity ≥20/30 unless a specific request was made by the patient. Pre-post analysis of an automated time-motion study was conducted for the data collected 3 months before and 3 months after the policy change occurred on March 30, 2018. Changes to process and wait times were summarized using descriptive statistics and fitted to linear mixed regression models adjusting for appointment type, clinic volume, and daily clinic trends. Results One thousand nine hundred twenty-three visits with 1588 patients were included in the analysis. Mean [SD] age was 65.9 [14.7] years and 892 [56.2%] were women. After the policy change, technician process time decreased by 2.9 min (p < 0.0001) while daily clinical patient volume increased from 51.9 ± 16.8 patients to 58.4 ± 17.4 patients (p < 0.038). No significant difference was found in total wait time (p = 0.18) or total visit time (p = 0.83). Conclusions Real-time locating systems are effective at capturing clinical flow data and assessing clinical practice change initiatives. The refraction policy change was associated with reduced technician process time and overall the clinic was able to care for 7 more patients per day without significantly increasing patient wait time.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Measuring impact of a quality improvement initiative on glaucoma clinic flow using an automated real-time locating system

et al. 2022

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“…In this case, each reader is assigned to a specific area. Alternatively, the assignment can be based on the maximum signal strength received by the readers [120] or by the tag [127], [128]. In any case, the last reader illuminating the tag of the patients can write its ID on the tag, so that other readers can retrieve its last known position [123].…”

Section: B Patient Identification and Managementmentioning

confidence: 99%

A Survey on Radio Frequency Identification as a Scalable Technology to Face Pandemics

Bianco,

Occhiuzzi,

Panunzio

et al. 2021

Preprint

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The COVID-19 pandemic forced mankind to unprecedented global challenges, drastically changing our way of living. To minimize life losses, multi-level strategies requiring collective efforts were adopted, while waiting for researchers and Pharma companies to develop vaccines. The management of so complex processes has partly taken benefit from a network vision and from the rising framework of the Internet of Things (IoT). Among the several technologies converging to IoT, the Radiofrequency Identification (RFID), based on backscattering communication, is probably the approach that is most suitable to both the micro (the user) and the macro (the processes) scale. Accordingly, a single infrastructure can support almost all the logistic and monitoring issues related to the war against a pandemic. Based on the earned COVID-19 experience, this paper is a guide about how state-of-the-art RFID systems can be employed in facing future pandemic outbreaks. The three pillars of the contrast are addressed, namely: 1) use and managing of Personal Protective Equipment (PPE), 2) access control and social distancing, and 3) early detection of symptoms. For each class, the envisaged RFID devices and procedures are identified and discussed based on the already available technology and on the state of the art of worldwide research. The presented guide tells us that this technology has a real potentiality to play a key role in generating an extraordinary amount of data, so that complementary paradigms of Edge Computing and Artificial intelligence should be tightly integrated to extract profiles and identify anomalous events, in compliance with privacy and security.

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Multi-resource allocation and care sequence assignment in patient management: a stochastic programming approach

Yao,

Shehadeh,

Padman

2024

Health Care Manag Sci

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To mitigate outpatient care delivery inefficiencies induced by resource shortages and demand heterogeneity, this paper focuses on the problem of allocating and sequencing multiple medical resources so that patients scheduled for clinical care can experience efficient and coordinated care with minimum total waiting time. We leverage highly granular location data on people and medical resources collected via Real-Time Location System technologies to identify dominant patient care pathways. A novel two-stage Stochastic Mixed Integer Linear Programming model is proposed to determine the optimal patient sequence based on the available resources according to the care pathways that minimize patients’ expected total waiting time. The model incorporates the uncertainty in care activity duration via sample average approximation.We employ a Monte Carlo Optimization procedure to determine the appropriate sample size to obtain solutions that provide a good trade-off between approximation accuracy and computational time. Compared to the conventional deterministic model, our proposed model would significantly reduce waiting time for patients in the clinic by 60%, on average, with acceptable computational resource requirements and time complexity. In summary, this paper proposes a computationally efficient formulation for the multi-resource allocation and care sequence assignment optimization problem under uncertainty. It uses continuous assignment decision variables without timestamp and position indices, enabling the data-driven solution of problems with real-time allocation adjustment in a dynamic outpatient environment with complex clinical coordination constraints.

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Designing and validating a low-cost real time locating system to continuously assess patient wait times

Cited by 12 publications

References 14 publications

Measuring impact of a quality improvement initiative on glaucoma clinic flow using an automated real-time locating system

Measuring impact of a quality improvement initiative on glaucoma clinic flow using an automated real-time locating system

A Survey on Radio Frequency Identification as a Scalable Technology to Face Pandemics

Multi-resource allocation and care sequence assignment in patient management: a stochastic programming approach

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