Measuring process change in primary care using real-time location systems: Feasibility and the results of a natural experiment

Stahl, James E.; Drew, Mark; Leone, Donna; Crowley, Rosemary S.

doi:10.3233/thc-2011-0638

Cited by 17 publications

(6 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Tracking patient flows for throughput management can help diagnose bottlenecks and tailor (and monitor the implementation of) appropriate solutions for problems such as extended waiting times, overcrowding and boarding in outpatient clinics, emergency departments/rooms (ED/ER) and post-anaesthesia care units (PACUs); bumped and late surgeries; and the lack of available routine inpatient and intensive care unit (ICU) beds [1,5,14,15]. …”

Section: Rtls Applications In Healthcarementioning

confidence: 99%

Real-time locating systems (RTLS) in healthcare: a condensed primer

Boulos

Berry²

2012

International Journal of Health Geographics

154

View full text Add to dashboard Cite

Real-time locating systems (RTLS, also known as real-time location systems) have become an important component of many existing ubiquitous location aware systems. While GPS (global positioning system) has been quite successful as an outdoor real-time locating solution, it fails to repeat this success indoors. A number of RTLS technologies have been used to solve indoor tracking problems. The ability to accurately track the location of assets and individuals indoors has many applications in healthcare. This paper provides a condensed primer of RTLS in healthcare, briefly covering the many options and technologies that are involved, as well as the various possible applications of RTLS in healthcare facilities and their potential benefits, including capital expenditure reduction and workflow and patient throughput improvements. The key to a successful RTLS deployment lies in picking the right RTLS option(s) and solution(s) for the application(s) or problem(s) at hand. Where this application-technology match has not been carefully thought of, any technology will be doomed to failure or to achieving less than optimal results.

show abstract

Section: Rtls Applications In Healthcarementioning

confidence: 99%

Real-time locating systems (RTLS) in healthcare: a condensed primer

Boulos

Berry²

2012

International Journal of Health Geographics

154

View full text Add to dashboard Cite

show abstract

“…To our knowledge, this was the first study to use lean principles and an RFID-based RTLS in a glaucoma clinic. This combinatory approach has been frequently used in other specialties including in emergency medicine [ 25 ], family medicine [ 26 ], radiology [ 27 ], oncology [ 28 , 29 ], surgery [ 30 ], and intensive care units [ 31 ]. It possesses promising potential to guide data-driven change within the field of glaucoma care.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

View full text Add to dashboard Cite

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.

show abstract

“…Parametrically fitted arrival and exam time Normal distributions are drawn from a national survey of the Society of General Internal Medicine, 20 the National Ambulatory Medical Care Survey, 24 and a series of studies on real-time location systems (RTLS) in health care delivery. 25–27 Further discussion of arrival rate modeling considerations is provided in Appendix B.1. In general, triangular distributions are used for stochastic model inputs for which data for parametric fitting of distributions was not available, an approach commonly used in simulation studies, 28 allowing for both ease of elicitation from experts and intuitive presentation.…”

Section: Methodsmentioning

confidence: 99%

Simulation Analysis and Comparison of Point of Care Testing and Central Laboratory Testing

Harder

Wei

Vaze

et al. 2019

MDM Policy & Practice

Self Cite

View full text Add to dashboard Cite

Background. In response to demand for fast and efficient clinical testing, the use of point-of-care testing (POCT) has become increasingly common in the United States. However, studies of POCT implementation have found that adopting POCT may not always be advantageous relative to centralized laboratory testing. Methods. We construct a simulation model of patient flow in an outpatient care setting to evaluate tradeoffs involved in POCT implementation across multiple dimensions, comparing measures of patient outcomes in varying clinical scenarios, testing regimes, and patient conditions. Results. We find that POCT can significantly reduce clinical time for patients, as compared to traditional testing regimes, in settings where clinic and central testing areas are far apart. However, as distance from clinic to central testing area decreased, POCT advantage over central laboratory testing also decreased, in terms of time in the clinical system and estimated subsequent productivity loss. For example, testing for pneumonia resulted in an estimated average of 27.80 (central lab) versus 15.50 (POCT) total lost productive hours in a rural scenario, and an average of 14.92 (central lab) versus 15.50 (POCT) hours in a hospital-based scenario. Conclusions. Our results show that POCT can effectively reduce the average time a patient spends in the system for varying condition profiles and clinical scenarios. However, the number of total lost productive hours, a more holistic measure, is greatly affected by testing quality, where POCT often is at a disadvantage. Thus, it is important to consider factors such as clinical setting, target condition, testing costs, and test quality when selecting appropriate testing regime.

show abstract

Measuring process change in primary care using real-time location systems: Feasibility and the results of a natural experiment

Cited by 17 publications

References 18 publications

Real-time locating systems (RTLS) in healthcare: a condensed primer

Real-time locating systems (RTLS) in healthcare: a condensed primer

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

Simulation Analysis and Comparison of Point of Care Testing and Central Laboratory Testing

Contact Info

Product

Resources

About