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

Abstract

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.

Application of Agile and Simulation Approaches for the Maximal Benefits of Reduced Turnaround Time from the Point of Care Testing

“…One of the key advantages of using point of care systems is the increased patient flow (Harder et al 2019). If the healthcare processes are not redesigned to take advantage of reduced turnaround time, the benefits portrayed by the point of care system can be distorted.…”

“…Reduced turnaround time between patient sample collection and test results is the primary benefit because test results are available to healthcare decision-makers within minutes. Nevertheless, the ability of clinical processes (patient process) to take advantage of the reduced turnaround time is the critical determinant of the effects of point-of-care testing on patient care (Harder et al 2019, Lingervelder et al 2022.…”

Comparison of GFAP and UCH-L1 Measurements from Two Prototype Assays: The Abbott i-STAT and ARCHITECT Assays

“…However, core laboratory assays typically produce more analytically robust values, have a wider dynamic range, and have a higher overall throughput. 10 As the literature on GFAP and UCH-L1 matures, it would be helpful to have a clear understanding on how values of these biomarkers differ when measured using different platforms. Conversion of ARCHITECT to i-STAT values will enable direct comparison of assay results derived from the two platforms.…”

Lateral flow assay: a promising rapid point-of-care testing tool for infections and non-communicable diseases

“…In another report, it was concluded that the use of POCT in hospital EDs significantly contributes to cost management compared to using conventional diagnostic methods, further emphasizing their importance in cost-effectiveness [ 66 ]. However, it is worth noting that the cost of POCT can fluctuate, sometimes exceeding that of traditional methods, depending on the clinical setting, target condition, and test quality [ 67 ].…”