Real-Time Locating Systems and the Effects on Efficiency of Anesthesiologists

Abstract

Objective: To investigate the impact of Real Time Locating System (RTLS) technology on the perioperative efficiency of anesthesiologists.Methods: A retrospective chart review was performed for all outpatient and short-stay patients who received General Anesthesia care at our institution between January 2016 and October 2017. Patients included were over 18 years and had ASA classification scores of 1, 2, and 3. Only first cases of the day for individual anesthesiologists were included. Duration between two perioperative time points was collected and used as a measure of efficiency. Two groups of anesthesiologists were compared Group 1: Anesthesiologists at Main Campus who do not use RTLS Group 2: Anesthesiologists at Josie Robertson Surgery Center who use RTLS The outcome measure collected from patient electronic medical records was defined as DUR: Duration from when patient is admitted to the operating room and initiation of induction only for first case of the day by attending anesthesiologist. The outcome was compared between the two groups using Wilcoxon rank sum test. Results:The duration between admission to the OR and initiation of induction was significantly shorter in JRSC (with RTLS) than main campus (without RTLS); specifically, median (25 th , 75 th percentile) of the duration was 7.0 (5.0, 10.0) at JRSC vs. 8.0 (6.0, 11.0) at main campus (p < 0.0001, Table 1). Conclusion:In our initial study, we found that anesthesiologists who had access to RTLS at JRSC performed more efficiently in their preoperative evaluation of patients as well as time to induction for general anesthesia cases. Because of various confounding factors that potentially influenced the increase in efficiency of anesthesiologists with access to RTLS, this follow-up study aims to eliminate several confounding factors by assessing only time to induction of general anesthesia for all first cases of the day by anesthesiologists. We continue to find a small yet statistically significant difference in time to induction of anesthesiologists with access to RTLS. This translates directly into increased efficiency in perioperative workflow. Additional investigation and application can help elucidate the true value of RTLS on workflow efficiency in the healthcare setting.

Leveraging machine learning and prescriptive analytics to improve operating room throughput

“…The program focused on Positive Deviance seminars offered by the most successful surgical professionals in their respective domains. This included surgeons and registered nurses (RNs) with the highest SSR, with the idea of sharing their expertise and best practices with the team to improve overall SSR (8). At our center, during the PD exercise the anesthesiologists refused to participate.…”

“…Current options that support and enhance the scheduling and efficiency of hospitals come in two main types: clinical and nonclinical methods. The non-clinical methods (6, 7) can be divided into three approaches: firstly, incorporating new resources to enhance the effectiveness of operating rooms (8)(9)(10)(11); secondly, utilizing data-driven methods like rhetorical data and descriptive analytics to modify, assess, or reorganize existing hospital resources (12,13); and thirdly, employing machine learning (ML) solutions specifically designed for operating room optimization. The majority of these solutions have the common goal of foreseeing various aspects of surgical procedures.…”