Stellmaker, Jessica A.

Abstract Background The use of autonomous mobile robots (AMRs) to move materials/supplies is long-standing in manufacturing/warehouse settings and is expanding into hospitals and clinical laboratories. The recently launched Proxie robot (Collaborative Robotics i.e. Cobot) is an AMR that can autonomously move existing carts between defined locations. However, AMRs pose new challenges compared to traditional lab automation. The aims of this study were to: i) perform functional validation to verify Proxie*s manufacturer performance specifications within the laboratory, ii) assess the risk of using Proxie to deliver laboratory specimens, and iii) pilot the use of the Proxie robot to autonomously deliver loaded carts from the Pathology case intake area to the sorting station at Mayo Clinic Laboratories. Methods Functional validation of Proxie consisted of verifying manufacturer’s performance specifications for the following robot parameters (5 test runs): maximum speed, emergency-stop, and ability to maintain localization, travel autonomously, stop and/or avoid moving/fixed objects, and park/unpark. Risk assessment for the robotic use case was performed by a multi-disciplinary team utilizing an AMR risk assessment tool developed by the institutional robotics group. Hazards were categorized as mechanical, electrical, noise, ergonomic, environmental, material/substance or combination risks. Injury severity, exposure(frequency), and avoidance scores were assigned to each hazard to determine negligible-, low-, medium-, high- or very high-risk levels. Proxie’s workstream was evaluated weekly over four weeks by measuring number of cart deliveries, total time/miles traveled, % autonomous deliveries(goal >80%), % on-time deliveries, average±standard deviation(SD) time (min:sec±min:sec) for delivery/return trips, and dwell times at intake/sorting stations. Results Manufacturer’s performance specifications were verified in 100% of test runs. Proxie traveled at human walking speed, stopped within 1 second of emergency stop being enabled, maintained localization, and traveled autonomously for =5 consecutive workflow cycles. Proxie navigated through spaces =4’ wide along fixed pathways and stopped safely when encountering obstacles. Proxie navigated around people and carts in the main 6’ hallway if they were blocking <2’ hallway width. For objects blocking >2’, Proxie stopped and resumed motion after the object moved. After task completion, Proxie side-shifted into the AMR parking space stopping no closer than 7.8” from any object. Twenty-four potential hazards were identified through the risk assessment tool with all risk levels scored as negligible or low. Proxie completed 304 cart deliveries/returns operating 17:35 hours and traveling 11.5 miles during the pilot. The % autonomous deliveries for week 1-4 was 82%,88%,91% and 88%, respectively with =99% on-time deliveries. Delivery from pathology case intake to sorting station averaged 5:43±0:25 min and return trips averaged 3:32±0:34. Proxie dwell times were 13:10±0:33 and 37:34±0:23 min at the pathology intake and sorting stations, respectively. Conclusions The Proxie AMR was capable of successfully and autonomously moving carts with laboratory specimens between the pathology intake and sorting stations of the laboratory during the pilot study. Adding Proxie to this workstream translated to eliminating 5,800 steps and 4 hours 24 min of human cart-pushing per week. Incorporating Proxie into laboratory operations as a cart-moving AMR would increase efficiency and allow laboratory staff to focus on technical, non-repetitive work.

In the ever-evolving healthcare landscape, hospitals routinely grapple with daily disruptions and unforeseen events affecting resources and capacity. This paper explores the implementation and impact of the Rochester Hospital Operations Command Center (RHOCC) as a strategic response to challenges faced by the Mayo Clinic Hospital campuses in Rochester. The RHOCC, developed with an expedited timeline in response to capacity issues, exacerbated by COVID-19, serves as a centralised hub for real-time monitoring, coordination and decision-making related to patient flow. The process of establishing the command centre involved role identification, skill set determination, location of important personnel in an organised central space and vendor selection to develop the necessary infrastructure. Dashboards were developed to provide real-time actionable insights into external transfers, surgical and other planned admissions, emergency department status, patient throughput and discharges. These dashboards include colour-coded keys highlighting thresholds related to patient flow metrics and are used to facilitate daily huddles and enhance transparency and data-driven decision-making among hospital stakeholders. The outcomes of implementing the RHOCC include improved efficiency and collaboration, as well as a significantly enhanced ability to proactively respond to factors affecting census. The development of a command centre — driven by leadership endorsement and a commitment to continuous improvement — emerges as a transformative strategy in healthcare innovation. The RHOCC’s approach of building capability, fostering inclusion and articulating a vision of providing superior care while driving impactful improvements, positions it as a leading force in creating operational efficiencies to define healthcare delivery.

Time-drive activity-based costing (TDABC) is a practical way of calculating costs, decreasing waste, and improving efficiency. Although TDABC has been utilized in other service industries for years, it has only recently gained attention in healthcare. In this review article, we define the basic concepts and steps of TDABC and provide examples for applications in breast imaging.