Rosier, Ashley S.

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.

ABSTRACT Background Risk for medication error increases during care transitions. Error susceptibility increases in pediatrics due to age and weight‐based dosing. Governing bodies acknowledge errors endanger patients, and transplant pharmacotherapy experts are mandated by the Center for Medicare and Medicaid Services (CMS). Pharmacist‐led medication histories reduce errors; however, pharmacists' roles in the transitions of care between transplant centers are unaddressed by CMS. We assessed the impact of transplant pharmacist involvement in medication histories for pediatrics transitioning between transplant centers. Methods Pediatric patients pre‐ or post‐heart transplant transitioning to our center were proactively identified. Transplant pharmacists conducted medication histories by phone with caregivers and tracked discrepancies between existing medication lists and interview responses. Descriptive statistical analyses were completed. Results Of 27 patients identified, seven caregivers were uncontactable, one declined participation, and 19 underwent transplant pharmacist medication history. Medication list errors were detected in 100% of patients ( n = 19), with a median [IQR] of 5 [3–11] issues per patient. Of 122 issues, 72 (59%) were inaccurate or missing data, 17.2% ( n = 21) listed stopped drugs, 9.8% ( n = 12) revealed incorrect administration routes, 7.4% ( n = 9) were duplicate medications, and 6.6% ( n = 8) of errors were medications needing to be added. Corrections included updating 84 inaccuracies (68.8%); removing/adding drugs (30 [24.6%] and 8 [6.6%], respectively); and team communication. Conclusions Complex dosing strategies in pediatrics confer error vulnerability. Designing transition of care processes with transplant pharmacist involvement in medication histories can assist in ensuring medication list accuracy, thereby improving pediatric patient safety.

Background The Scientific Registry for Transplant Recipients (SRTR) publishes outcomes of all transplant centres in the USA two times a year. The outcomes are publicly available and used by insurance payers and patients to assess the performance of a programme. Poor performance can result in temporary suspension or termination of a transplant programme. The estimated 1-year survival hazard ratio (EHR) is an important metric publicly reported by the SRTR. Problem The EHR at our institution was 1.13, indicating a graft loss rate that was 13% higher than the national average. Methods/INTERVENTION We defined an improvement in this metric as achieving an EHR of <1.0. Our balance measure was maintaining similar liver transplant volumes and avoiding limiting access to transplant. Using a causality tree, we identified there was no ‘real time’ assessment of programme risk or objective metric to assess this. An affinity diagram was used to determine high and intermediate risk factors for mortality and graft loss and, using a REDCap form (a web application used to manage our database) to track actual and potential complications, we calculated a weekly ‘risk metric’ that was introduced at multidisciplinary selection conference meetings. Results We remeasured our EHR at each interval release of the SRTR outcomes and found it to be 0.98 and 0.65 after implementing the ‘risk metric.’ During the intervention period, annual liver transplant volume remained above the baseline measure. Conclusion By implementing a ‘risk metric’ to prospectively assess the risk of a low EHR at transplant selection committee meetings, we were able to reduce the EHR well below the national average without limiting access to liver transplants.