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Background: Hospital Sant Joan de Déu (Barcelona) initiated a pediatric acute home-hospitalization program. Due to high patient turnover and the health staff's lack of planning training, daily scheduling was a time-consuming task. Home-hospitalization planning is a vehicle routing problem that can be solved with a technological solution. It was therefore decided to evaluate the efficacy and necessity of the SmartMonkey.io planner.
Objectives: To compare traditional manual route planning with a route optimizer, and to evaluate the technical feasibility of the implementation of a route planner into a homecare program.
Methods: Eight participants (experienced homecare staff and inexperienced hospital staff) were included. Personal interviews were performed to assess their eagerness to try a technological solution to the planning problem. Objective benefits including reduced travel time (time planning, distance traveled, and time traveled) were evaluated. Paired -test, -test, and Pearson's correlation were used to compare manual and route planner scheduling. Participants then answered a questionnaire to assess planning difficulty and the acceptance of the route planner.
Results: Homecare staff were initially reluctant to use the technology. Significant differences ( < 0.0001) in three variables were found between manual planning and the route planner. A moderate correlation between time planning and plan difficulty ( = 0.59, < 0.0001) was found with manual planning but not with the route planner. All route planner schedules saved time and distance. No significant differences were found between expertise and planning method. It was noted that it was easy to create plans with the route planner, while difficulty with manual planning increased as more locations were added. All participants evaluated the route planning tool favorably.
Conclusions: Route-planning technology saved planning time and generated better plans than manual planning. The route planner's learning curve was fast and results were obtained in the same amount of time regardless of difficulty and expertise. SmartMonkey.io also has the potential to reduce internal and environmental costs and increase staff productivity.
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http://dx.doi.org/10.3389/fped.2022.928273 | DOI Listing |
Min Metall Explor
July 2025
Department of Mathematics and Industrial Engineering, Polytechnique Montreal, 2500 Chemin de Polytechnique, H3T 1J4 Montreal, QC Canada.
Accurately predicting haul truck (HT) travel times (TT) in underground mines is essential for enhancing operational planning, as it allows planners to forecast extraction rates at each work face, minimize queue-related downtime, and ultimately increase productivity. However, in underground environments where GPS signals are unavailable, beacon-based locating systems have not yet been utilized for this predictive purpose. This study addresses that gap by introducing a machine learning approach for HT TT prediction that relies exclusively on beacon detection data, thus eliminating the need for traditional telemetry.
View Article and Find Full Text PDFThis article proposes a novel approach to address the need for visual analysis tools in the transportation domain. Transportation planners require a tool to understand the interplay between vehicles, personnel, transported goods, and routes dynamically over time. Existing tools focus on map visualizations and are limited to animations when depicting changes over time in large amounts of data.
View Article and Find Full Text PDFBMJ Open
August 2025
Medical School, University of Exeter, Exeter, UK.
Introduction: The UK's medical workforce is under increasing strain, and this is compounded by increasing numbers of resident doctors diverging from specialist training pathways, instead entering non-training roles, reducing clinical hours or leaving the profession or UK workforce entirely. These decisions are shaped by both individual motivations and wider structural conditions, including unsatisfactory working conditions, limited flexibility and a perceived lack of support or autonomy. While pursuing alternative career routes offers personal and professional benefits, they can also delay progression to senior clinical roles, contributing to workforce instability.
View Article and Find Full Text PDFUnderstanding how functional connectivity can provide mobile consumers access to key resources can inform habitat management. The spatial arrangement of landscape features, for example, can affect movement among resource patches. Guided by the Haíɫzaqv (Heiltsuk) Integrated Resource Management Department (HIRMD), and within Haíɫzaqv Territory, coastal British Columbia (BC), Canada, our objectives were to (1) estimate functional connectivity for grizzly and black bears ( and , respectively) among aggregations of spawning Pacific salmon ( spp.
View Article and Find Full Text PDFAcc Chem Res
June 2025
Department of Electrical Engineering and Computer Science, MIT, Cambridge, Massachusetts 02139, United States.
ConspectusThe advancement of machine learning and the availability of large-scale reaction datasets have accelerated the development of data-driven models for computer-aided synthesis planning (CASP) in the past decade. In this Account, we describe the range of data-driven methods and models that have been incorporated into the newest version of ASKCOS, an open-source software suite for synthesis planning that we have been developing since 2016. This ongoing effort has been driven by the importance of bridging the gap between research and development, making research advances available through a freely available practical tool.
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