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The objective of this scoping review is to identify and explore the current literature related to patient navigation services focused on palliative care delivery and outcomes for individuals living with advanced cancer. This review will not only define the range of navigation services for these patients but will also outline the outcomes of patient navigation techniques. The results of this review can help direct future research and may inform guidelines related to patient navigation in palliative care for patients with advanced cancer.

Older persons with serious illnesses living in rural communities are an underserved population. They often live with heavy symptom burden and poor quality of life with limited access to resources. Nav-CARE (Navigation: Connecting Accessing Resourcing and Engaging) was developed to specially train and mentor volunteer navigators who help connect older persons with serious illness to the resources and information they need. Aims: This mixed methods longitudinal study evaluated Nav-CARE for feasibility, acceptability, ease of use, and satisfaction by older persons and volunteers. Methods: Nine volunteer navigators visited 23 older persons with serious illness every 3 to 4 weeks for 1 year. Data were collected from volunteer navigators, and older person participants at baseline, during the year- long implementation and post implementation. Results: Volunteer navigators and older persons reported Nav-CARE was easy to use, feasible and acceptable. The majority of older persons agreed or strongly agreed that they were satisfied with the navigation services (100%; 8/8), that navigation services were important to them (87%; 7/8), that they would recommend the program to someone else (87%; 7/8), and would participate in the program again (75%; 6/8). Similarly, volunteer navigators reported 100% (9/9) satisfaction with the program, 100% (9/9) would recommend it to others, and 67% (6/8) would participate again. Conclusions: Nav-CARE appears to be a feasible, acceptable, and satisfactory program for older persons with serious illness and volunteer navigators.

Road network performance (RNP) is a key element for urban sustainability as it has a significant impact on economy, environment, and society. Poor RNP can lead to traffic congestion, which can lead to higher transportation costs, more pollution and health issues regarding the urban population. To evaluate the effects of the RNP, the involved stakeholders need a real-world data base to work with. This paper develops a data collection approach to enable location-based RNP analysis using publicly available traffic information. Therefore, we use reachable range requests implemented by navigation service providers to retrieve travel times, travel speeds, and traffic conditions. To demonstrate the practicability of the proposed methodology, a comparison of four German cities is made, considering the network characteristics with respect to detours, infrastructure, and traffic congestion. The results are combined with cost rates to compare the economical dimension of sustainability of the chosen cities. Our results show that digitization eases the assessment of traffic data and that a combination of several indicators must be considered depending on the relevant sustainability dimension decisions are made from., early access version

In spite of recent advances in Intelligent Transport, vehicular traffic dynamics are still hard to represent and analyze. Most of the previous work on traffic regards highways or single lanes where vehicles interact in one dimension. Models for multi-dimensional vehicle-to-vehicle interactions and models for urban intersections are quite complicated and hardly applicable on a large scale. Nonetheless, urban traffic jams are an actual problem that requires a solution. This paper proposes a method to optimize urban traffic layout using basic heuristics and computationally efficient simulations. Instead of modeling an entire urban map with hundreds of intersections, each typology of intersection is simulated in order to understand how it responds to different traffic patterns and intensities. This knowledge is leveraged to allow the computation of minimal delay route on the complete road map. In order to validate our model, we use the solution obtained with our heuristic to derive the average travel delay through simulation on realistic Manhattan topologies with different intersection types. © 2012 IEEE.