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1. Development of a Surrogate Model for the Assessment of Crew Workload in Emergency Medical Services

   Ercolani, J; Cure, L (June 2025, Proceedings of the IISE Anual Conference and Expo 2025)

   Gentry, E; Ju, F; Liu, X (Ed.)

   One commonly used workload metric in Emergency Medical Services (EMS) is the Unit Hour Utilization (UHU). The UHU is a productivity measure that, by definition, represents the ratio of patient transport calls to the total hours that ambulances are staffed. It is often misinterpreted as a utilization measure representing the percentage of crews’ available working hours that are spent performing work. This paper investigates a surrogate model to estimate a measure of EMS crew utilization that considers not only call response, but also indirect work tasks, such as documentation and shift start activities. We explored Kriging, KPLS, RBF, and physics-based models based on EMS work dynamics. The true measure of utilization was based on Montecarlo samples of estimated work time patterns associated with a year’s worth of dispatch data augmented with the results of a work measurement study. The best performing model in terms of the root mean square error (RSME), the symmetric mean absolute percent error (sMAPE), and Pearson correlation estimates, was the physics-based model. This model requires time studies to estimate the average time spent in shift start activities and documenting calls, geographic information systems to estimate the average time driving back to the post, and dispatch data analysis to estimate the average time to respond to calls. Sensitivity analysis was used to provide recommendations for when to update these parameters and general recommendations were given to implement this approach in other EMS systems. 

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2. Developing workload-informed crew configuration recommendations for emergency medical services

   https://doi.org/10.1016/j.ergon.2025.103777  

   Darvishi, Setareh; Misasi, Paul; Cure, Laila (July 2025, International Journal of Industrial Ergonomics)

   While crew configuration in primary care settings has been studied in terms of its impact on patient outcomes, less is known about how it influences the members' workload experience. This study investigates the workload implications of crew configuration based on members' certification in emergency medical services (EMS). Advanced life support (ALS) ambulance crews are commonly comprised of two paramedics (homogeneous crew) or an emergency medical technician (EMT) and a paramedic (heterogeneous crew). The goals of this study were the following: (1) to investigate differences in workload among members of the same crew, and (2) to use workload assessments to inform crew configuration strategies. We mapped one year of an EMS system's dispatch data to members' workload estimates using the visual, auditory, cognitive, and psychomotor (VACP) approach. We found that lead members (lead paramedics) experience higher workload levels compared to support members (support paramedics or EMTs) in both types of crews. Neither configuration had a consistently lower workload than the other, but differences varied for different shifts and stations. These results informed crew configuration recommendations for stations and shifts in the collaborating system, and in terms of more generalizable variables. A minimum number of staffed crews, half-half shift type (covering both day and night hours), and 30-day frequency of calls with priority P7 most significantly impacted the recommended crew configurations. 

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3. Changes in public–police cooperation following the murder of George Floyd

   https://doi.org/10.1093/pnasnexus/pgac189  

   Brantingham, P. Jeffrey; Mohler, George; MacDonald, John; Pescosolido, ed., Bernice (September 2022, PNAS Nexus)

   Abstract The murder of George Floyd triggered a broad social response and noticeable shift in public opinion of policing. Since policing is dependent upon public cooperation, a question is whether the shift in opinion had an effect on police calls-for-service. Data from Los Angeles and New York City are evaluated using a regression discontinuity design. Violent crime, property crime, and quality-of-life disorder calls are analyzed to address differences in reporting norms. The role of racial–ethnic composition of local areas is assessed by examining census tracts where the majority of the residential population is Asian, Black, Hispanic, or White. Following the murder of George Floyd, in New York City violent crime, property crime, and quality-of-life calls all increased significantly. In Los Angeles, quality-of-life calls for service decreased significantly. The increase in violent crime calls observed in New York was greatest in areas where the majority of residents are Black, whereas the increase in property crime calls was the greatest in areas where a majority of residents are White. The decrease in quality-of-life calls observed in Los Angeles was in areas where the majority of residents are White. In both cases, the effect was relatively short-lived. 

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4. An Online Decision-Theoretic Pipeline for Responder Dispatch

   Mukhopadhyay, Ayan; Pettet, Geoff; Samal, Chinmaya; Dubey, Abhishek; Vorobeychik, Yevgeniy (January 2019, International Conference on Cyber-Physical Systems)

   The problem of dispatching emergency responders to service traffic accidents, fire, distress calls and crimes plagues urban areas across the globe. While such problems have been extensively looked at, most approaches are offline. Such methodologies fail to capture the dynamically changing environments under which critical emergency response occurs, and therefore, fail to be implemented in practice. Any holistic approach towards creating a pipeline for effective emergency response must also look at other challenges that it subsumes - predicting when and where incidents happen and understanding the changing environmental dynamics. We describe a system that collectively deals with all these problems in an online manner, meaning that the models get updated with streaming data sources. We highlight why such an approach is crucial to the effectiveness of emergency response, and present an algorithmic framework that can compute promising actions for a given decision-theoretic model for responder dispatch. We argue that carefully crafted heuristic measures can balance the trade-off between computational time and the quality of solutions achieved and highlight why such an approach is more scalable and tractable than traditional approaches. We also present an online mechanism for incident prediction, as well as an approach based on recurrent neural networks for learning and predicting environmental features that affect responder dispatch. We compare our methodology with prior state-of-the-art and existing dispatch strategies in the field, which show that our approach results in a reduction in response time with a drastic reduction in computational time. 

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5. Continuous-Time Modeling of Zipfian Workload Locality

   https://doi.org/10.1145/3746450  

   Wang, Yiyang; Ding, Chen; Sciortino, Leo; Chen, Linlin (July 2025, ACM Transactions on Modeling and Performance Evaluation of Computing Systems)

   Traditional workload analysis uses discrete times measured by data accesses. An example is the classic independent reference model (IRM). Effective solutions have been developed to model workloads with stochastic access patterns, but they incur a high cost for Zipfian workloads, which may contain millions of items each accessed with a different frequency. This paper first presents a continuous-time model of locality for workloads with stochastic access patterns. It shows that two previous techniques by Dan and Towsley and by Denning and Schwartz can be interpreted as a single model using different discrete times. Using continuous time, it derives a closed-form solution for an item and a general solution that is a differentiable function. In addition, the paper presents an approximation technique by grouping items into partitions. When evaluated using Zipfian workloads, it shows that a workload with millions of items can be approximated using a small number of partitions, and the continuous-time model has greater accuracy and is faster to compute numerically. For the largest data size verifiable using trace generation and simulation, the new techniques reduce the time of locality analysis by 6 orders of magnitude. 

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