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1. Assessing Trauma Center Accessibility for Healthcare Equity Using an Anti-Covering Approach

   https://doi.org/10.3390/ijerph19031459  

   Chea, Heewon; Kim, Hyun; Shaw, Shih-Lung; Chun, Yongwan (February 2022, International Journal of Environmental Research and Public Health)

   Motor vehicle accidents are one of the most prevalent causes of traumatic injury in patients needing transport to a trauma center. Arrival at a trauma center within an hour of the accident increases a patient’s chances of survival and recovery. However, not all vehicle accidents in Tennessee are accessible to a trauma center within an hour by ground transportation. This study uses the anti-covering location problem (ACLP) to assess the current placement of trauma centers and explore optimal placements based on the population distribution and spatial pattern of motor vehicle accidents in 2015 through 2019 in Tennessee. The ACLP models seek to offer a method of exploring feasible scenarios for locating trauma centers that intend to provide accessibility to patients in underserved areas who suffer trauma as a result of vehicle accidents. The proposed ACLP approach also seeks to adjust the locations of trauma centers to reduce areas with excessive service coverage while improving coverage for less accessible areas of demand. In this study, three models are prescribed for finding optimal locations for trauma centers: (a) TraCt: ACLP model with a geometric approach and weighted models of population, fatalities, and spatial fatality clusters of vehicle accidents; (b) TraCt-ESC: an extended ACLP model mitigating excessive service supply among trauma center candidates, while expanding services to less served areas for more beneficiaries using fewer facilities; and (c) TraCt-ESCr: another extended ACLP model exploring the optimal location of additional trauma centers. 

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2. Planning the Trauma Hospital Network Expansion to Increase Access in Rural Communities

   Holly, Streber; Streber, Kayla; Van, Mary; Pérez, Eduardo (April 2022, Proceedings of the IISE Annual Conference & Expo 2022)

   Ellis, K.; Ferrell, W.; Knapp J. (Ed.)

   Trauma care services are a vital part of all healthcare-based networks as timely accessibility is important for citizens. Trauma care access is even more relevant when unexpected events such as the COVID-19 pandemic overload the capacity of hospitals. Research literature has highlighted that access to trauma care is not equal for all populations, especially when comparing rural and urban groups. In this research we present a decision-making model for the expansion of a trauma hospital network by considering the demand for services of rural communities. The decision making model provides recommendations in terms of where to place additional aeromedical facilities and where to locate additional trauma hospitals. A case study is presented for the state of Texas, where a sensitivity analysis was conducted to consider changes in demand, cost, and the total number of facilities allowed in the network. The results show that the location of new facilities is sensitive to the expected service demand and the maximum number of facilities allowed in the network. 

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3. Delineations for Police Patrolling on Street Network Segments with p-Median Location Models

   https://doi.org/10.3390/ijgi13110410  

   Lee, Changho; Kim, Hyun; Chun, Yongwan; Griffith, Daniel A (November 2024, ISPRS International Journal of Geo-Information)

   Police patrolling intends to enhance traffic safety by mitigating the risks associated with vehicle crashes and accidents. From a view of operations, patrolling requires an effective distribution of resources and often involves area delineations for this distribution purpose. Given constraints such as budget and human resources for traffic safety, delineating geographic areas optimally for police patrol areas is an important agenda item. This paper considers two p-median location models using segments on a street network as observational units on which traffic issues such as vehicle crashes occur. It also uses two weight sets to construct an enhanced delineation of police patrol areas in the City of Plano, Texas. The first model for the standard p-median formulation gives attention to the cumulative number of motor vehicle crashes from 2011 to 2021 on the major transportation networks in Plano. The second model, an extension of this first p-median one, uses balancing constraints to achieve balanced spatial coverage across patrol areas. These two models are also solved with network kernel density count estimates (NKDCE) instead of crash counts. These smoothed densities on a network enable consideration of uncertainty affiliated with this aggregation. The analysis results of this paper suggest that the p-median models provide effective specifications, including their capability to define patrol areas that encompass the entire study region while minimizing distance costs. The inclusion of balancing constraints ensures a more equitable distribution of workloads among patrol areas, improving overall efficiency. Additionally, the model with NKDCE results in an improved workload balance among delineated areas for police patrolling activities, thus supporting more informed spatial decision-making processes for public safety. 

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4. Nested trauma network design considering equity and effectiveness in patient safety

   https://doi.org/10.1016/j.cie.2023.109250  

   Hirpara, Sagarkumar; Parikh, Pratik J; Kong, Nan (July 2023, Computers & Industrial Engineering)

   Trauma injuries continue to be the leading cause of mortality and morbidity among US citizens aged 44 years and under. Government agencies are often in charge of designing an effective trauma network in their region to provide prompt and definitive care to their citizens. This process is, however, largely manual, experience-based and often leads to a suboptimal network in terms of patient safety. To support effective decision making, we propose a Nested Trauma Network Design Problem (NTNDP), which can be characterized as a nested multi-level, multi-customer, multi-transportation, multi-criteria, capacitated model with the bi-objective of maximizing the weighted sum of equity and effectiveness in patient safety. We use mistriages (system-related under- and over-triages) as surrogates for patient safety. To add realism, we include intermediate trauma centers that are set up in many states in the US to serve as feeder centers to major trauma centers to improve patient safety and three criteria to mimic EMS’s on-scene decisions. We propose a ‘3-phase’ solution approach that first solves a relaxed version of the model, then solves a Constraint Satisfaction Problem, and then a modified version of the original optimization problem (if needed), all using a commercial solver. Our findings suggest that solutions are sensitive to (i) the proportion of assignments attributed to various destination determination criteria, (ii) distribution of trauma patients, and (iii) relative emphasis on equity vs. effectiveness. We also illustrate the use of our approach using real data from a midwestern US state; results show over 30% performance improvement in the objective value. 

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5. The Multiple Gradual Maximal Covering Location Problem

   https://doi.org/10.1111/gean.12410  

   Price, Ashleigh_N; Curtin, Kevin_M (July 2024, Geographical Analysis)

   This article describes a new spatial optimization model, the Multiple Gradual Maximal Covering Location Problem (MG‐MCLP). This model is useful when coverage from multiple facilities or sensors is necessary to consider a demand to be covered, and when the quality of that coverage varies with the number of located facilities within the service distance, and the distance from the demand itself. The motivating example for this model uses a coupled GIS and optimization framework to determine the optimal locations for acoustic sensors—typically used in police applications for gunshot detection—in Tuscaloosa, AL. The results identify the optimal facility locations for allocating multiple facilities, at different locations, to cover multiple demands and evaluate those optimal locations with distance‐decay. Solving the MG‐MCLP over a range of values allows for comparing the performance of varying numbers of available resources, which could be used by public safety operations to demonstrate the number of resources that would be required to meet policy goals. The results illustrate the flexibility in designing alternative spatial allocation strategies and provide a tractable covering model that is solved with standard linear programming and GIS software, which in turn can improve spatial data analysis across many operational contexts. 

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