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Amouzad Mahdiraji, SaeidORCID iD iconorcid.org/0000-0003-2769-4826
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Publications (7 of 7) Show all publications
Abid, M. A., Amouzad Mahdiraji, S., Lorig, F., Holmgren, J., Mihailescu, R.-C. & Petersson, J. (2023). A Genetic Algorithm for Optimizing Mobile Stroke Unit Deployment. Paper presented at 27th International Conference on Knowledge Based and Intelligent Information and Engineering Systems (KES 2023), Athens, Greece, 6-8 September 2023. Procedia Computer Science, 225, 3536-3545
Open this publication in new window or tab >>A Genetic Algorithm for Optimizing Mobile Stroke Unit Deployment
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2023 (English)In: Procedia Computer Science, ISSN 1877-0509, Vol. 225, p. 3536-3545Article in journal (Refereed) Published
Abstract [en]

A mobile stroke unit (MSU) is an advanced ambulance equipped with specialized technology and trained healthcare personnel to provide on-site diagnosis and treatment for stroke patients. Providing efficient access to healthcare (in a viable way) requires optimizing the placement of MSUs. In this study, we propose a time-efficient method based on a genetic algorithm (GA) to find the most suitable ambulance sites for the placement of MSUs (given the number of MSUs and a set of potential sites). We designed an efficient encoding scheme for the input data (the number of MSUs and potential sites) and developed custom selection, crossover, and mutation operators that are tailored according to the characteristics of the MSU allocation problem. We present a case study on the Southern Healthcare Region in Sweden to demonstrate the generality and robustness of our proposed GA method. Particularly, we demonstrate our method's flexibility and adaptability through a series of experiments across multiple settings. For the considered scenario, our proposed method outperforms the exhaustive search method by finding the best locations within 0.16, 1.44, and 10.09 minutes in the deployment of three MSUs, four MSUs, and five MSUs, resulting in 8.75x, 16.36x, and 24.77x faster performance, respectively. Furthermore, we validate the method's robustness by iterating GA multiple times and reporting its average fitness score (performance convergence). In addition, we show the effectiveness of our method by evaluating key hyperparameters, that is, population size, mutation rate, and the number of generations.

Place, publisher, year, edition, pages
Elsevier, 2023
Keywords
genetic algorithm, mobile stroke unit (MSU), optimization, healthcare, time to treatment
National Category
Communication Systems Neurology
Identifiers
urn:nbn:se:mau:diva-64632 (URN)10.1016/j.procs.2023.10.349 (DOI)
Conference
27th International Conference on Knowledge Based and Intelligent Information and Engineering Systems (KES 2023), Athens, Greece, 6-8 September 2023
Funder
The Kamprad Family Foundation
Available from: 2023-12-20 Created: 2023-12-20 Last updated: 2023-12-20Bibliographically approved
Amouzad Mahdiraji, S., Abid, M. A., Holmgren, J., Mihailescu, R.-C., Lorig, F. & Petersson, J. (2023). An Optimization Model for the Placement of Mobile Stroke Units. In: Teresa Guarda; Filipe Portela; Jose Maria Diaz-Nafria (Ed.), Advanced Research in Technologies, Information, Innovation and Sustainability: Third International Conference, ARTIIS 2023, Madrid, Spain, October 18–20, 2023, Proceedings, Part I. Paper presented at Advanced Research in Technologies, Information, Innovation and Sustainability, Third International Conference, ARTIIS 2023, Madrid, Spain, October 18–20, 2023 (pp. 297-310). Springer
Open this publication in new window or tab >>An Optimization Model for the Placement of Mobile Stroke Units
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2023 (English)In: Advanced Research in Technologies, Information, Innovation and Sustainability: Third International Conference, ARTIIS 2023, Madrid, Spain, October 18–20, 2023, Proceedings, Part I / [ed] Teresa Guarda; Filipe Portela; Jose Maria Diaz-Nafria, Springer, 2023, p. 297-310Conference paper, Published paper (Refereed)
Abstract [en]

Mobile Stroke Units (MSUs) are specialized ambulances that can diagnose and treat stroke patients; hence, reducing the time to treatment for stroke patients. Optimal placement of MSUs in a geographic region enables to maximize access to treatment for stroke patients. We contribute a mathematical model to optimally place MSUs in a geographic region. The objective function of the model takes the tradeoff perspective, balancing between the efficiency and equity perspectives for the MSU placement. Solving the optimization problem enables to optimize the placement of MSUs for the chosen tradeoff between the efficiency and equity perspectives. We applied the model to the Blekinge and Kronoberg counties of Sweden to illustrate the applicability of our model. The experimental findings show both the correctness of the suggested model and the benefits of placing MSUs in the considered regions.

Place, publisher, year, edition, pages
Springer, 2023
Series
Communications in Computer and Information Science, ISSN 1865-0929, E-ISSN 1865-0937 ; 1935
Keywords
Optimization, MILP, Time to Treatment, Mobile Stroke Unit (MSU), MSU Placement
National Category
Neurology Computational Mathematics
Identifiers
urn:nbn:se:mau:diva-64865 (URN)10.1007/978-3-031-48858-0_24 (DOI)2-s2.0-85180781530 (Scopus ID)978-3-031-48857-3 (ISBN)978-3-031-48858-0 (ISBN)
Conference
Advanced Research in Technologies, Information, Innovation and Sustainability, Third International Conference, ARTIIS 2023, Madrid, Spain, October 18–20, 2023
Available from: 2024-01-08 Created: 2024-01-08 Last updated: 2024-01-08Bibliographically approved
Amouzad Mahdiraji, S., Holmgren, J., Alshaban, A., Mihailescu, R.-C., Petersson, J. & Al Fatah, J. (2022). A Framework for Constructing Discrete Event Simulation Models for Emergency Medical Service Policy Analysis. Paper presented at 12th International Conference on Current and Future Trends of Information and Communication Technologies in Health care (ICTH 2022) October 26-28, 2022, Leuven, Belgium. Procedia Computer Science, 210, 133-140
Open this publication in new window or tab >>A Framework for Constructing Discrete Event Simulation Models for Emergency Medical Service Policy Analysis
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2022 (English)In: Procedia Computer Science, E-ISSN 1877-0509, Vol. 210, p. 133-140Article in journal (Refereed) Published
Abstract [en]

Constructing simulation models can be a complex and time-consuming task, in particular if the models are constructed from scratch or if a general-purpose simulation modeling tool is used. In this paper, we propose a model construction framework, which aims to simplify the process of constructing discrete event simulation models for emergency medical service (EMS) policy analysis. The main building blocks used in the framework are a set of general activities that can be used to represent different EMS care chains modeled as flowcharts. The framework allows to build models only by specifying input data, including demographic and statistical data, and providing a care chain of activities and decisions. In a case study, we evaluated the framework by using it to construct a model for the simulation of the EMS activities related to acute stroke. Our evaluation shows that the predefined activities included in the framework are sufficient to build a simulation model for the rather complex case of acute stroke.

Place, publisher, year, edition, pages
Elsevier, 2022
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:mau:diva-56003 (URN)10.1016/j.procs.2022.10.129 (DOI)2-s2.0-85144819456 (Scopus ID)
Conference
12th International Conference on Current and Future Trends of Information and Communication Technologies in Health care (ICTH 2022) October 26-28, 2022, Leuven, Belgium
Available from: 2022-11-14 Created: 2022-11-14 Last updated: 2024-02-05Bibliographically approved
Amouzad Mahdiraji, S., Holmgren, J., Mihailescu, R.-C. & Petersson, J. (2022). A Micro-Level Simulation Model for Analyzing the Use of MSUs in Southern Sweden. Paper presented at 11th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH 2021) November 1-4, 2021, Leuven, Belgium. Procedia Computer Science, 198, 132-139
Open this publication in new window or tab >>A Micro-Level Simulation Model for Analyzing the Use of MSUs in Southern Sweden
2022 (English)In: Procedia Computer Science, E-ISSN 1877-0509, Vol. 198, p. 132-139Article in journal (Refereed) Published
Abstract [en]

A mobile stroke unit (MSU) is a special type of ambulance, where stroke patients can be diagnosed and provided intravenous treatment, hence allowing to cut down the time to treatment for stroke patients. We present a discrete event simulation (DES) model to study the potential benefits of using MSUs in the southern health care region of Sweden (SHR). We included the activities and actions used in the SHR for stroke patient transportation as events in the DES model, and we generated a synthetic set of stroke patients as input for the simulation model. In a scenario study, we compared two scenarios, including three MSUs each, with the current situation, having only regular ambulances. We also performed a sensitivity analysis to further evaluate the presented DES model. For both MSU scenarios, our simulation results indicate that the average time to treatment is expected to decrease for the whole region and for each municipality of SHR. For example, the average time to treatment in the SHR is reduced from 1.31h in the baseline scenario to 1.20h and 1.23h for the two MSU scenarios. In addition, the share of stroke patients who are expected to receive treatment within one hour is increased by a factor of about 3 for both MSU scenarios.

Place, publisher, year, edition, pages
Elsevier, 2022
Keywords
Ischemic stroke; stroke transport; MSU; DES; time to treatment; stroke logistics
National Category
Computational Mathematics
Identifiers
urn:nbn:se:mau:diva-54479 (URN)10.1016/j.procs.2021.12.220 (DOI)2-s2.0-85124617439 (Scopus ID)
Conference
11th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH 2021) November 1-4, 2021, Leuven, Belgium
Available from: 2022-08-22 Created: 2022-08-22 Last updated: 2024-02-05Bibliographically approved
Amouzad Mahdiraji, S. (2022). On the Use of Simulation and Optimization for the Analysis and Planning of Prehospital Stroke Care. (Licentiate dissertation). Malmö: Malmö universitet
Open this publication in new window or tab >>On the Use of Simulation and Optimization for the Analysis and Planning of Prehospital Stroke Care
2022 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Immediate treatment is of extreme importance for stroke patients. However, providing fast enough treatment for stroke patients is far from trivial, mainly due to logistical challenges and difficulties in diagnosing the correct stroke type. One way to reduce the time to treatment is to use so-called Mobile Stroke Units (MSUs), which allows to diagnose and provide treatment for stroke patients already at the patient scene. A well-designed stroke transport policy is vital to improve the access to treatment for stroke patients. Simulation and mathematical optimization are useful approaches for assessing and optimizing stroke transport policies, without endangering the health of the patients.

The main purpose of this thesis is to contribute to improving the situation for stroke patients and to reducing the social impacts of stroke. The aim is to study how to use simulation and optimization to achieve improved analysis and planning of prehospital stroke care. In particular, we focus on assessing the potential use of MSUs in a geographic area. In this thesis, optimization is used to identify the optimal locations of MSUs, and simulation is used to assess different stroke transport policies, including MSU locations. The results of this thesis aim to support public health authorities when making decisions in the prehospital stroke care domain.

In order to fulfill the aim of this thesis, we develop and analyze a number of different simulation and optimization models. First, we propose a macro-level simulation model, an average time to treatment estimation model, used to estimate the expected time to treatment for different parts of a geographic region. Using the proposed model, we generate two different MSU scenarios to explore the potential benefits of employing MSUs in Sweden’s southern healthcare region (SHR).  

Second, we present an optimization model to identify the best placement of MSUs while making a trade-off between the efficiency and equity perspectives, providing maximum population coverage and equal service for all patients, respectively. The trade-off function used in the model makes use of the concepts of weighted average time to treatment to model efficiency and the time difference between the expected time to treatment for different geographical areas to model equity. In a scenario study applied in the SHR, we evaluate our optimization model by comparing the current situation with three MSU scenarios, including 1, 2, and 3 MSUs.

Third, we present a micro-level discrete event simulation model to assess stroke transport policies, including MSUs, allowing us to model the behaviors of individual entities, such as patients and emergency vehicles, over time. We generate a synthetic set of stroke patients using a Poisson distribution, used as input in a scenario study.

Finally, we present a modeling framework with reusable components, which aims to facilitate the construction of discrete event simulation models in the emergency medical services domain. The framework consists of a number of generic activities, which can be used to represent healthcare chains modeled in the form of flowcharts. As the framework includes activities and policies modeled on the general level, the framework can be used to create models only by providing input data and a care chain specification. We evaluate the framework by using it to build a model for simulating EMS activities related to the complex case of acute stroke.

Place, publisher, year, edition, pages
Malmö: Malmö universitet, 2022. p. 55
Series
Studies in Computer Science ; 21
Keywords
Stroke Transport Policies, EMS, Mobile Stroke Unit, MSU, Simulation, Optimization, Modeling Framework.
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mau:diva-55489 (URN)10.24834/isbn.9789178773039 (DOI)978-91-7877-304-6 (ISBN)978-91-7877-303-9 (ISBN)
Presentation
2022-10-18, 13:00 (English)
Opponent
Supervisors
Note

Note: The papers are not included in the fulltext online.

Available from: 2022-10-25 Created: 2022-10-24 Last updated: 2024-02-26Bibliographically approved
Mahdiraji, S. A., Holmgren, J., Mihailescu, R.-C. & Petersson, J. (2021). An Optimization Model for the Tradeoff Between Efficiency and Equity for Mobile Stroke Unit Placement. In: Innovation in Medicine and Healthcare: Proceedings of 9th KES-InMed 2021. Paper presented at 9th KES-InMed 2021 (pp. 183-193). Springer
Open this publication in new window or tab >>An Optimization Model for the Tradeoff Between Efficiency and Equity for Mobile Stroke Unit Placement
2021 (English)In: Innovation in Medicine and Healthcare: Proceedings of 9th KES-InMed 2021, Springer, 2021, p. 183-193Conference paper, Published paper (Refereed)
Abstract [en]

A mobile stroke unit (MSU) is an ambulance, where stroke patients can be diagnosed and treated. Recently, placement of MSUs has been studied focusing on either maximum population coverage or equal service for all patients, termed efficiency and equity, respectively. In this study, we propose an unconstrained optimization model for the placement of MSUs, designed to introduce a tradeoff between efficiency and equity. The tradeoff is based on the concepts of weighted average time to treatment and the time difference between the expected time to treatment for different geographical areas. We conduct a case-study for Sweden’s Southern Health care Region (SHR), generating three scenarios (MSU1, MSU2, and MSU3) including 1, 2, and 3 MSUs, respectively. We show that our proposed optimization model can tune the tradeoff between the efficiency and equity perspectives for the MSU(s) allocation. This enables a high level of equal service for most inhabitants, as well as reducing the time to treatment for most inhabitants of a geographic region. In particular, placing three MSUs in the SHR with the proposed tradeoff, the share of inhabitants who are expected to receive treatment within an hour potentially improved by about a factor of 14 in our model.

Place, publisher, year, edition, pages
Springer, 2021
Series
Smart Innovation, Systems and Technologies, ISSN 2190-3018, E-ISSN 2190-3026 ; 242
Keywords
Driving time estimation, Efficient coverage, Equal treatment, Mobile stroke unit, Time to treatment, Tradeoff function, Efficiency, Optimization, Equal services, Expected time, Geographical area, Optimization modeling, Stroke patients, Time-differences, Unconstrained optimization, Weighted averages, Patient treatment
National Category
Communication Systems
Identifiers
urn:nbn:se:mau:diva-45147 (URN)10.1007/978-981-16-3013-2_15 (DOI)2-s2.0-85111101237 (Scopus ID)9789811630125 (ISBN)
Conference
9th KES-InMed 2021
Available from: 2021-08-23 Created: 2021-08-23 Last updated: 2024-02-05Bibliographically approved
Mahdiraji, S. A., Dahllöf, O., Hofwimmer, F., Holmgren, J., Mihailescu, R.-C. & Petersson, J. (2021). Mobile stroke units for acute stroke care in the south of sweden. Cogent Engineering, 8(1), Article ID 1874084.
Open this publication in new window or tab >>Mobile stroke units for acute stroke care in the south of sweden
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2021 (English)In: Cogent Engineering, E-ISSN 2331-1916, Vol. 8, no 1, article id 1874084Article in journal (Refereed) Published
Abstract [en]

A Mobile stroke unit (MSU) is a type of ambulance deployed to promote the rapid delivery of stroke care. We present a computational study using a time to treatment estimation model to analyze the potential benefits of using MSUs in Sweden's Southern Health Care Region (SHR). In particular, we developed two scenarios (MSU1 and MSU2) each including three MSUs, which we compared with a baseline scenario containing only regular ambulances. For each MSU scenario, we assessed how much the expected time to treatment is estimated to decrease for the whole region and each subregion of SHR, and how the population is expected to benefit from the deployment of MSUs. For example, the average time to treatment in SHR was decreased with 20,4 and 15,6 minutes, respectively, in the two MSU scenarios. Moreover, our computational results show that the locations of the MSUs significantly influence what benefits can be expected. While MSU1 is expected to improve the situation for a higher share of the population, MSU2 is expected to have a higher impact on the patients who currently have the longest time to treatment.

Place, publisher, year, edition, pages
Taylor & Francis, 2021
Keywords
driving time estimation, mobile stroke unit, MSU, stroke transport, time to treatment
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
urn:nbn:se:mau:diva-41078 (URN)10.1080/23311916.2021.1874084 (DOI)000613349600001 ()2-s2.0-85100213272 (Scopus ID)
Available from: 2021-03-09 Created: 2021-03-09 Last updated: 2024-02-05Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-2769-4826

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