| 1. |
- Andersson Granberg, Tobias, 1973-, et al.
(author)
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Kvantitativa modeller för ett robust och resilient transportsystem
- 2022
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Reports (other academic/artistic)abstract
- Både mindre störningar och större händelser som katastrofer och kriser har en påverkan på transportsystemet. Dels kan de ge upphov till förändrade möjligheter att tillgodose efterfrågan, till exempel om infrastruktur blir skadad, dels kan det ge förändringar i efterfrågan, vilket t.ex. var tydligt under Covid-19 pandemin, eller ge upphov till nya behov, t.ex. av nödtransporter. Hanteringen av dessa störningar, ur ett transportsystemperspektiv, kan ske via förebyggande och förberedande åtgärder, vilka bidrar till en ökad robusthet och resiliens. Det kan vara att stärka och skydda infrastruktur eller att ha resurser i beredskap, som operativt kan verka avhjälpande och återställande. Åtgärderna kräver ofta komplexa beslut kring prioritering och resurshantering - områden där kvantitativa modeller har goda möjligheter att användas som grund för beslutsstöd.Syftet med denna studie var att undersöka möjligheten att använda kvantitativa modeller för att öka robustheten och resiliensen hos det svenska transportsystemet vid större störningar.Via en litteraturstudie och intervjuer med systemexperter från räddningsområdet, transportsektorn samt akademin, identifierades fem olika områden där kvantitativa modeller bedöms kunna ge värdefulla bidrag. Dessa är 1. Efterfrågemodellering, 2. Risk- och sårbarhetsanalys, 3. Evakueringsplanering, 4. Resurslokalisering och 5. Prioritering och resurshantering. Inom samtliga finns utrymme för att via forskning och utveckling ta fram beslutsstödsverktyg som kan bidra vid planering, förebyggande arbete, och operativ resursstyrning. Även inom andra områden, till exempel kommunikation, samverkan och organisering, finns det behov av forskning, då gärna med inslag av andra discipliner såsom human factors och digitalisering.
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| 2. |
- Andersson Granberg, Tobias, 1973-, et al.
(author)
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Sensor Requirements for Logistics Analysis of Emergency Incident Sites
- 2020
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In: Proceedings of the 17th ISCRAM Conference. - : Information Systems for Crisis Response and Management. - 9781949373271 ; , s. 952-960
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Conference paper (peer-reviewed)abstract
- Using sensors to collect data at emergency incident sites can facilitate analysis of the logistic operations. This can be used to improve planning and preparedness for new operations. Furthermore, real-time information from the sensors can serve as operational decision support. In this work in progress, we investigate the requirements on the sensors, and on the sensor data, to facilitate such an analysis. Through observations of exercises, the potential of using sensors for data collection is explored, and the requirements are considered. The results show that the potential benefits are significant, especially for tracking patients, and understanding the interaction between the response actors. However, the sensors need to be quite advanced in order to capture the necessary data.
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| 3. |
- Fryk, Pontus, et al.
(author)
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A modern process perspective, process mapping, and simulation in health care : Opportunities and IT infrastructural needs
- 2010
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In: Proceedings of 2010 IEEE Workshop on Health Care Management (WHCM). - 9781424449989 - 9781424449972 ; , s. 1-6
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Conference paper (peer-reviewed)abstract
- Today, health care organizations often claim that theyare “process oriented”, and that one should approach health carefrom a process perspective in order to utilize the present ITrelated benefits; such as increased service quality, cost efficiency,and enhanced communication. In this paper we investigate howwell founded the concept of process orientation really is – byexamining IT/IS infrastructures, and procedures for processdefinition, visualization, and evaluation – at a prominent hospitalin Stockholm, Sweden. A case study of the organization and theinteraction of the emergency and radiology departments at thesame hospital (using process mapping and data analysis) revealsdata fragmentation, incompatible data, and disparateinformation systems. This results in difficulties regarding processdefinition and analysis, which makes the use of innovative toolssuch as simulation, problematic. The implications of this, and thecontextual factors, are also discussed and some finalrecommendations for smooth digitization are put forth.Today, health care organizations often claim that theyare “process oriented”, and that one should approach health carefrom a process perspective in order to utilize the present ITrelated benefits; such as increased service quality, cost efficiency,and enhanced communication. In this paper we investigate howwell founded the concept of process orientation really is – byexamining IT/IS infrastructures, and procedures for processdefinition, visualization, and evaluation – at a prominent hospitalin Stockholm, Sweden. A case study of the organization and theinteraction of the emergency and radiology departments at thesame hospital (using process mapping and data analysis) revealsdata fragmentation, incompatible data, and disparateinformation systems. This results in difficulties regarding processdefinition and analysis, which makes the use of innovative toolssuch as simulation, problematic. The implications of this, and thecontextual factors, are also discussed and some finalrecommendations for smooth digitization are put forth.
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| 4. |
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| 5. |
- Prytz, Erik, 1985-, et al.
(author)
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Evaluating the Effect of Bleeding Control Kit Locations for a Mass Casualty Incident Using Discrete Event Simulation
- 2020
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In: Proceedings of the 17th ISCRAM Conference. - : Information Systems for Crisis Response and Management. - 9781949373271 ; , s. 167-178
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Conference paper (peer-reviewed)abstract
- The purpose of this study was to develop a simulation model to evaluate bleeding control kit location strategies for a mass casualty incident scenario. Specifically, the event simulated was an explosion at a large sports arena. The model included a representation of the arena itself, simulated crowd movements following the detonation of an improvised explosive device, injuries and treatments, and different ways for immediate responders to help injured patients using tourniquets. The simulation model gave logically consistent results in the validation scenarios and the simulation outcomes were in line with the expected outcomes. The results of the different tourniquet location scenarios indicated that decentralized placement (more than one location) is better, easy access is important (between rather than at emergency exits) and that an increased number of available tourniquets will result in an increased number of survivors.
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| 7. |
- Steins, Krisjanis, 1971-, et al.
(author)
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A generic simulation model for planning critical care resource requirements
- 2013
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In: Anaesthesia. - : Wiley. - 0003-2409 .- 1365-2044. ; 68:11, s. 1148-1155
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Journal article (peer-reviewed)abstract
- Intensive care capacity planning based on factual or forecasted mean admission numbers and mean length of stay without taking non-linearity and variability into account is fraught with error. Simulation modelling may allow for a more accurate assessment of capacity needs. We developed a generic intensive care simulation model using data generated from anonymised patient records of all admissions to four different hospital intensive care units. The model was modified and calibrated stepwise to identify important parameters and their values to obtain a match between model predictions and actual data. The most important characteristic of the final model was the dependency of admission rate on actual occupancy. Occupancy, coverage and transfers of the final model were found to be within 2% of the actual data for all four simulated intensive care units. We have shown that this model could provide accurate decision support for planning critical care resource requirements.
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| 8. |
- Steins, Krisjanis, 1971-, et al.
(author)
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Developing a Generic Simulation Model for Planning of Intensive Care Resource Needs
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Other publication (other academic/artistic)abstract
- The estimation of intensive care resource needs is often made on incomprehensive grounds as simple calculations fail to account for the complexity and variability in the patient flow. The aim of the study was to develop and validate a generic intensive care unit simulation model which could reproduce resource use, i.e. occupancy and coverage, as found in data from the Swedish Intensive Care Registry (SIR). The generic ICU model was developed using a stepwise modification and calibration approach in order to identify important parameters and their values to obtain a match between model predictions and actual data in four selected ICUs. The final version of the model included special logic for handling elective surgery patients, holding beds for dealing with overutilizations, and a mathematical model to describe admission rate dependency on actual occupancy. The results from model calibration indicate that simple models cannot adequately describe the behavior in all studied ICUs. It is necessary to include certain patient characteristics as well as to account properly for dependencies in input data in order to have the model predict ICU resource use as observed in historical data.
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| 9. |
- Steins, Krisjanis, 1971-
(author)
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Discrete-Event Simulation for Hospital Resource Planning : Possibilities and Requirements
- 2010
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Licentiate thesis (other academic/artistic)abstract
- The delivery of health care services has been under pressure due to limited funding and increasing demand. This has highlighted the need to increase not only the effectiveness but also the efficiency of health care delivery. Discrete-event simulation has been suggested as an analysis tool in health care management to support the planning of health care resources.The overall purpose of this thesis is to investigate the possibilities and requirements for using discrete-event simulation in analyzing and planning the use of hospital resources. This is achieved by three case studies that focus on improvements in patient flow of emergency patients that require a radiology examination, intensive care unit capacity planning and operating room allocation strategies, respectively.The first case investigates the current stage of digitization and process orientation in hospital care as a prerequisite for efficient process simulation and analysis. The study reveals an emergency-radiology patient flow process that is not very well measured and uncovers disparate information systems storing incompatible and fragmented data. These results indicate that the current degree of process orientation and the current IT infrastructure does not enable efficient use of quantitative process analysis and management tools like simulation.In the second case the possibilities to develop generic hospital unit simulation models by building and validating a generic intensive care unit (ICU) model are explored. The results show that some of the modeling approaches described in literature cannot replicate the actual behavior observed in all studied ICUs. It is important to identify patient groups for different admission priorities, to account for over-utilizations in the model logic, and to discover and properly model dependencies in the input data. The research shows that it is possible to develop a generic ICU simulation model that could realistically describe the performance of different real ICUs in terms of occupancy, coverage and transfers.The value of simulation modeling in health care management is examined in the third case through the development and use of a simulation model for optimal resource allocation and patient flow in a hospital operating department. The goal of the simulation modeling in this case was to identify bottlenecks in the patient flow and to try different alternatives for allocation of operating room capacity in order to increase the utilization of operating room resources. The final model was used to evaluate four different proposed changes to operating room time allocation.
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| 10. |
- Steins, Krisjanis, 1971-, et al.
(author)
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Forecasting the Demand for Emergency Medical Services
- 2019
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In: Proceedings of the 52nd Hawaii International Conference on System Sciences, 2019. - : University of Hawai'i at Manoa. - 9780998133126 ; , s. 1855-1864
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Conference paper (peer-reviewed)abstract
- Accurate forecast of the demand for emergency medical services (EMS) can help in providing quick and efficient medical treatment and transportation of out-of-hospital patients. The aim of this research was to develop a forecasting model and investigate which factors are relevant to include in such model. The primary data used in this study was information about ambulance calls in three Swedish counties during the years 2013 and 2014. This information was processed, assigned to spatial grid zones and complemented with population and zone characteristics. A Zero-Inflated Poisson (ZIP) regression approach was then used to select significant factors and develop the forecasting model. The model was compared to the forecasting model that is currently incorporated in the EMS information system used by the ambulance dispatchers. The results show that the proposed model performs better than the existing one.
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| 11. |
- Steins, Krisjanis, 1971-, et al.
(author)
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Identifying Factors for Successful Implementation of Simulation Modeling in Healthcare
- 2015
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In: International Journal of Privacy and Health Information Management (IJPHIM). - : IGI Global. - 2155-5621 .- 2155-563X. ; 3:1, s. 1-19
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Journal article (peer-reviewed)abstract
- A number of academic literature surveys have shown that only a small fraction of published healthcare simulation studies are actually implemented. This research identifies factors that can contribute to successful implementation of simulation results in healthcare. The authors have been involved in a six year long simulation study in a Swedish regional hospital’s operating department. The three most important factors that contributed to implementation in this case were: the timing of simulation study to support a critical decision, advantageous cost benefit ratio of the implementation and thorough model validation. Other contributing factors included high degree of staff involvement, availability of good quality data, as well as proper incentives to improve the system. Findings of this study can help in establishing the prerequisites for successful implementation in other cases.
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| 12. |
- Steins, Krisjanis, 1971-, et al.
(author)
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Increasing Utilization in a Hospital Operating Department Using Simulation Modeling
- 2010
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In: Simulation (San Diego, Calif.). - : SAGE. - 0037-5497 .- 1741-3133. ; 86:8-9, s. 463-480
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Journal article (peer-reviewed)abstract
- This article focuses on the planning and scheduling of operating rooms (ORs) in a regional hospital in Sweden. A simulation study was carried out to find new ideas and new planning and scheduling techniques to improve the overall process of surgery, including pre- and post-operating activities. This study mainly addresses the problem of low utilization of the ORs, and also takes into consideration problems with variation in workload, both in ORs and in post-anesthesia care units. The final simulation model includes pre-operative care carried out in the operating department and all ORs, as well as post-operative care units. It was driven by a number of input parameters, such as the volume and specific characteristics of actual cases, opening hours and number of ORs, and the number of beds for pre- and post-operative care. The model also includes logic for prioritizing and allocating cases to available ORs, planning operating schedules and the utilization of medical equipment limited in quantity. Output performance measures from simulation experiments include the utilization of allocated OR times, waiting time for patients, queue dynamics, number of cancellations, and variation of finishing times, as well as occupancy statistics in the post-operative care unit. Four different change alternatives were evaluated using the simulation model. Simulation experiments showed that with the implementation of the proposed changes it is possible to achieve slightly better and more even resource utilization, as well as provide greater flexibility in scheduling operations.
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