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  • 1.
    Fryk, Pontus
    et al.
    Uppsala University, Sweden.
    Steins, Krisjanis
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska högskolan.
    A modern process perspective, process mapping, and simulation in health care: Opportunities and IT infrastructural needs2010Inngår i: Proceedings of 2010 IEEE Workshop on Health Care Management (WHCM), 2010, s. 1-6Konferansepaper (Fagfellevurdert)
    Abstract [en]

    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.

  • 2.
    Holmberg, M
    et al.
    Östergötlands Läns Landsting, Närsjukvården i östra Östergötland, Akutkliniken ViN.
    Steins, Krisjanis
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska högskolan.
    Walther, Sten
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Hjärt- och Medicincentrum, Thorax-kärlkliniken i Östergötland.
    Does high ICU occupancy have adverse effects on patient outcomes? An obeservational multicentre study of the relationship between occupancy, length-of-stay and mortality2013Inngår i: Intensive Care Medicine, 2013Konferansepaper (Fagfellevurdert)
  • 3. Holmer, M.
    et al.
    Steins, Krisjanis
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, EISLAB - Economic Information Systems.
    Visuell modellering av patientflödet på en operationsavdelning2006Inngår i: Utvecklingskraft 2006 - konferensen för utveckling av arbetssätt i svensk hälso- och sjukvård,2006, 2006Konferansepaper (Annet vitenskapelig)
    Abstract [sv]

       

  • 4.
    Rapp, Birger
    et al.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, EISLAB - Economic Information Systems.
    Steins, Krisjanis
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, EISLAB - Economic Information Systems.
    Using Simulation Gaming in Logistic Training2002Inngår i: Proceedings Transbaltica,2002, 2002Konferansepaper (Annet vitenskapelig)
  • 5. Bestill onlineKjøp publikasjonen >>
    Steins, Krisjanis
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska högskolan.
    Discrete-Event Simulation for Hospital Resource Planning: Possibilities and Requirements2010Licentiatavhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    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.

    Delarbeid
    1. A modern process perspective, process mapping, and simulation in health care: Opportunities and IT infrastructural needs
    Åpne denne publikasjonen i ny fane eller vindu >>A modern process perspective, process mapping, and simulation in health care: Opportunities and IT infrastructural needs
    2010 (engelsk)Inngår i: Proceedings of 2010 IEEE Workshop on Health Care Management (WHCM), 2010, s. 1-6Konferansepaper, Publicerat paper (Fagfellevurdert)
    Abstract [en]

    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.

    Emneord
    IT, digitization, process mapping, process orientation, data analysis, discrete event simulation (DES), health care.
    HSV kategori
    Identifikatorer
    urn:nbn:se:liu:diva-56553 (URN)10.1109/WHCM.2010.5441276 (DOI)978-1-4244-4998-9 (ISBN)978-1-4244-4997-2 (ISBN)
    Konferanse
    IEEE Workshop on Health Care Management, February 18-20, Venice, Italy
    Tilgjengelig fra: 2010-05-21 Laget: 2010-05-21 Sist oppdatert: 2017-08-14
    2. Developing a Generic Simulation Model for Planning of Intensive Care Resource Needs
    Åpne denne publikasjonen i ny fane eller vindu >>Developing a Generic Simulation Model for Planning of Intensive Care Resource Needs
    (engelsk)Manuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    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.

    Emneord
    Intensive care, discrete-event simulation, capacity planning, utilisation
    HSV kategori
    Identifikatorer
    urn:nbn:se:liu:diva-56555 (URN)
    Tilgjengelig fra: 2010-05-21 Laget: 2010-05-21 Sist oppdatert: 2010-06-14
    3. Increasing Utilization in a Hospital Operating Department Using Simulation Modeling
    Åpne denne publikasjonen i ny fane eller vindu >>Increasing Utilization in a Hospital Operating Department Using Simulation Modeling
    2010 (engelsk)Inngår i: Simulation (San Diego, Calif.), ISSN 0037-5497, E-ISSN 1741-3133, Vol. 86, nr 8-9, s. 463-480Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    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.

    sted, utgiver, år, opplag, sider
    SAGE, 2010
    Emneord
    Healthcare, operating department, operating rooms, utilization, discrete-event simulation, planning, scheduling
    HSV kategori
    Identifikatorer
    urn:nbn:se:liu:diva-56554 (URN)10.1177/0037549709359355 (DOI)000280765600002 ()
    Tilgjengelig fra: 2010-05-21 Laget: 2010-05-21 Sist oppdatert: 2017-12-12
  • 6.
    Steins, Krisjanis
    et al.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, EISLAB - Economic Information Systems.
    Glenros, J.
    Lundin, M.
    Walter, S.
    Planning Intensive Care Resource Need Using Discrete Event Simulation Modelling2006Annet (Annet (populærvitenskap, debatt, mm))
    Abstract [en]

            

  • 7.
    Steins, Krisjanis
    et al.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, EISLAB - Economic Information Systems.
    Lundin, M
    Walter, S.
    Planning Intensive Care Resource Need Using Discrete Event Simulation Modelling2006Inngår i: ESICM 2006 ¿- 19th Annual Congress of European Society of Intensive Care Medicine,2006, Barcelona, Spanien: Congress of European Society of Intensive Care Medicine , 2006Konferansepaper (Annet vitenskapelig)
  • 8.
    Steins, Krisjanis
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska fakulteten.
    Matinrad, Niki
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska fakulteten.
    Andersson Granberg, Tobias
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska fakulteten.
    Forecasting the Demand for Emergency Medical Services2019Inngår i: Proceedings of the 52nd Hawaii International Conference on System Sciences, 2019, University of Hawai'i at Manoa , 2019, s. 1855-1864Konferansepaper (Fagfellevurdert)
    Abstract [en]

    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.

  • 9.
    Steins, Krisjanis
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska högskolan.
    Persson, Fredrik
    Linköpings universitet, Institutionen för teknik och naturvetenskap. Linköpings universitet, Tekniska högskolan.
    Holmer, Martin
    County Hospital Ryhov, Jönköping, Sweden.
    Increasing Utilization in a Hospital Operating Department Using Simulation Modeling2010Inngår i: Simulation (San Diego, Calif.), ISSN 0037-5497, E-ISSN 1741-3133, Vol. 86, nr 8-9, s. 463-480Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    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.

  • 10.
    Steins, Krisjanis
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska högskolan.
    Walther, Sten
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Östergötlands Läns Landsting, Hjärt- och Medicincentrum, Thorax-kärlkliniken i Östergötland. Linköpings universitet, Hälsouniversitetet.
    A generic simulation model for planning critical care resource requirements2013Inngår i: Anaesthesia, ISSN 0003-2409, E-ISSN 1365-2044, Vol. 68, nr 11, s. 1148-1155Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    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.

  • 11.
    Steins, Krisjanis
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska högskolan.
    Walther, Sten
    Linköpings universitet, Institutionen för medicin och hälsa. Linköpings universitet, Hälsouniversitetet.
    Developing a Generic Simulation Model for Planning of Intensive Care Resource NeedsManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    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.

1 - 11 of 11
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  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • Annet format
Fler format
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
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  • html
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  • rtf