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A modern process perspective, process mapping, and simulation in health care: Opportunities and IT infrastructural needs
Uppsala University, Sweden.
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, The Institute of Technology.
2010 (English)In: Proceedings of 2010 IEEE Workshop on Health Care Management (WHCM), 2010, 1-6 p.Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
2010. 1-6 p.
Keyword [en]
IT, digitization, process mapping, process orientation, data analysis, discrete event simulation (DES), health care.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-56553DOI: 10.1109/WHCM.2010.5441276ISBN: 978-1-4244-4998-9 (print)ISBN: 978-1-4244-4997-2 (print)OAI: oai:DiVA.org:liu-56553DiVA: diva2:320131
Conference
IEEE Workshop on Health Care Management, February 18-20, Venice, Italy
Available from: 2010-05-21 Created: 2010-05-21 Last updated: 2017-08-14
In thesis
1. Discrete-Event Simulation for Hospital Resource Planning: Possibilities and Requirements
Open this publication in new window or tab >>Discrete-Event Simulation for Hospital Resource Planning: Possibilities and Requirements
2010 (English)Licentiate thesis, comprehensive summary (Other academic)
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.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2010. 25 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1446
Keyword
Discrete-event simulation (DES), health care, resource planning
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-56556 (URN)LIU-TEK-LIC-2010:17 (Local ID)978-91-7393-360-5 (ISBN)LIU-TEK-LIC-2010:17 (Archive number)LIU-TEK-LIC-2010:17 (OAI)
Presentation
2010-06-10, TP2, Täppan, Campus Norrköping., Linköpings universitet, Norrköping, 13:15 (Swedish)
Opponent
Supervisors
Available from: 2010-06-14 Created: 2010-05-21 Last updated: 2010-06-14Bibliographically approved
2. Towards Increased Use of Discrete-Event Simulation for Hospital Resource Planning
Open this publication in new window or tab >>Towards Increased Use of Discrete-Event Simulation for Hospital Resource Planning
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Health care systems in many countries are experiencing a growing demand while their resources remain limited. The discrepancy between demand and capacity creates many problems – long waiting times for treatment, overcrowding in hospital wards, high workload, etc. More efficient delivery of health care services can be achieved by better planning of its resources so that the mismatch between demand and capacity is minimized. Planning health care resources, including hospital resources, is difficult due to system complexity and variability in both resource availability and demand. Discrete-event simulation and other operational research methods can be used for solving planning problems in health care, and have been gaining increased attention from researchers during recent decades. Despite the growing number of academic publications, simulation appears to be less used in health care than in other application areas and only a small proportion of simulation studies is actually implemented.

The aim of this thesis is to contribute to increased use of discrete-event simulation in hospital resource planning. The separate studies regarding intensive care unit capacity planning, operating room allocation strategies and the management of emergency patient flow in a radiology department highlight both the possibilities and the requirements for practical application of discrete-event simulation in hospital resource planning. The studies are described in five papers.

In the first paper, the relationship between intensive care unit (ICU) occupancy and patient outcomes was investigated and the results showed that risk adjusted mortality was higher in the group of patients who were treated during high levels of occupancy. This indicates that appropriate planning of ICU resources is necessary to avoid adverse effects on patient outcomes.

In the second paper, analysis of a relatively simple care chain consisting of two hospital departments – emergency and radiology – revealed a process that was not very well defined and measured. Investigation into data availability uncovered disparate information systems storing incompatible and fragmented data. It suggests that the current degree of process orientation and the current IT infrastructure does not enable efficient use of quantitative process analysis and management tools such as simulation.

In the third paper, the value and possibilities of using simulation modelling in hospital resource planning were examined through the development and use of a simulation model for improved operating room time allocation and patient flow in a hospital operating department. The model was initially used for studying overcrowding in a post-anaesthesia care unit. Advanced planning logic implemented in the model enabled evaluation of several different scenarios aiming to improve the utilization of operating room resources. The results showed that it is possible to achieve slightly better and more even resource utilization, as well as provide greater flexibility in scheduling operations.

In the fourth paper, a generic ICU model was developed and validated using data from four different hospital ICUs. The model was adapted and calibrated stepwise in order to identify important parameters and their values to obtain a match between model predictions and actual data. The study showed that in presence of high quality data and well defined process logic it is possible to develop a generic ICU simulation model that could provide accurate decision support for planning critical care resources.

In the fifth paper, a number of factors that can contribute to successful implementation of simulation results in health care were identified. The timing of the simulation study must be right to support a critical decision, the benefit from implementation should clearly outweigh the cost of making the necessary changes and the model should be thoroughly validated to increase the credibility of the results. Staff involvement in simulation modelling activities, availability of good quality data, as well as proper incentives to improve the system contribute to implementation as well. These findings can help in establishing the conditions for successful implementation in future applications of simulation modelling in health care.

Abstract [sv]

Hälso- och sjukvårdssystemen i många länder möter en växande efterfrågan samtidigt som resurserna är begränsade. När efterfrågan överstiger kapaciteten skapas många problem, bland annat långa väntetider för behandling, överbeläggningar i sjukhusavdelningar och hög arbetsbelastning för personalen. En effektivare sjukvård kan uppnås genom bättre planering av resurserna, så att obalansen mellan efterfrågan och kapacitet minimeras. Planering av hälso- och sjukvårdsresurser, inklusive sjukhusresurser, är svårt på grund av systemkomplexitet och variation i både resurstillgänglighet och efterfrågan. Simulering och andra operationsanalytiska metoder som används för att lösa planeringsproblem inom tillverkning, logistik och andra områden, kan med fördel användas också inom sjukvården och har fått ökad uppmärksamhet av forskare under de senaste årtiondena. Trots det växande antalet akademiska publikationer verkar simulering användas betydligt mindre inom sjukvården än i andra tillämpningsområden och endast en liten del av resultaten omsätts i praktiken.

Syftet med denna avhandling är att bidra till ökad användning av simulering vid planering av sjukhusresurser. De separata studierna i avhandlingen behandlar kapacitetsdimensionering av intensivvård, allokering av operationssalsresurser samt hantering av akutpatientflödet på en röntgenavdelning, och lyfter därigenom fram både möjligheterna och kraven för praktisk tillämpning av diskret händelsesstyrd simulering för planering av sjukhusresurser.

Intensivvårdsavdelningar anses vara bland de dyraste resurserna på ett sjukhus. Det är därför ekonomiskt önskvärt att ha en hög utnyttjandegrad av en sådan resurs. Samtidigt är det viktigt att alltid ha utrymme för kritiskt sjuka patienter. I en studie där förhållandet mellan beläggningen på intensivvårdsavdelningar och patientutfall undersöktes visade resultaten att riskjusterad dödlighet var högre för patienter som behandlades när beläggningen på avdelningen var hög, vilket understryker att bra planering av intensivvårdsresurser är mycket viktigt.

Hög grad av processorientering och tillgång till data som möjliggör undersökning av patientflödet över gränserna av sjukhusets organisatoriska och funktionella enheter är exempel på förutsättningar för användning av simulering för hela vårdkedjor. En analys av en relativt enkel vårdkedja bestående av två sjukhusavdelningar avslöjade dock en process som inte var särskilt väldefinierad, och där olika informationssystem lagrade inkompatibla och fragmenterade data. Avsaknaden av processorientering och den befintliga IT-infrastrukturen är hinder för effektiv användning av kvantitativa processanalysverktyg som simulering.

Värdet av att utnyttja simulering och modellering för planering av sjukhusresurser användes vidare för att hitta en bättre och jämnare fördelning av operationssalsresurser. Modellen användes för att undersöka ett antal scenarier och resultatet visade att det är möjligt att uppnå ett jämnare utnyttjande av operationssalar och en större flexibilitet vid schemaläggning av operationer.

Generiska simuleringsmodeller, som med hjälp av ett antal parameterinställningar kan omvandlas till en ny modell av en given sjukhusenhet, skulle sannolikt öka användningen av simulering. Dock kan det vara svårt att visa hur dessa modeller avbildar varje specifik enhet på ett tillräckligt trovärdigt sätt. En generisk modell för kapacitetsdimensionering av intensivvårdsavdelningar har utvecklats och validerats med hjälp av data från fyra olika sjukhus. Studien visade att när data är av hög kvalitet och processlogiken är väldefinierad är det möjligt att utveckla en sådan generisk simuleringsmodell som kan ge beslutsstöd vid planering av intensivvårdsresurser.

Flera litteraturundersökningar har visat att endast en liten del av publicerade simuleringsstudier inom sjukvården har implementerats. Genom att studera ett flerårigt simuleringsprojekt identifierades ett antal faktorer som kan bidra till att simuleringsresultat faktiskt används för att förändra verksamheten. Tidpunkten för simuleringsstudien måste vara välanpassad för att stödja ett kritiskt beslut, fördelar med förändringen bör tydligt överväga kostnaden för att genomföra den och modellen bör grundligt valideras för att öka resultatens trovärdighet. Personalens engagemang i modelleringsaktiviteter, tillgång till data av god kvalitet samt lämpliga incitament för att förbättra systemet bidrar också till genomförandet. Resultaten kan hjälpa till att skapa förutsättningar för framgångsrik framtida användning av simulering vid planering av sjukhusresurser.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2017. 33 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1866
National Category
Health Care Service and Management, Health Policy and Services and Health Economy Computer Systems Reliability and Maintenance Transport Systems and Logistics Computer and Information Science
Identifiers
urn:nbn:se:liu:diva-139732 (URN)10.3384/diss.diva-139732 (DOI)978-91-7685-488-4 (ISBN)
Public defence
2017-09-12, K3, Campus Norrköping, Norrköping, 13:15 (English)
Opponent
Supervisors
Available from: 2017-08-14 Created: 2017-08-14 Last updated: 2017-08-15Bibliographically approved

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  • nn-NB
  • sv-SE
  • Other locale
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  • asciidoc
  • rtf