Simulation modelling and resource allocation in complex services

Bayer, Steffen

doi:10.1136/bmjqs-2013-002742

Cited by 8 publications

(5 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Modelling of health systems in these terms is common-place and capturing the ecological dynamics of a complex intervention, thus far, does not require new methods. It simply requires a broader ‘whole systems’ perspective to ensure that both local and system wide effects are captured [ 20 ]. Recent articles provide guidelines on various dynamic modelling approaches and their potential applications, highlighting examples in the evaluation of health services delivery interventions [ 21 , 22 ].…”

Section: Discussionmentioning

confidence: 99%

Complex intervention modelling should capture the dynamics of adaptation

Greenwood-Lee

Hawe

Nettel-Aguirre

et al. 2016

BMC Med Res Methodol

View full text Add to dashboard Cite

BackgroundComplexity has been linked to health interventions in two ways: first as a property of the intervention, and secondly as a property of the system into which the intervention is implemented. The former recognizes that interventions may consist of multiple components that act both independently and interdependently, making it difficult to identify the components or combinations of components (and their contexts) that are important mechanisms of change. The latter recognizes that interventions are implemented in complex adaptive systems comprised of intelligent agents who modify their behaviour (including any actions required to implement the intervention) in an effort to improve outcomes relative to their own perspective and objectives. Although an intervention may be intended to take a particular form, its implementation and impact within the system may deviate from its original intentions as a result of adaptation. Complexity highlights the challenge in developing interventions as effective health solutions. The UK Medical Research Council provides guidelines on the development and evaluation of complex interventions. While mathematical modelling is included in the guidelines, there is potential for mathematical modeling to play a greater role.DiscussionThe dynamic non-linear nature of complex adaptive systems makes mathematical modelling crucial. However, the tendency is for models of interventions to limit focus on the ecology of the system - the ‘real-time’ operation of the system and impacts of the intervention. These models are deficient by not modelling the way the system reacts to the intervention via agent adaptation. Complex intervention modelling needs to capture the consequences of adaptation through the inclusion of an evolutionary dynamic to describe the long-term emergent outcomes that result as agents respond to the ecological changes introduced by intervention in an effort to produce better outcomes for themselves. Mathematical approaches such as those found in economics in evolutionary game theory and mechanism design can inform the design and evaluation of health interventions. As an illustration, the introduction of a central screening clinic is modeled as an example of a health services delivery intervention.SummaryComplexity necessitates a greater role for mathematical models, especially those that capture the dynamics of human actions and interactions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12874-016-0149-8) contains supplementary material, which is available to authorized users.

show abstract

Section: Discussionmentioning

confidence: 99%

Complex intervention modelling should capture the dynamics of adaptation

Greenwood-Lee

Hawe

Nettel-Aguirre

et al. 2016

BMC Med Res Methodol

View full text Add to dashboard Cite

show abstract

“…bed usage) and to provide empirical evidence on the effect on performance. Our research extends the use of DES as a methodology for operational problems involving sequential events [ 28 ] by incorporating the incremental LOS associated with complications in the patient flow.…”

Section: Discussionmentioning

confidence: 99%

Quantifying the effect of complications on patient flow, costs and surgical throughputs

Almashrafi

Vanderbloemen

2016

BMC Med Inform Decis Mak

View full text Add to dashboard Cite

Background: Postoperative adverse events are known to increase length of stay and cost. However, research on how adverse events affect patient flow and operational performance has been relatively limited to date. Moreover, there is paucity of studies on the use of simulation in understanding the effect of complications on care processes and resources. In hospitals with scarcity of resources, postoperative complications can exert a substantial influence on hospital throughputs. Methods: This paper describes an evaluation method for assessing the effect of complications on patient flow within a cardiac surgical department. The method is illustrated by a case study where actual patient-level data are incorporated into a discrete event simulation (DES) model. The DES model uses patient data obtained from a large hospital in Oman to quantify the effect of complications on patient flow, costs and surgical throughputs. We evaluated the incremental increase in resources due to treatment of complications using Poisson regression. Several types of complications were examined such as cardiac complications, pulmonary complications, infection complications and neurological complications.

show abstract

“…The ability to analyse the impact on the efficiency and probability of successful outcomes of a clinical procedure from deviations in the task sequence, variations in dependent variables and resource availability could reduce the risk of harm to patients and staff, and improve procedural outcomes. In addition, it would help healthcare providers use available money more efficiently and reduce patient waiting times through optimal use of resources and removal of process bottlenecks (Bayer, 2014).…”

Section: Introductionmentioning

confidence: 99%

Effect of venepuncture process design on efficiency and failure rates: A simulation model study for secondary care

Reed

Remenyte‐Prescott

Rees

2017

International Journal of Nursing Studies

View full text Add to dashboard Cite

Reed, Sean and Remenyte-Prescott, Rasa and Rees, Ben (2017) Effect of venepuncture process design on efficiency and failure rates: a simulation model study for secondary care. International Journal of Nursing Studies,[68][69][70][71][72][73][74][75][76][77][78][79][80][81][82] Access from the University of Nottingham repository: http://eprints.nottingham.ac.uk/41154/1/Effect%20of%20Venepuncture%20process %20design%20on%20efficiency%20and%20failure.pdf Copyright and reuse:The Nottingham ePrints service makes this work by researchers of the University of Nottingham available open access under the following conditions. This article is made available under the Creative Commons Attribution Non-commercial No Derivatives licence and may be reused according to the conditions of the licence. For more details see: http://creativecommons.org/licenses/by-nc-nd/2.5/ A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription.For more information, please contact eprints@nottingham.ac.uk Effect of venepuncture process design on efficiency and failure rates: a simulation model study for secondary care AbstractBackground: Healthcare aims to deliver good patient outcomes. For many clinical procedures there are multiple alternative task sequences that can be performed. These deviations can influence procedure reliability, efficiency of usage of hospital resources and risk to staff and patient safety. Venepuncture is one of the most common invasive procedures in healthcare. Literature of clinical practice shows evidence of wide variability in the procedure order and the duration of each step, which can depend on attributes, such as patient health, sampling method and staff skills.Objective: To use a computer simulation model based on Petri nets to evaluate the impact on outcomes of commonly practiced deviations from the guideline venepuncture procedure and variations in key dependent variables. The outcomes considered include the probability of successfully obtaining a blood sample and the procedure completion time.Design: A computer simulation model was constructed using the Petri net technique which mimics the different variations of the venepuncture procedure. Qualitative and quantitative data for the model was collected from the literature and through interviews and questionnaire responses from doctors and phlebotomists. Statistics on the reliability and duration for different variations were then calculated from the model output.Setting: A digital laboratory to model venepuncture in secondary care.Results: The model showed that the common practice of applying the tourniquet prior to vein identification and releasing it after sample tubes are filled may result in a ten-fold increase in sample haemolysis, compared to the recommended guideline procedure. Equipment la...

show abstract

Simulation modelling and resource allocation in complex services

Cited by 8 publications

References 13 publications

Complex intervention modelling should capture the dynamics of adaptation

Complex intervention modelling should capture the dynamics of adaptation

Quantifying the effect of complications on patient flow, costs and surgical throughputs

Effect of venepuncture process design on efficiency and failure rates: A simulation model study for secondary care

Contact Info

Product

Resources

About