A Generic Simulation Model of the Relative Cost-Effectiveness of ICU Versus Step-Down (IMCU) Expansion

Mahmoudian-Dehkordi, Amin; Sadat, Somayeh

doi:10.1177/0885066617737303

Cited by 4 publications

(5 citation statements)

References 83 publications

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“…Three studies used economic efficiency analysis with SD to inform decision-making at the micro level. Mahmoudian-Dehkordi and Sadat (2017), for example, compared intensive care units (ICU) versus step-down or intermediate care unit (IMCU) capacity expansion in hospitals [ 34 ]. In terms of geography, twelve of the study settings were focused on the USA, with four studies focused on a low- and middle-income country setting.…”

Section: Resultsmentioning

confidence: 99%

“…All of the studies evaluating services innovation (n = 2) or service delivery innovation (n = 11) or both (n = 1) were in the health sector. These included expanded provision for beds in intensive care units [ 34 ], increasing access to eye care services [ 41 ], screening and treatment services for breast cancer [ 42 ], and more intensive school-based anti-tobacco educational efforts [ 43 ].…”

Section: Resultsmentioning

confidence: 99%

“…beds in intensive care units [34], increasing access to eye care services [41], screening and treatment services for breast cancer [42], and more intensive school-based anti-tobacco educational efforts [43].…”

Section: Plos Onementioning

confidence: 99%

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Using system dynamics modelling to assess the economic efficiency of innovations in the public sector - a systematic review

et al. 2022

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Background Decision-makers for public policy are increasingly utilising systems approaches such as system dynamics (SD) modelling, which test alternative interventions or policies for their potential impact while accounting for complexity. These approaches, however, have not consistently included an economic efficiency analysis dimension. This systematic review aims to examine how, and in what ways, system dynamics modelling approaches incorporate economic efficiency analyses to inform decision-making on innovations (improvements in products, services, or processes) in the public sector, with a particular interest in health. Methods and findings Relevant studies (n = 29) were identified through a systematic search and screening of four electronic databases and backward citation search, and analysed for key characteristics and themes related to the analytical methods applied. Economic efficiency analysis approaches within SD broadly fell into two categories: as embedded sub-models or as cost calculations based on the outputs of the SD model. Embdedded sub-models within a dynamic SD framework can reveal a clear allocation of costs and benefits to periods of time, whereas cost calculations based on the SD model outputs can be useful for high-level resource allocation decisions. Conclusions This systematic review reveals that SD modelling is not currently used to its full potential to evaluate the technical or allocative efficiency of public sector innovations, particularly in health. The limited reporting on the experience or methodological challenges of applying allocated efficiency analyses with SD, particularly with dynamic embedded models, hampers common learning lessons to draw from and build on. Further application and comprehensive reporting of this approach would be welcome to develop the methodology further.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Using system dynamics modelling to assess the economic efficiency of innovations in the public sector - a systematic review

et al. 2022

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“…A primary goal of most simulation research is to identify bottlenecks, detect areas of improvement, and test various "what if" strategies. Simulation is also used in addressing common ED issues, generally with respect to forecasting, capacity planning, resource allocation, staffing and scheduling, measuring performance metrics, geographic optimization, and supply chain management [22,23].…”

Section: Simulation Modeling For Improving Ed Patient Flowsmentioning

confidence: 99%

Bottleneck Detection and Reduction Using Simulation Modeling to Reduce Overcrowding of Hospital Emergency Department

Peng¹,

Yang²,

Strome³

et al. 2020

J. Model. Optim.

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Overcrowding is a common problem in hospital emergency departments (EDs) where the ED service cannot meet care demands within reasonable time frames. This paper introduces a quantitative approach using computer simulation modeling for hospital decision makers to explore trade-offs between efficiency, workload and capacity of EDs. A computer simulation model is built based on the ED of a local hospital to improvement efficiency of the ED patient flow. Bottlenecks of the emergency care process are detected using the built model. The ED performance is examined by applying alternative strategies to reduce patient waiting time and length of stay. The proposed method can be applied to improve the operation efficiency of healthcare systems in the current pandemic, COVID -19.

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“… 1 However, elderly patients are frequently associated with many preoperative comorbidities 2 or may have reduced organ functions, resulting in high complications rates, 3 , 4 high postoperative mortalities and impaired quality of life. 5 , 6 Admission to Intensive Care Unit (ICU) for those elderly patients, will not only lead to high medical costs 7 and heavy medical burdens 8 , but also poor prognosis.…”

Section: Introductionmentioning

confidence: 99%

Prediction of ICU admission after orthopedic surgery in elderly patients

Tang¹,

Li²,

Guo

2021

Pak J Med Sci

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Objectives: Prediction of ICU admission after surgery are important for rational decision-making for different patients in clinical practice. Little information is available about the risk factors of postoperative ICU admission in elderly patients undergoing orthopedic surgery. This study aimed to identify risk factors and develop a predictive model for postoperative ICU admission in elderly patients undergoing orthopedic surgery. Methods: A total of 2826 cases of elderly patients receiving orthopedic surgery from October 2010 to September 2016 were retrospectively collected and analyzed. Logistic regression was used to evaluate the impacts of covariates. Support vector machine (SVM) was employed to develop a predictive model based on all pre-operative covariates and the demographic information. Results: There were 256 patients transferred to ICU after surgery. ASA III or IV and emergency surgery were found to be independent risk factors while neuraxial anesthesia and joint surgery were protective factors. In addition, a SVM-based predictive model was developed, which had a sensitivity of 90.99%, a specificity of 99.10% and an area under ROC curve of 0.9678. Conclusions: Our study revealed that emergency surgery, anesthesia method, surgery type and ASA grade were risk factors to predict postoperative ICU admission in elderly orthopedic patients. doi: https://doi.org/10.12669/pjms.37.4.3371 How to cite this:Tang Y, Li H, Guo Z. Prediction of ICU admission after orthopedic surgery in elderly patients. Pak J Med Sci. 2021;37(4):1179-1184. doi: https://doi.org/10.12669/pjms.37.4.3371 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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A Generic Simulation Model of the Relative Cost-Effectiveness of ICU Versus Step-Down (IMCU) Expansion

Abstract: In terms of operational costs, ICU beds are more cost effective for saving patients than IMCU beds. However, capital costs of setting up ICU versus IMCU beds should be considered for a complete economic analysis.

Cited by 4 publications

References 83 publications

Using system dynamics modelling to assess the economic efficiency of innovations in the public sector - a systematic review

Using system dynamics modelling to assess the economic efficiency of innovations in the public sector - a systematic review

Bottleneck Detection and Reduction Using Simulation Modeling to Reduce Overcrowding of Hospital Emergency Department

Prediction of ICU admission after orthopedic surgery in elderly patients

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