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Simio LLC discrete-event simulation models
Discrete Event Simulation Models, supplied by Simio LLC, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/discrete+event+simulation+model/discrete+event+simulation+model/pmc10783703-114-16-24
Average 90 stars, based on 1 article reviews
discrete-event simulation models - by Bioz Stars, 2026-10
90/100 stars

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Article Title: Screening for Latent Tuberculosis Infection in Migrants With CKD: A Cost-effectiveness Analysis.
Article Snippet: Results: Screening with IGRA was superior to the tuberculin skin test in all situations.. Screening with IGRA was less expensive and resulted in better outcomes compared to no screening in those initiating dialysis therapy from countries with an elevated TB incidence.. In individuals with late-stage CKD, screening with IGRA was only cost-effective in those 60 years or older (cost per QALY gained, <$48,000) from countries with an elevated TB incidence.

Article Title: Simulation model of the relationship between cesarean section rates and labor duration.
Article Snippet: Cesarean delivery is the most common major abdominal surgery in many parts of the world, and it accounts for nearly onethird of births in the United States.. For a patient who requires a C-section, allowing prolonged labor is not recommended because of the increased risk of infection.. However, for a patient who is capable of a successful vaginal delivery, performing an unnecessary C-section can have a substantial adverse impact on the patient’s future health.

Article Title: Cost-effectiveness of post-landing latent tuberculosis infection control strategies in new migrants to Canada
Article Snippet: A discrete event simulation (DES) model was developed in Simio and run using Simio Replication Runner (Version 8.146.14121, Simio LLC, Sewickley, PA).

Control:

Article Title: Systems Engineering Methods for Enhancing the Value Stream in Public Health Preparedness: The Role of Markov Models, Simulation, and Optimization
Article Snippet: The NC LHDs shared the details of their clinic operations to inform development of the discrete event simulation (DES) models and facilitate the creation of reasonably accurate 3D depictions of the clinics using Simio ® simulation software. .. 34 A sample model is shown in . fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window caption a7 Snapshot of a Simio ® Discrete Event Simulation model animation of a mass vaccination clinic a a Waiting clients are guided into the clinic by a crowd control agent. ..



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Markov and the <t>Discrete</t> <t>Event</t> <t>Simulation</t> models used in the analysis. P1: Probability of graft failure after transplantation; P2: Probability of death after transplantation; P3: Probability of death after graft failure; P4: Probability of death while waitlisted. T1: Time-to-graft failure after transplantation; T2: Time-to-death after transplantation; T3: Time-to-death after graft failure; T4: Time-to-death while waitlisted
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Markov and the Discrete Event Simulation models used in the analysis. P1: Probability of graft failure after transplantation; P2: Probability of death after transplantation; P3: Probability of death after graft failure; P4: Probability of death while waitlisted. T1: Time-to-graft failure after transplantation; T2: Time-to-death after transplantation; T3: Time-to-death after graft failure; T4: Time-to-death while waitlisted

Journal: Health Economics Review

Article Title: Time-to-event analysis in economic evaluations: a comparison of modelling methods to assess the cost-effectiveness of transplanting a marginal quality kidney

doi: 10.1186/s13561-021-00312-4

Figure Lengend Snippet: Markov and the Discrete Event Simulation models used in the analysis. P1: Probability of graft failure after transplantation; P2: Probability of death after transplantation; P3: Probability of death after graft failure; P4: Probability of death while waitlisted. T1: Time-to-graft failure after transplantation; T2: Time-to-death after transplantation; T3: Time-to-death after graft failure; T4: Time-to-death while waitlisted

Article Snippet: Decision analytic models: a Markov model and a Discrete event simulation model were constructed using TreeAge Pro 2020 with the purpose of estimating the incremental costs and quality-adjusted life years (QALY) (Fig. ).

Techniques: Transplantation Assay

Cost (AUD), QALY and net monetary benefit per patient by  model  and time-horizon for the Markov and DES models

Journal: Health Economics Review

Article Title: Time-to-event analysis in economic evaluations: a comparison of modelling methods to assess the cost-effectiveness of transplanting a marginal quality kidney

doi: 10.1186/s13561-021-00312-4

Figure Lengend Snippet: Cost (AUD), QALY and net monetary benefit per patient by model and time-horizon for the Markov and DES models

Article Snippet: Decision analytic models: a Markov model and a Discrete event simulation model were constructed using TreeAge Pro 2020 with the purpose of estimating the incremental costs and quality-adjusted life years (QALY) (Fig. ).

Techniques: