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Related Concept Videos

One-Compartment Open Model for IV Bolus Administration: Estimation of Clearance00:56

One-Compartment Open Model for IV Bolus Administration: Estimation of Clearance

Clearance is a key pharmacokinetic parameter that quantifies the volume of body fluid from which a drug is entirely removed within a specific time frame. It is crucial in assessing how a drug is eliminated from the body and has critical clinical applications.
In the one-compartment open model for intravenous (IV) bolus administration, clearance is estimated by dividing the elimination rate by the plasma drug concentration. This equation leverages the elimination rate constant and the apparent...
One-Compartment Open Model for IV Bolus Administration: Estimation of Elimination Rate Constant, Half-Life and Volume of Distribution01:09

One-Compartment Open Model for IV Bolus Administration: Estimation of Elimination Rate Constant, Half-Life and Volume of Distribution

The one-compartment open model is a simplified approach used in pharmacokinetics to understand the distribution and elimination of a drug administered through an intravenous bolus. This model assumes rapid drug dispersal throughout the body and elimination using a first-order process. Key pharmacokinetic parameters, such as the elimination rate constant (k), half-life (t1/2), and the apparent volume of distribution (Vd), can be estimated from this model. The elimination rate is calculated from...
One-Compartment Model: IV Infusion01:09

One-Compartment Model: IV Infusion

Intravenous (IV) infusion is often utilized when continuous and controlled drug delivery is necessary, such as during surgery or in the treatment of chronic diseases. This method offers numerous advantages, including immediate drug action, precise control over dosage, and bypassing the first-pass metabolism.
The one-compartment model for IV infusion uses mathematical equations to describe the rate of change in drug quantity in the body. At steady-state or infusion equilibrium, the drug input...
Two-Compartment Open Model: IV Infusion01:15

Two-Compartment Open Model: IV Infusion

A two-compartment model is a vital tool in pharmacokinetics, providing an essential understanding of drug behavior, especially for those administered via zero-order intravenous infusion. This model outlines two compartments: the central compartment, where elimination occurs, and the peripheral compartment.
The model illustrates the decrease in plasma drug concentration from the central compartment with a specific equation. It shows that under steady-state conditions, the drug's input rate...
One-Compartment Open Model for IV Bolus Administration: General Considerations01:19

One-Compartment Open Model for IV Bolus Administration: General Considerations

The one-compartment model is a pharmacokinetic tool that models the body as a single, uniform compartment, facilitating the understanding of drug distribution and elimination. This model is particularly beneficial for intravenous (IV) bolus administration, where the drug rapidly circulates throughout the body.
The drug's presence in the body is defined by an equation representing the difference between the rates of drug entry and exit. Key parameters—elimination rate constant, half-life,...
Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations01:15

Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations

Gentamicin, an aminoglycoside antibiotic, is commonly administered via intermittent intravenous infusion to treat severe infections. An intermittent one-hour infusion of gentamicin, administered at eight-hour intervals, allows for precise control of plasma drug concentrations, minimizing toxicity while ensuring therapeutic efficacy. Pharmacokinetic principles govern the dynamics of plasma concentrations and can be mathematically described using specific equations.The plasma drug concentration...

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Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies
10:38

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies

Published on: January 16, 2019

Estimating ICU bed capacity using discrete event simulation.

Zhecheng Zhu1, Bee Hoon Hen, Kiok Liang Teow

  • 1Department of Health Services and Outcomes Research, National Healthcare Group, Singapore. zhecheng_zhu@nhg.com.sg

International Journal of Health Care Quality Assurance
|March 30, 2012
PubMed
Summary

This study developed a discrete event simulation (DES) model to optimize intensive care unit (ICU) bed capacity. The model balances patient service levels with cost-effectiveness, aiding hospital resource management.

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Last Updated: May 23, 2026

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies
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Published on: January 16, 2019

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Published on: May 20, 2018

Area of Science:

  • Healthcare Operations Research
  • Hospital Management Systems

Background:

  • Intensive care units (ICUs) are critical for critically ill patients.
  • ICU bed capacity significantly impacts hospital performance, affecting ambulance diversions, surgery cancellations, and resource allocation.

Purpose of the Study:

  • To develop a discrete event simulation (DES) model for determining optimal ICU bed capacity.
  • To balance patient service levels with cost-effectiveness in ICU resource management.

Main Methods:

  • A DES model was created to represent complex ICU patient flow.
  • Actual operational data (arrivals, length of stay) were used to calibrate the model.
  • The model was validated using open and black box testing methods.

Main Results:

  • A 12-month dataset from a 13-bed ICU was utilized.
  • The DES model accurately reflected system variations and validated against real-world data.
  • The model demonstrated flexibility in simulating 'what-if' scenarios for bed capacity planning.

Conclusions:

  • Discrete event simulation (DES) provides a valuable tool for describing current ICU operations.
  • DES facilitates the simulation of future scenarios, supporting informed planning for ICU bed capacity.