Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Two-Compartment Open Model: IV Infusion01:15

Two-Compartment Open Model: IV Infusion

442
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...
442
Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations01:15

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

108
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...
108
One-Compartment Open Model for IV Bolus Administration: Estimation of Clearance00:56

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

229
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...
229
One-Compartment Model: IV Infusion01:09

One-Compartment Model: IV Infusion

382
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...
382
Determination of Multiple Dosing Parameters: Loading and Maintenance Doses01:25

Determination of Multiple Dosing Parameters: Loading and Maintenance Doses

110
A loading dose is an essential pharmacological strategy to rapidly achieve the target plasma drug concentration necessary for an immediate therapeutic effect. This approach is especially critical for drugs characterized by slow absorption or extended half-lives, where delaying therapeutic plasma levels could compromise treatment outcomes. By administering a loading dose, clinicians ensure a prompt onset of drug action, even for agents with complex pharmacokinetic profiles.Achieving steady-state...
110
Drug Accumulation During Multiple Dosing: Intermittent IV Infusions01:24

Drug Accumulation During Multiple Dosing: Intermittent IV Infusions

120
Intermittent intravenous (IV) infusion is a method of drug administration where medications are delivered over short infusion periods followed by intervals of no drug delivery. This approach helps to prevent sustained high drug concentrations in the bloodstream, reducing the risk of adverse effects associated with prolonged exposure. Unlike continuous infusion, steady-state concentrations may not be achieved during a single dosing cycle but can be reached through repeated...
120

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Analyzing longitudinal antidiabetic medication patterns: a data-driven clustering framework.

BMC medical informatics and decision making·2026
Same author

Co-use of opioids and cannabis versus single-substance use: a national analysis of US adults.

Frontiers in public health·2025
Same author

Disparities in objective sleep measures among individuals who have undergone polysomnographic studies.

Frontiers in sleep·2025
Same author

Recent Trends in Cigarette and HTP Use in Japan: A Scoping Review.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco·2025
Same author

Diabetes Belt has lower efficiency in providing diabetes preventive care than surrounding counties.

Health services & outcomes research methodology·2025
Same author

Exploring Polysubstance Use with a Data Mining Approach in Individuals with and without Mental Health Conditions.

Journal of psychoactive drugs·2025

Related Experiment Video

Updated: Dec 6, 2025

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
08:34

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies

Published on: February 6, 2019

20.8K

Scheduling patient appointment in an infusion center: a mixed integer robust optimization approach.

Mona Issabakhsh1, Seokgi Lee2, Hyojung Kang3

  • 1Department of Industrial Engineering, University of Miami, 1251 Memorial Drive, 281, Coral Gables, FL, 33146, USA.

Health Care Management Science
|October 12, 2020
PubMed
Summary

Optimizing infusion center scheduling reduces patient wait times and staff overtime. Mathematical models and heuristics improve chemotherapy appointment scheduling for better patient care and operational efficiency.

Keywords:
Adaptive large neighborhood searchInfusion appointment schedulingInfusion time uncertaintyOperations researchRobust optimization

More Related Videos

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
08:25

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

Published on: April 11, 2018

15.7K
Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
05:18

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant

Published on: October 6, 2023

1.7K

Related Experiment Videos

Last Updated: Dec 6, 2025

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
08:34

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies

Published on: February 6, 2019

20.8K
Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
08:25

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

Published on: April 11, 2018

15.7K
Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
05:18

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant

Published on: October 6, 2023

1.7K

Area of Science:

  • Operations Research
  • Healthcare Management
  • Biomedical Informatics

Background:

  • Infusion centers face increasing demand, leading to prolonged patient wait times.
  • Uncertainty in chemotherapy session duration exacerbates wait times and staff workload.
  • Long wait times negatively impact vulnerable cancer patients' physical and emotional well-being.

Purpose of the Study:

  • To develop mathematical models for optimizing infusion appointment scheduling.
  • To minimize patient wait times, overall completion time (makespan), and resource utilization.
  • To create robust scheduling methods that account for variable patient infusion durations.

Main Methods:

  • A mixed integer programming infusion appointment scheduling (IAS) model was developed.
  • A mixed integer programming robust slack allocation (RSA) model was designed for schedule reliability.
  • A robust scheduling heuristic (RSH) using adaptive large neighborhood search (ALNS) was created for large-scale application.

Main Results:

  • Computational experiments demonstrated the effectiveness of the developed scheduling models.
  • The models significantly improved upon the existing scheduling system at a cancer center.
  • Robust approaches (RSA and RSH) yielded more reliable schedules compared to deterministic methods under time variations.

Conclusions:

  • Optimized scheduling models can effectively reduce patient wait times and improve operational efficiency in infusion centers.
  • Robust scheduling strategies are crucial for managing variability in patient treatment times.
  • The developed heuristic (RSH) enables the application of these optimization techniques to real-world, large-scale infusion center operations.