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Related Concept Videos

Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

543
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
543
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

253
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
253
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

330
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
330
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

247
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
247
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

516
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
516
Inhaled Medications01:23

Inhaled Medications

769
Inhaled medications are crucial for managing chronic obstructive pulmonary disease (COPD) and asthma. They are essential for effective treatment and control, ensuring optimal respiratory health and well-being. Inhaled medication delivers drugs directly to the lungs, providing a rapid onset of action and reducing systemic side effects compared to oral or injectable medications. Three primary types of inhalation devices are used to administer these medications: nebulizers, metered-dose inhalers...
769

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Exploring Inpatient Medication Patterns: A Big Data and Multilevel Approach.

Figaro L Loresto1, John Welton, Stephanie Grim

  • 1Author Affiliations: Nurse Quality Research Specialist (Dr Loresto), Denver Health and Hospital Authority, Colorado; Professor (Dr Welton), University of Colorado College of Nursing; and Senior Data Reporting Analyst (Ms Grim), Children's Hospital Colorado, Aurora; and Biostatistician (Ms Valdez) and Research Assistant (Ms Eron), Denver Health and Hospital Authority, Colorado.

The Journal of Nursing Administration
|May 29, 2019
PubMed
Summary
This summary is machine-generated.

Medication administration delays averaged 12 minutes. Patient demographics like Spanish language and nurse certification significantly impacted timing, highlighting multifactorial influences on inpatient medication accuracy.

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Area of Science:

  • Healthcare Operations
  • Nursing Practice
  • Patient Safety

Background:

  • Inpatient medication administration is critical for patient outcomes.
  • Understanding factors influencing medication timing is essential for improving care quality.

Purpose of the Study:

  • To explore patterns in inpatient medication administration.
  • To identify variables affecting the time between scheduled and actual medication delivery.

Main Methods:

  • Utilized data from multiple sources for analysis.
  • Employed a 3-level hierarchical linear regression model.
  • Calculated and compared intraclass correlation coefficients (ICCs).

Main Results:

  • Average medication delay was 12 minutes (SD, 48.8).
  • Patient ICCs were lower when 'unit' replaced 'nurse' as the third level (0.541 vs 0.444).
  • Spanish-speaking patients experienced 2.3- to 4.2-minute delays; certified nurses administered meds 1.6 minutes faster.

Conclusions:

  • Medication administration is influenced by multiple factors, including nursing staff.
  • Nursing leaders should consider patient demographics and unit characteristics for optimization.
  • Addressing these factors can lead to improved medication administration timeliness and patient safety.