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Related Concept Videos

Variability: Analysis01:11

Variability: Analysis

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Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
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Dosage Regimen: Individualization01:24

Dosage Regimen: Individualization

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Individualization in dosing regimens is the customization of medication doses for individual patients. Its necessity arises from the goal of maximizing therapeutic benefits while minimizing risks. This approach is pivotal because human responses to drugs can vary widely; what is effective for one person may be inadequate or excessive for another. Interpatient (intersubject) variability refers to differences in drug responses between individuals, while intrapatient (intrasubject) variability...
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Regression Toward the Mean01:52

Regression Toward the Mean

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Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
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Compartment Models: Two-Compartment Model01:20

Compartment Models: Two-Compartment Model

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The two-compartment model divides the body into central and peripheral compartments to account for varying blood perfusion rates among organs and tissues, affecting drug distribution. The central compartment includes blood and highly perfused tissues with rapid drug distribution, while the peripheral compartment contains tissues with slower drug distribution. After a single IV bolus dose, the drug concentration is high in plasma and low in tissues. The drug distribution between compartments...
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Two-Compartment Open Model: Extravascular Administration01:12

Two-Compartment Open Model: Extravascular Administration

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The two-compartment model for extravascular administration represents a drug's absorption and distribution process. It features a central compartment, where the drug is first absorbed, and a peripheral compartment, which illustrates the drug's distribution throughout the body. The rate of change in drug concentration in the central compartment is calculated by three exponents: absorption, distribution, and elimination.
The absorption exponent (ka) indicates the speed at which the drug...
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Volume of Distribution01:20

Volume of Distribution

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The apparent volume of distribution (Vd) is a crucial pharmacokinetic parameter representing the hypothetical body fluid volume into which a drug disperses. It is calculated based on the total amount of drug in the body (estimated from the administered dose and bioavailability) divided by the plasma drug concentration. The total amount of drug in the body does not directly refer to the dose given but is derived by accounting for absorption, distribution, metabolism, and excretion processes.
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Author Spotlight: Unveiling Prognostic Indicators in Heart Failure - The Role of Phase Angle and Bioelectrical Impedance Analysis
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Emergency department visit volume variability.

Seung Woo Kang1, Hyun Soo Park1

  • 1Department of Emergency Medicine, Jeju National University Hospital, Jeju, Korea.

Clinical and Experimental Emergency Medicine
|October 19, 2016
PubMed
Summary
This summary is machine-generated.

Emergency department (ED) patient visit volumes show high daily variability, not a normal distribution. Relying on average ED visits is insufficient for effective operational planning.

Keywords:
CrowdingEfficiencyEmergency service, hospitalManagement information systems

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Area of Science:

  • Emergency Medicine
  • Healthcare Operations Research
  • Health Services Research

Background:

  • Patient visit volume is a critical variable for emergency department (ED) operations.
  • Current ED operational planning often relies on average patient visit volumes.
  • Understanding ED patient visit variability is crucial but poorly understood.

Purpose of the Study:

  • To evaluate the variability of patient visits in emergency departments.
  • To determine if average ED patient visit volumes adequately represent operational demands.

Main Methods:

  • Analysis of nationwide ED patient visit data from the National Emergency Department Information System.
  • Inclusion of hourly ED visit volumes over 365 days from 141 EDs.
  • Statistical analysis of visit volume variability to assess the representativeness of the average.

Main Results:

  • A total of 4,672,275 patient visits were analyzed from 2013.
  • Daily ED patient visits exhibited wide dispersion and positive skewness.
  • The distribution of daily visits was not symmetric or normally distributed.

Conclusions:

  • Daily ED patient visit variability is substantial and does not follow a normal distribution.
  • Average visit volume is an inadequate metric for representing ED operational needs.
  • Rethinking operational strategies based on visit variability is necessary.