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Calculating drug dosage and accumulation in multiple-dose regimens is crucial for achieving therapeutic efficacy while avoiding toxicity. This involves determining the plasma drug concentrations over time to optimize dosing schedules. The principle of superposition is fundamental in this process, allowing for the prediction of drug concentration in plasma following multiple doses based on single-dose data.The principle of superposition asserts that the plasma concentration-time curves from...
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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...
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Assessing the reliability of an automated dose-rounding algorithm.

Kevin B Johnson1, Yun-Xian Ho, S Andrew Spooner

  • 1Biomedical Informatics, Pediatrics, Vanderbilt University School of Medicine, 2209 Garland Ave, Room 428, Nashville, TN 37232, United States.

Journal of Biomedical Informatics
|June 25, 2013
PubMed
Summary

Automated pediatric dose rounding using the STEPSTools algorithm is feasible, showing improved performance over manual methods in a pilot study. This validates decision-support systems for safer e-prescribing in pediatrics.

Keywords:
Biomedical informaticsClinical practiceComputer softwareElectronic prescribingMedical informaticsPrescriptions

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Area of Science:

  • Pediatric pharmacology
  • Health informatics
  • Clinical decision support

Background:

  • Pediatric dose rounding is complex and often unsupported by electronic prescribing systems.
  • Automation of pediatric dose rounding can improve safety and efficiency.

Purpose of the Study:

  • To validate an automated dose-rounding algorithm (STEPSTools) for pediatric prescriptions.
  • To assess the performance of STEPSTools against manually prescribed doses.

Main Methods:

  • Developed STEPSTools based on expert consensus and therapeutic/toxic windows.
  • Refined the algorithm using a 60% subsample of electronic prescriptions.
  • Tested concordance on the remaining 40% and surveyed pediatricians on discrepant cases.

Main Results:

  • STEPSTools matched or exceeded manual recommendations in 76% of test cases.
  • Pediatricians preferred STEPSTools recommendations in 14 of 24 discrepant cases (p<0.05).
  • Estimated 82% performance with additional dose-selection rules.

Conclusions:

  • Automated dose rounding is a viable approach for e-prescribing systems.
  • Validation of decision-support systems is crucial for iterative performance improvement.