Journal of Pharmacokinetics and Biopharmaceutics

, Volume 20, Issue 1, pp 63–94

Measuring the predictive performance of computer-controlled infusion pumps

  • John R. Varvel
  • David L. Donoho
  • Steven L. Shafer

DOI: 10.1007/BF01143186

Cite this article as:
Varvel, J.R., Donoho, D.L. & Shafer, S.L. Journal of Pharmacokinetics and Biopharmaceutics (1992) 20: 63. doi:10.1007/BF01143186


Current measures of the performance of computer-controlled infusion pumps (CCIPs) are poorly defined, of little use to the clinician using the CCIP, and pharmacostatistically incorrect. We propose four measures be used to quantitate the performance of CCIPs: median absolute performance error (MDAPE), median performance error (MDPE), divergence, and wobble. These measures offer several significant advantages over previous measures. First, their definitions are based on the performance error as a fraction of the predicted (rather than measured) drug concentration, making the measures much more useful to the clinician. Second, the measures are defined in a way that addresses the pharmacostatistical issue of appropriate estimation of population parameters. Finally, the measure of inaccuracy, MDAPE, is defined in a way that is consistent with iteratively reweighted least squares nonlinear regression, a commonly used method of estimating pharmacokinetic parameters. These measures make it possible to quantitate the overall performance of a CCIP or to compare the predictive performance of CCIPs which differ in either general approach (e.g., compartmental model driven vs. plasma efflux approach), pump mechanics, software algorithms, or pharmacokinetic parameter sets.

Key words

anesthesia computer-assisted equipment infusion pump performance pharmacokinetics predictive performance 

Copyright information

© Plenum Publishing Corporation 1992

Authors and Affiliations

  • John R. Varvel
    • 1
  • David L. Donoho
    • 2
  • Steven L. Shafer
    • 3
  1. 1.Department of AnesthesiaSt. Elizabeth's Community Health CenterLincoln
  2. 2.Department of StatisticsUniversity of CaliforniaBerkeley
  3. 3.Department of AnesthesiaStanford University Medical CenterStanford

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