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Deriving Dose Limits for Warnings in Electronic Prescribing Systems

Statistical Analysis of Prescription Data at University Hospital Birmingham, UK

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Abstract

Introduction: Electronic decision support can reduce medication errors, and dose-range checking is one element of that support.

Objective: The aim of this study was to design an approach to setting upper dose warning limits in electronic prescribing systems where there are historical data on dosing.

Method: We used historical data on 56 drug-form combinations for which over 100 prescriptions had been issued between 1 June 2009 and 31 May 2010 in a bespoke electronic prescribing system at University Hospital Birmingham, UK. First, two experts derived dose limits for each drug-form combination, then the drugs were randomly divided into a training set and a test set. A variation of the ‘Nearest Rank’ approach to estimate statistical limits was used to derive the percentile with the optimal sensitivity and specificity.

Results: For the 28 drug-form combinations in the test set, the 86th percentile of dose gave a mean sensitivity of 95.3% and a mean specificity of 97.9% for warning limits, representing the highest reasonable dose; the 96th percentile gave a mean sensitivity of 90.2% and mean specificity of 99.5% for disallow limits, beyond which no dose should be prescribed.

Conclusions: Dosing decision support within electronic prescribing systems can be derived by statistical analysis of historical prescription data. We advocate a combined theoretical and statistical derivation of dose checking rules in order to ensure that prescribers are alerted appropriately to potentially toxic doses.

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Acknowledgements

We would like to thank Dr Peter G. Nightingale for providing independent statistical support.

This work was funded by the National Institute for Health Research (NIHR) through the Collaborations for Leadership in Applied Health Research and Care for Birmingham and Black Country (CLAHRC-BBC) programme.

The views expressed in this publication are not necessarily those of the NIHR, the Department of Health, National Health Service Partner Trusts, the University of Birmingham or the CLAHRC-BBC Theme 9 Management/Steering Group. All authors declare no conflicts of interest that are directly relevant to the content of this study.

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Authors and Affiliations

  1. Queen Elizabeth Hospital Birmingham, University Hospital Birmingham NHS Foundation Trust, Birmingham, UK

    Jamie J. Coleman & James Hodson

  2. Department of Clinical Pharmacology, School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, UK

    Jamie J. Coleman & Robin E. Ferner

  3. West Midlands Centre for Adverse Drug Reactions, City Hospital, Birmingham, UK

    Jamie J. Coleman & Robin E. Ferner

Authors
  1. Jamie J. Coleman
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  2. James Hodson
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  3. Robin E. Ferner
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Correspondence to Jamie J. Coleman.

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Coleman, J.J., Hodson, J. & Ferner, R.E. Deriving Dose Limits for Warnings in Electronic Prescribing Systems. Drug Saf 35, 291–298 (2012). https://doi.org/10.2165/11594810-000000000-00000

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  • DOI: https://doi.org/10.2165/11594810-000000000-00000

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