European Journal of Clinical Pharmacology

, Volume 69, Issue 2, pp 255–259 | Cite as

Improvement in the detection of adverse drug events by the use of electronic health and prescription records: An evaluation of two trigger tools

  • Ugochi Nwulu
  • Krishnarajah Nirantharakumar
  • Rachel Odesanya
  • Sarah E. McDowell
  • Jamie J. Coleman
Pharmacoepidemiology and Prescription



To test if two of the adverse event triggers proposed by the Institute of Healthcare Improvement can detect adverse drug events (ADEs) in a UK secondary care setting, using an electronic prescribing and health record system.


In order to identify triggers for over-anticoagulation and potential opioid overdose and we undertook a retrospective review of electronic medical and prescription records from 54,244 hospital admissions over a 1-year period, alongside a review of medical incident reports. Once prescription data were linked to triggers and duplicates were removed, case note review eliminated the false positive ADEs. Additionally, we tested the use of an electronic algorithm for the International Normalized Ratio (INR) ≥6 trigger.


The INR ≥6 electronic trigger identified 46 potential ADEs and the naloxone electronic trigger identified 82 ADEs. Based on the available case note review, the INR ≥6 trigger had a positive predictive value (PPV) of 38 % (14/37) and the naloxone trigger had a PPV of 91 % (61/67). The electronic algorithm for the INR ≥6 trigger identified 12 ADEs, thus reducing the need of case note review. This was in comparison with one and two critical incidents reported in the trust medical incident reports system, which respectively related to over-coagulation with warfarin and over-sedation with opioid medication.


We have integrated automated and manual methods of detecting ADEs using previously defined triggers. Incorporating electronic triggers in already established electronic health records with prescription and laboratory test data can improve the detection of ADEs, and potentially lead to methods to avert them.


Adverse drug events Medication errors Trigger tool Electronic health records Computerized physician order entry 



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, NHS Partner Trusts, University of Birmingham or the CLAHRC-BBC Theme 9 Management/Steering Group.

Competing interest statement

UN, SEM and JJC work within the University Hospital Birmingham NHS Foundation Trust, which is collaborating with CSE Healthcare Systems to commercialise the PICS system in the UK. All other authors report no financial relationships with commercial entities that might have an interest in the submitted work. No spouses, partners, or children of the authors have relationships with commercial entities that might have an interest in the submitted work. None of the authors have non-financial interests that may be relevant to the submitted work

Statements of contribution

All authors had full access to all of the data in the study and can take responsibility for the integrity of the data and the accuracy of the data analysis. All authors contributed to the writing of the manuscript, the interpretation of data, and approved the final version.


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Ugochi Nwulu
    • 4
  • Krishnarajah Nirantharakumar
    • 3
  • Rachel Odesanya
    • 3
  • Sarah E. McDowell
    • 1
  • Jamie J. Coleman
    • 1
    • 2
  1. 1.University Hospitals Birmingham NHS Foundation TrustBirminghamUK
  2. 2.College of Medical and Dental SciencesUniversity of BirminghamBirminghamUK
  3. 3.School of Health and Population SciencesUniversity of BirminghamBirminghamUK
  4. 4.Queen Elizabeth Hospital BirminghamUniversity Hospitals Birmingham NHS Foundation TrustBirminghamUK

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