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Methods Inf Med 2017; 56(04): 276-282
DOI: 10.3414/ME16-01-0126
Paper
Schattauer GmbH

Data Requirements for the Correct Identification of Medication Errors and Adverse Drug Events in Patients Presenting at an Emergency Department

Bettina Plank-Kiegele
1   Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
,
Thomas Bürkle
2   Institute for Medical Informatics, Bern University of Applied Science BFH, Biel, Switzerland
,
Fabian Müller
1   Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
,
Andrius Patapovas
3   Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
,
Anja Sonst
4   Department of Emergency Medicine, Klinikum Fürth, Fürth, Germany
,
Barbara Pfistermeister
1   Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
,
Harald Dormann
4   Department of Emergency Medicine, Klinikum Fürth, Fürth, Germany
,
Renke Maas
1   Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
› Author Affiliations Funding This research project was supported by The German Federal Ministry of Health within the ‘German Coalition for Patient Safety’ (http://www.aktionsbuendnis-pa tientensicherheit.de/) by a BMG grant II A 5–2509 ATS 003 to HD, RM and TB.
Further Information

Publication History

received: 07 November 2016

accepted in revised form: 01 April 2017

Publication Date:
24 January 2018 (online)

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Summary

Background: Adverse drug events (ADE) involving or not involving medication errors (ME) are common, but frequently remain undetected as such. Presently, the majority of available clinical decision support systems (CDSS) relies mostly on coded medication data for the generation of drug alerts. It was the aim of our study to identify the key types of data required for the adequate detection and classification of adverse drug events (ADE) and medication errors (ME) in patients presenting at an emergency department (ED).

Methods: As part of a prospective study, ADE and ME were identified in 1510 patients presenting at the ED of an university teaching hospital by an interdisciplinary panel of specialists in emergency medicine, clinical pharmacology and pharmacy. For each ADE and ME the required different clinical data sources (i.e. information items such as acute clinical symptoms, underlying diseases, laboratory values or ECG) for the detection and correct classification were evaluated.

Results: Of all 739 ADE identified 387 (52.4%), 298 (40.3%), 54 (7.3%), respectively, required one, two, or three, more information items to be detected and correctly classified. Only 68 (10.2%) of the ME were simple drug-drug interactions that could be identified based on medication data alone while 381 (57.5%), 181 (27.3%) and 33 (5.0%) of the ME required one, two or three additional information items, respectively, for detection and clinical classification.

Conclusions: Only 10% of all ME observed in emergency patients could be identified on the basis of medication data alone. Focusing electronic decisions support on more easily available drug data alone may lead to an under-detection of clinically relevant ADE and ME.

Keywords

Adverse drug event - medication error - side effect - medication data - prospective study - clinical decision support system
 

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