2012
DOI: 10.1136/amiajnl-2011-000454
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A systematic review to evaluate the accuracy of electronic adverse drug event detection

Abstract: Several factors led to inaccurate ADE detection algorithms, including immature underlying information systems, non-standard event definitions, and variable methods for detection rule validation. Few ADE detection algorithms considered clinical priorities. To enhance the utility of electronic detection systems, there is a need to systematically address these factors.

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Cited by 44 publications
(56 citation statements)
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“…27 Most likely, one of the principal structural factors that makes clinical and therapeutic follow-up of the patient difficult for the group of professionals who provide care is related to the availability and adequate use of responsive and uniform information systems for the different levels of care. 28,29 Therefore, using a single electronic medical record or reinforcing the training of professionals in the use of available information tools would be beneficial steps.…”
Section: Comparison With Existing Literaturementioning
confidence: 99%
“…27 Most likely, one of the principal structural factors that makes clinical and therapeutic follow-up of the patient difficult for the group of professionals who provide care is related to the availability and adequate use of responsive and uniform information systems for the different levels of care. 28,29 Therefore, using a single electronic medical record or reinforcing the training of professionals in the use of available information tools would be beneficial steps.…”
Section: Comparison With Existing Literaturementioning
confidence: 99%
“…[6] Although showed many advantages, including the ability to analyse routinely collected (low cost and readily available) data, this system has also barriers to overcome prior to achieve the goal as the standard ADEs detection method. [7] These barriers include the inconsistency of ADEs definition and the lack of ADEs standard nomenclature. [8] What makes the use of this method difficult is the fact that ADEs are usually contextdependent, that means that they are caused by disease-related and patient-related, rather than drug-related conditions.…”
Section: Introduction 11 Introduction On Using Information Technologmentioning
confidence: 99%
“…20,[177][178][179] Early research found these tools to be very effective at detecting renal failure, diarrhoea and hypoglycaemia, but not as good as manual chart review at detecting symptom-related adverse medication events such as altered mental status.…”
Section: Trigger Toolsmentioning
confidence: 99%
“…181 Forster et al in 2011 undertook a systematic review to evaluate the accuracy of electronic tools in identifying AMEs, and found that detection rules were variable, definitions were variable, rules were often not validated against a "gold standard" and few of the detection algorithms considered clinical priorities. 179 Importantly, the review by Forster et al excluded research in the paediatric setting, however these limitations are also likely to exist with information systems used for ADE detection in paediatrics. 179 In contrast, automated adverse event detection was found to have positive effects on quality of care and cost-effectiveness by Lemon et al in the paediatric setting.…”
mentioning
confidence: 99%
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