Automatic, real-time detection of adverse drug events in paediatric hospitals

Automatic, real-time detection of adverse drug events in paediatric hospitals

Preventing patient harm in paediatric hospitals: automatic, real-time detection of adverse drug events using data from electronic clinical information systems


Project description

An adverse drug event (ADE) refers to injury resulting from the use of a drug and may be due to a medication error or an adverse drug reaction. ADEs are a persistent and important problem in paediatric hospitals worldwide in terms of morbidity, mortality and cost. ADEs are frequent, but often preventable if detected early. Even for non-preventable ADEs, early detection enables healthcare providers to intervene to mitigate their effects and lessen their severity. Big data routinely collected from clinical information systems, especially recently available medication data from the electronic medication management systems (eMMS), presents a new opportunity to develop ADE detection algorithms using advanced statistical techniques and methodologies.

Project members


Associate Professor Ling Li
Associate Professor


Professor Johanna Westbrook

Professor


Dr Kasun Rathnayake

Postdoctoral Research Fellow

Project members - external

Prof Ric Day – UNSW

A/Prof Cheryl McCullagh – CEO, Sydney Children’s Hospital Network
Adjunct Fellow, Macquarie University

Dr Alain Koyama
Honorary Research Fellow, Macquarie University

Content owner: Australian Institute of Health Innovation Last updated: 23 Oct 2019 8:27am

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