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Developing a Decision Support System at ED triage for predicting health outcomes

Year:
2020
Duration:
26 months
Approved budget:
$239,389.00
Researchers:
Dr Zhenqiang Wu
,
Dr Kate Allan
,
Dr Laura Chapman
Health issue:
Other (generic health or health services)
Proposal type:
Precision Driven Health Postdoctoral Fellowship
Lay summary
Emergency department overcrowding is a major global healthcare issue. The consequences are well-established, usually affecting patients (poor outcomes), staff (stressed) and healthcare system (long length of stay). Without increases number of EDs and staff, an effective way is to optimise the use of existing resources. This study intends to develop a Decision Support System at ED triage time to predict hospital admission and longer ED length of stay by using a wide range of routinely collected big data (DHB’s Health Records System and MoH database). This system has the potential to meet the ED health target of “shorter stay” and “lower hospital admission rates” by accurately identifying high-risk patients at an early stage of ED, and making more effective interventions to them. If so, this Decision Support System can be widely used by ED triage assessors in the near future, with the potential to improve the quality of acute care.