Julie Daltrey
Nurse Practitioner / Teaching Fellow, The University of Auckland, NZ
Julie has been a nurse since 1999. She is a professional teaching fellow and PhD candidate at the University of Auckland (UoA). Her PhD is focused on Developing a Deterioration Early Warning System (DEWS) to support residential aged care staff to recognise and respond to acute events in people living in care. Her research interests focus on older people and she was recently part of a team investigating strategies to support older people living with dementia mate wareware and their care partners to manage and promote continence.
Recognised for academic, clinical, and leadership contribution to nursing. She is currently the clinical lead at Te Tāhū Hauora for aged residential care (ARC) related projects and co-authored the 2023 edition of the National Frailty Care Guides. |
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Julie is a recipient of the Denis Pickup Clinical Educator Award (UoA) for contribution to the Nurse Practitioner Training Programme and an New Zealand Nurses Organisation national “Services to Nursing” award. Quality improvement projects in the Waikato region include the introduction of the SBARR communication tool to the hospital and the development of a best practice guide for the management of Scabies in ARC.
Drivers of Innovation in Aged Care - The Deterioration Early Warning System
This presentation provides a brief overview of the Deterioration Early Warning System (DEWS), a newly developed evidence based standardised tool to support residential aged care (RAC) staff with the timely identification of and response to acute deterioration in people living in care. DEWS has been developed, co-designed and feasibility tested in New Zealand. It uses the track and trigger (health surveillance & response) concepts of other national and international early warning systems and applies them to the unique population and clinical context of RAC. Leaders of RAC have advocated for sector wide implementation. To support this process DEWS is currently being converted to work in digital patient management systems. This will be supported with a national on-line education module. A planned staged implementation is underway providing an opportunity to collect hard outcome measures.