The Geriatric Emergency Care Applied Research (GEAR) network approach: a protocol to advance stakeholder consensus and research priorities in geriatrics and dementia care in the emergency department.

Increasingly, older adults are turning to emergency departments (EDs) to address healthcare needs. To achieve these research demands, infrastructure is needed to both generate evidence of intervention impact and advance the development of implementation science, pragmatic trials evaluation and dissemination of findings from studies addressing the emergency care needs of older adults. The Geriatric Emergency Care Applied Research Network (https://gearnetwork.org) has been created in response to these scientific needs-to build a transdisciplinary infrastructure to support the research that will optimise emergency care for older adults and persons living with dementia.In this paper, we describe our approach to developing the GEAR Network infrastructure, the scoping reviews to identify research and clinical gaps and its use of consensus-driven research priorities with a transdisciplinary taskforce of stakeholders that includes patients and care partners. We describe how priority topic areas are ascertained, the process of conducting scoping reviews with integrated academic librarians performing standardised searches and providing quality control on reviews, input and support from the taskforce and conducting a large-scale consensus workshop to prioritise future research topics. The GEAR Network approach provides a framework and systematic approach to develop a research agenda and support research in geriatric emergency care.This is a systematic review of previously conducted research; accordingly, it does not constitute human subjects research needing ethics review. These reviews will be prepared as manuscripts and submitted for publication to peer-reviewed journals, and the results will be presented at conferences.Open Science Framework registered DOI: 10.17605/OSF.IO/6QRYX, 10.17605/OSF.IO/AKVZ8, 10.17605/OSF.IO/EPVR5, 10.17605/OSF.IO/VXPRS.

Duke Scholars

Author Armin Nowroozpoordailami