Avoiding Admissions To Emergency Departments From Long Term Care Facilities Using Nurse Led Decision Making Algorithm
The global population of those aged 80 and above is expected to triple by 2050 leading to an increased demand for care in a Residential Care Facility (RCF).This population are at increased risk of developing multiple conditions, frailty, and cognitive impairment.This increase in acuity leads to transfers from the residential setting to the emergency department.Aim: The aim of this quality initiative was to trial the NaRT tool in conjunction with the Stop and Watch tool to aid staff with clinical decision making in the management of a deteriorating patient, thus ensuring care pathway appropriateness, reduction in inappropriate presentations to the emergency department and enhanced person-centred care.Methods: Mixed methods were employed.An evidence review was undertaken to identify studies relating to the use of a nurse led decision making algorithm for long-term care facilities.Focus group interviews were also undertaken.Following analysis an outreach model was introduced in two nursing homes within an integrated care framework, thus allowing for enhanced clinical communication between the RCF and the acute hospitals.Data collection: A suite of metrics was collated monthly to track trends.RCF sample size: Residential Care Facility (RCF) A is a 102-bed residential care facility and RCF B has 89 beds, both based within the Hospitals Integrated Care Framework.Interventions: The Stop and Watch tool was first used to allow for early intervention and prevention of further resident deterioration.The Nursing and Residential Triage tool (NaRT), designed for use within the residential setting, is based on the Manchester triage system and contains two presentational charts: injury and illness.Staff were asked to complete the NaRT tool pre decision to transfer residents to the
Publication Details
- Journal
- International Journal of Nursing and Health Care Research
- Published
- 2024-08-15
- DOI
- https://doi.org/10.29011/26889501.101561
- Primary Topic
- Healthcare Operations and Scheduling Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00