Alternative pre-hospital pathways for mental health patients
A collaboration between NIHR CLAHRC Yorkshire and Humber Avoidable Attendances and Admissions Theme and Yorkshire Ambulance Service is exploring the care provided for 999 patients with mental health problems. This includes a pilot study evaluating mental health nurse triage within the Emergency Operations Centre where calls are handled. This new service provides front-line call-handlers, clinicians and patients with access to specialist mental health support. The aims of the evaluation are to assess the impact of the service on outcomes for patients and on the working practices of Ambulance Service staff. It will also examine the costs and benefits associated with the service and any lessons learned from its implementation. The study is collecting routine data on calls to the new service as well as qualitative data from staff and patients. Early indications from routine data suggest a reduction in ambulance transport for patients with mental health problems and improved response time performance as a result for high priority calls.
Analysing emergency and urgent care system demand: a data linkage study of pre-hospital and emergency hospital data
A better understanding of the causes of increasing service pressures in the emergency and urgent care (EUC) system is fundamental to the delivery of more appropriate and better quality care for patients. Currently there is a lack of detailed information on how patients use the EUC system, from the point of access to point of discharge. The NIHR CLAHRC Yorkshire and Humber Avoidable Attendances and Admissions Theme is undertaking a pilot of the region’s first EUC routine dataset linking pre-hospital and hospital data. All 14 acute hospitals NHS trusts in Yorkshire and Humber have agreed to participate. Data has been collected so far from nine acute trusts, collating data for over 10 million patient attendances to hospital. Data from the Yorkshire Ambulance Service for NHS 111 and 999 calls will be linked with these hospital episodes to provide a complete picture of the patient journey from time of call through to discharge. Analysis of this dataset will provide crucial intelligence on how best to target interventions to provide better quality and appropriate care for patients at different parts of the EUC pathway.