With a successful Hospital at Night pilot behind it and Computers on Wheels in clinical areas, a Liverpool trust significantly reduced junior doctors’ hours
The Royal Liverpool and Broadgreen University Hospitals trust is based over two sites. The Royal site is acute and has 900 beds; the Broadgreen site is non acute and has 300 beds.
The trust had already acted as a successful pilot for Hospital at Night in 2004 and used this as a basis for achieving European working time directive 2009 compliance.
“The trust achieved a reduction of up to 16 per cent in the working hours”
The trust held a consultation period to help plan, prioritise and deliver a better system for doctors and better service for patients. It also helped improve relationships with staff of all grades and increased sign-up to the project.
Focus groups were held for all junior doctors, while ward staff and out of hours teams (nurse practitioners) were also consulted. Common themes were identified and fed into working groups that had been established as subgroups. This gave each working group a clear implementation plan to ensure work progressed at an appropriate rate.
Regular written and verbal reports were made to the executive team, project group, local negotiating committee and the patients’ council to ensure everyone was informed. Update sessions were held with junior doctors, ward staff and nurse practitioners, and articles were published in the trust magazine and newsletter.
The trust was successful in achieving a reduction of up to 16 per cent in the average working week of junior doctors. In order to produce rotas that met service needs and maintain standards of patient care, rotas needed to consider alternative working patterns and incorporate guidance issued by the royal colleges.
The pilot, together with the trust’s workforce model, has encouraged the development of the assistant and nurse practitioner roles.
A formal handover policy was developed for the afternoon and evening.
The Computers on Wheels initiative across 55 clinical areas is expected to cut the time doctors spend on tasks such as data input and retrieval, improving teaching and care through fast bedside data access.