JOURNAL ARTICLE

Improving healthcare transition for young people with cancer: factors fundamental to the quality improvement journey.

  • Published In: British Journal of Nursing, 2024, v. 33, n. 13. P. 622 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Potter, Emma; Lewis, Ciara; Tilbury, Angus; Tong, Jason; Sipanoun, Pippa 3 of 3

Abstract

Background: Young people receiving cancer treatment in the South Thames Children's, Teenagers' and Young Adults' Cancer Operational Delivery Network usually receive care across two or more NHS trusts, meaning transition into adult services can be challenging. Aim: To develop a planned, co-ordinated approach to transition across the network that meets National Institute for Health and Care Excellence guidance recommendations for transition and the cancer service specifications. Methods: A 2-year, nurse-led quality improvement (QI) project, using the principles of experience-based co-design. Outcomes: The QI project resulted in the development of six key principles of practice; refining and testing of a benchmarking tool; initiatives to facilitate first transition conversations; and the launch of an information hub. Conclusion: Robust QI processes, cross-network collaboration and wide stakeholder involvement required significant resource, but enabled deeper understanding of existing pathways and processes, facilitated the establishment of meaningful objectives, and enabled the testing of interventions to ensure the project outcomes met the needs of all stakeholders. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:British Journal of Nursing. 2024/07, Vol. 33, Issue 13, p622
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2024
  • ISSN:0966-0461
  • DOI:10.12968/bjon.2023.0146
  • Accession Number:178213452
  • Copyright Statement:Copyright of British Journal of Nursing is the property of Mark Allen Holdings Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.