Using advance care planning to enhance person-centred care at end of life.

  • Published In: Nursing Standard, 2025, v. 40, n. 12. P. 53 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Lawley, Elizabeth; Goodchild, Cathryn; Hine, Paula; Mitchell, Iain 3 of 3

Abstract

Why you should read this article: • To consider the challenges involved in predicting when someone is nearing the end of life • To update your knowledge of advance care planning and the different options available • To understand some of the barriers to and benefits of advance care planning. Advance care planning, which enables patients to make informed decisions about their care as they approach the end of their life, has been part of UK policy and strategy for almost two decades. Yet despite evidence of the benefits, advance care planning completion rates are low. This is due, in part, to healthcare professionals' lack of confidence in initiating such conversations and insufficient knowledge of the available advance care planning options. Moreover, although recognising when a patient is approaching end of life can provide nurses with an opportunity to initiate advance care planning discussions, predicting this life stage is inherently difficult. This article provides an overview of advance care planning and the challenges of predicting when someone is nearing end of life. The article also considers how nurses might approach advance care planning discussions with patients in a timely and sensitive manner and discusses some of the options available, such as an advance decision to refuse treatment or advance statements. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Nursing Standard. 2025/12, Vol. 40, Issue 12, p53
  • Document Type:Article
  • Subject Area:Nursing and Allied Health
  • Publication Date:2025
  • ISSN:0029-6570
  • DOI:10.7748/ns.2025.e12575
  • Accession Number:189733143
  • Copyright Statement:Copyright of Nursing Standard is the property of Royal College of Nursing of the United Kingdom (The) 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.)

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