医学
预先护理计划
心理干预
干预(咨询)
文档
人口
指令
价值(数学)
临终关怀
限制
风险分析(工程)
重症监护医学
医疗急救
护理部
缓和医疗
机械工程
环境卫生
机器学习
计算机科学
工程类
程序设计语言
作者
J. Andrew Billings,Rachelle Bernacki
标识
DOI:10.1001/jamainternmed.2013.14384
摘要
Strategically selecting patients for discussions and documentation about limiting life-sustaining treatments—choosing the right time along the end-of-life trajectory for such an intervention and identifying patients at high risk of facing end-of-life decisions—can have a profound impact on the value of advance care planning (ACP) efforts. Timing is important because the completion of an advance directive (AD) too far from or too close to the time of death can lead to end-of-life decisions that do not optimally reflect the patient’s values, goals, and preferences: a poorly chosen target patient population that is unlikely to need an AD in the near future may lead to patients making unrealistic, hypothetical choices, while assessing preferences in the emergency department or hospital in the face of a calamity is notoriously inadequate. Because much of the currently studied ACP efforts have led to a disappointingly small proportion of patients eventually benefitting from an AD, careful targeting of the intervention should also improve the efficacy of such projects. A key to optimal timing and strategic selection of target patients for an ACP program is prognostication, and we briefly highlight prognostication tools and studies that may point us toward high-value AD interventions.
科研通智能强力驱动
Strongly Powered by AbleSci AI