A Computer-Based Decision Aid for Advance Care Planning

描述（由申请人提供）：预先护理计划是“患者、其医疗保健提供者、其家属和其他重要人员之间就患者无法做出决定时认为适当的护理类型进行沟通的过程。“它通常涉及使用预先指示表格，概述具体指示，和/或指定代理决策者。尽管对预先指示的态度普遍积极，但很少有人真正完成预先指示，更少的人了解有意义的预先护理计划所需的关键要素，甚至有据可查的预先指示也经常被忽视。由于缺乏规划导致不必要的医疗干预，失去独立性，不必要的痛苦，以及对患者，他们的家庭和社会的经济负担，迫切需要改善提前护理规划的过程。 通过本研究，我们提出了开发，完善和评估基于计算机的决策辅助提前护理计划，通过三个具体目标：（1）产生一个交互式的计算机程序/决策辅助，以帮助人们的过程中提前护理计划。 (2)使用多属性效用理论（MAUT）帮助用户a）识别其对提前护理计划要素的真实偏好，以及B）准确表达这些偏好。 (3)评估计算机程序的易用性、可接受性及其对知识、态度和心理状态的影响;评估MAUT模型在澄清用户价值观和目标方面的预测准确性。 如果成功的话，这种决策辅助将有助于保护病人的自主权，保持他们的独立性，并促进合理使用卫生保健资源。

DESCRIPTION (provided by applicant): Advance care planning is a "process of communication among patients, their health-care providers, their families, and important others regarding the kind of care that will be considered appropriate when the patient cannot make decisions." It typically involves the use of advance directive forms outlining specific instructions, and/or the designation of a proxy decision-maker. Despite generally positive attitudes toward advance directives, few people actually complete advance directives, fewer yet understand key elements necessary for meaningful advance care planning, and even well-documented advance directives are routinely disregarded. Since the absence of planning leads to unwanted medical interventions, loss of independence, needless suffering, and financial burdens to patients, their families, and society, there is an urgent need to improve the process of advance care planning. With this study we propose to develop, refine, and evaluate a computer-based decision aid for advance care planning, through three Specific Aims: (1) To produce an interactive computer program/decision aid for helping people with the process of advance care planning. (2) To use Multi-Attribute Utility Theory (MAUT) to help users a) identify their true preferences for elements of advance care planning, and b) articulate them accurately. (3) To evaluate the computer program for ease of use, acceptability, and its effects on knowledge, attitudes, and psychological states; to assess the predictive accuracy of the MAUT model in clarifying users' values and goals. If successful, this decision aid will help to protect patients' autonomy, preserve their independence, and promote the sensible use of health-care resources.