The Dartmouth Institute for Health Policy and Clinical Practice, 1 Medical Center Drive, Lebanon, NH, 03766, USA.
Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.
Patient. 2018 Feb;11(1):97-106. doi: 10.1007/s40271-017-0268-2.
Seriously ill people at high risk of death face difficult decisions, especially concerning the extent of medical intervention. Given the inherent difficulty and complexity of these decisions, the care they receive often does not align with their preferences. Patient decision aids that educate individuals about options and help them construct preferences about life-sustaining care may reduce the mismatch between the care people say they want and the care they receive. The quantity and quality of patient decision aids for those at high risk of death, however, are unknown.
This protocol describes an approach for conducting an environmental scan of life-sustaining treatment patient decision aids for seriously ill patients, identified online and through informant analysis. We intend for the outcome to be an inventory of all life-sustaining treatment patient decision aids for seriously ill patients currently available (either publicly or proprietarily) along with information about their content, quality, and known use.
We will identify patient decision aids in a three-step approach (1) mining previously published systematic reviews; (2) systematically searching online and in two popular app stores; and (3) undertaking a key informant survey. We will screen and assess the quality of each patient decision aid identified using the latest published draft of the U.S. National Quality Forum National Standards for the Certification of Patient Decision Aids. Additionally, we will evaluate readability via readable.io and content via inductive content analysis. We will also use natural language processing to assess the content of the decision aids.
Researchers increasingly recognize the environmental scan as an optimal method for studying real-world interventions, such as patient decision aids. This study will advance our understanding of the availability, quality, and use of decision aids for life-sustaining interventions targeted at seriously ill patients. We also aim to provide patients, their families, and friends, along with their clinicians, a broad set of resources for making life-sustaining treatment decisions. Although we intend to capture all patient decision aids for the seriously ill in our review, we anticipate the possibility that we may miss some decision aids. In addition to publishing our findings in an academic journal, we plan to post our inventory online in an easy-to-read format for public and clinical consumption.
生命垂危的重病患者面临艰难的决策，尤其是在医疗干预程度方面。鉴于这些决策固有的难度和复杂性，他们所接受的护理往往与其偏好不符。教育个人了解各种选择并帮助他们构建对维持生命的护理偏好的患者决策辅助工具，可能会减少人们所说的想要的护理与实际接受的护理之间的不匹配。然而，对于生命垂危的患者，患者决策辅助工具的数量和质量尚不清楚。
本方案描述了一种针对生命垂危的重病患者的维持生命治疗患者决策辅助工具进行环境扫描的方法，通过在线和信息提供者分析来识别。我们的目标是制作一份当前所有维持生命的治疗患者决策辅助工具的清单，包括重病患者的信息，以及关于其内容、质量和已知用途的信息。
我们将通过三步骤的方法来识别患者决策辅助工具：（1）挖掘先前发表的系统评价；（2）在线和两个流行的应用商店中进行系统搜索；（3）进行关键信息提供者调查。我们将使用美国国家质量论坛国家患者决策辅助工具认证标准的最新草案，对每个识别出的患者决策辅助工具进行筛选和评估其质量。此外，我们将通过 readable.io 评估可读性，通过归纳内容分析评估内容。我们还将使用自然语言处理来评估决策辅助工具的内容。
研究人员越来越认识到，环境扫描是研究现实世界干预措施（如患者决策辅助工具）的最佳方法。这项研究将增进我们对针对重病患者的维持生命干预措施的决策辅助工具的可用性、质量和使用情况的了解。我们还旨在为患者、他们的家人和朋友以及他们的临床医生提供一套广泛的资源，以做出维持生命的治疗决策。尽管我们打算在综述中收录所有针对重病患者的决策辅助工具，但我们预计可能会遗漏一些决策辅助工具。除了在学术期刊上发表我们的研究结果外，我们还计划以易于阅读的格式在线发布我们的清单，供公众和临床使用。
