Measuring Chronic Pain Impact

摘要/摘要 在临床背景下收集个人患者报告结果(PRO)数据的情况正在增加，并且一直在 显示可加强临床医生与患者之间的沟通。它可以用来确定患者的优先顺序和偏好， 设定治疗预期，支持共同决策。在总体层面上，专业人士可以用来 检查治疗的临床和成本效益，测量和监测质量，并优化规划 和医疗保健服务的提供。患者报告结局测量信息系统 (PROMIS®)测量因其心理测量学的健壮性而在临床环境中具有吸引力， 直截了当的解释，标准化的指标被规范到一般人群中。然而， 现有的PROMIS轮廓测量对于常规临床使用来说是繁重的，导致许多人选择较短的测量 在PROMIS图书馆内外采取更有限的措施。我们的首要目标是计划和实施 复杂的统计分析，包括项目反应理论分析，通过确定 未来研究人员可以用来检查其影响的简短且心理健康的测量方法 对患者最重要的整体健康结果的干预。具体来说，我们建议 开发一种简短的Promis Profile测量(SPP)，它可以：1)有效地为八种健康状况打分 领域(即身体功能、疼痛干扰、疲劳、睡眠障碍、抑郁、焦虑、社会角色 参与、认知功能)；2)生成身心健康总结分数；以及3)计算 提示偏好(PROPr)评分。我们的方法包括来自投资利益相关者的持续投入，这些利益相关者将 与研究密切合作，确保所产生的SPP得到广泛认可。通过我们在家长基金上的工作， 我们的研究团队已经确定了可能包含在SPP中的50个独特的PROMIS项目，并可以访问 包括对所有候选项目的响应的数据源。我们将利用现有数据进行分析 并通过完成以下具体目标得到最优的SPP：1.构造多个候选者 通过识别和组合8个PROMIS域中的每一个的最佳执行两项集来进行SPPS 正在考虑列入《战略文件》；2.根据以下情况减少和完善候选措施的数量： A)通过因素分析得出的一般身心健康综合得分的表现；以及b) 评估候选配置文件测量的估计PROPr分数；以及3.选择最终的SPP规格 基于目标2的结果与利益相关者小组合作。在完成这三个目标时，我们 将有一个强大的SPP，可以包含在PROMIS库中，并可供一般使用。这个 这种措施的可获得性有可能显著影响例行程序的频率和有用性 PRO数据收集在临床护理中，还将使行为健康研究人员和临床试验人员能够 在他们的调查中包括一个强大的PROMIS量表，而不会造成过大的负担或精度损失。

Summary/Abstract Collection of individual patient-reported outcome (PRO) data in clinical contexts is increasing and has been shown to enhance clinician-patient communication. It can be used to identify patient priorities and preferences, set treatment expectations, and support shared decision-making. At an aggregate level, PROs can be used to examine the clinical- and cost-effectiveness of treatments, measure and monitor quality, and optimize planning and delivery of healthcare services. The Patient-Reported Outcome Measurement Information System (PROMIS®) measures are attractive for use in clinical settings because of their psychometric soundness, straightforward interpretation, and standardized metrics normed to the general population. However, the existing PROMIS Profile measures are burdensome for routine clinical use, leading many to opt for shorter more limited measures within or outside the PROMIS library. Our overarching goal is to plan and conduct complex statistical analyses, including item response theory analyses to fill this gap by identifying a brief and psychometrically sound measure that future researcher can use to examine impacts of their interventions on whole person health outcomes that matter most to patients. Specifically, we propose to develop a Short PROMIS Profile measure (SPP) that can: 1) efficiently produce scores for eight health domains (i.e., physical function, pain interference, fatigue, sleep disturbance, depression, anxiety, social role participation, cognitive function); 2) generate physical and mental health summary scores; and 3) calculate the PROMIS preference (PROPr) score. Our approach includes ongoing input from invested stakeholders who will work closely with the study to ensure broad buy-in for the resulting SPP. Through our work on the parent grant, our study team has identified 50 unique PROMIS items for possible inclusion in the SPP and has access to a data source that includes responses to all candidate items. We will conduct analyses using the existing data and arrive at an optimal SPP through completion of the following specific aims: 1. Construct several candidate SPPs by identifying and combining optimally performing two-item sets for each of the 8 PROMIS domains being considered for inclusion in the SPP; 2. Reduce and refine the number of candidate measures based on: a) performance of general physical and mental health summary scores derived from factor analysis; and b) evaluation of candidate profile measures’ estimated PROPr scores; and 3. Select the final SPP specification in collaboration with the stakeholder group based on results from Aim 2. At the completion of these three aims we will have a robust SPP that can be included in the PROMIS library and made available for general use. The availability of this measure has the potential to significantly impact the frequency and usefulness of routine PRO data collection in clinical care and will also enable behavioral health researchers and clinical trialists to include a robust PROMIS scale in their surveys without excessive burden or loss in precision.