Measuring Chronic Pain Impact

测量慢性疼痛的影响

• 批准号: 10559712
• 负责人: RONALD Dale HAYS
• 金额: $ 54.93万
• 依托单位: RAND CORPORATION
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10559712
• 关键词: Address; Advisory Committees; Agreement; Area; Back Pain; Case Mixes; Chronic low back pain; Chronic neck pain; Classification; Complementary Health; Data; Data Collection; Data Set; Effectiveness; Equilibrium; Exhibits; Future; Goals; Guidelines; Individual; Information Systems; Integrative Medicine; Intervention; Investments; Link; Measurement; Measures; Mechanics; Methods; Morbidity - disease rate; Neck; Nonpharmacologic Therapy; Outcome; Outcome Measure; Outcome Study; Pain; Patient Outcomes Assessments; Patients; Pharmacologic Substance; Population Research; Probability; Productivity; Property; Questionnaires; Recommendation; Research; Research Personnel; Sampling; Sampling Studies; Scheme; Source; Stratification; Subgroup; Time; Translating; United States National Institutes of Health; Validation; Work; chronic back pain; chronic pain; chronic pain management; chronic pain patient; cost; crowdsourcing; disability; effectiveness study; efficacy evaluation; health care service utilization; health related quality of life; improved; indexing; pain patient; patient subsets; relative effectiveness; working group

Project Summary/Abstract Many complementary and integrative health (CIH) approaches have been shown to be effective for chronic pain and included in guidelines. This evidence of effectiveness is built on hundreds of studies representing millions of research dollars, and the ability to analyze and better compare results across these studies is essential to obtain the full value of this investment. However, useful across-study comparisons which would allow better understanding and targeting of these interventions are hampered by at least two challenges: the lack of common outcome measures and the inability to meaningfully stratify or classify patients. To address the first challenge, in Aim 1 this study will develop and evaluate crosswalks or links between components of the 29-item Patient-Reported Outcomes Measurement Information System (PROMIS®) short form (PROMIS-29) and common legacy measures used for chronic pain. In particular, we will create crosswalks/links for the two most commonly used measures for CLBP, including the Roland-Morris Disability Questionnaire (RMDQ) and the Oswestry Disability Index (ODI). In addition, depending on data availability and input from our Advisory Council we will create at least two other crosswalks/links between the PROMIS-29 and other legacy measures for CLBP (e.g., the Back Pain Functional Scale) or legacy measures for other types of chronic pain (e.g., the Neck Disability Index for chronic neck pain). To address the second challenge, in Aim 2 we will evaluate and refine the chronic pain impact stratification scheme proposed by the NIH Research Task Force on chronic low back pain. The proposed scheme uses the Impact Stratification Score (ISS) which is calculated using 9 items from the PROMIS-29. We will first evaluate the ISS and its properties to assess whether they are stable across different samples and determine whether they can be improved. After we have finalized the components and calculation of the ISS, we will examine its effect on the impacts of chronic pain (e.g., health-related quality of life, healthcare utilization, worker productivity) to identify meaningful cut-points to use to stratify chronic pain patients into subgroups who exhibit different levels of chronic pain impact. Three types of data will be used in the analyses to address Aims 1 and 2: data from three large in-house existing datasets, data collected from a national convenience sample using Amazon’s Mechanical Turk (MTurk) crowdsourcing platform, and data from the probability-based nationally representative KnowledgePanel. Aim 3 will evaluate crowdsourcing as a reliable, efficient method to collect data on individuals with chronic pain through the comparison of its results to what was found using KnowledgePanel.

项目摘要/摘要 许多完善和综合健康（CIH）方法已被证明对慢性有效 疼痛并包括在准则中。这种有效性的证据建立在数百项代表的研究上 数百万的研究美元以及在这些研究中分析和更好地比较结果的能力是 获得这项投资的全部价值至关重要。但是，有用的跨研究比较 至少有两个挑战，可以更好地理解和靶向这些干预措施： 缺乏共同的结果指标，无法有意义地对患者进行分层或分类。 为了应对第一个挑战，在目标1中，本研究将开发和评估人行横道或之间的联系 29个项目的患者报告结果测量信息系统（Promis®）的组件短 形式（Promis-29）和用于慢性疼痛的共同遗产措施。特别是，我们将创建 两种最常用的CLBP措施的人行横道/链接，包括Roland-Morris残疾 问卷（RMDQ）和OSWESTRY残疾指数（ODI）。此外，取决于数据可用性和 我们的咨询委员会的意见我们将在Promis-29和 CLBP的其他遗产措施（例如，背痛功能量表）或其他类型的遗产措施 慢性疼痛（例如，慢性颈部疼痛的颈部残疾指数）。 为了应对第二个挑战，在AIM 2中，我们将评估和完善慢性疼痛冲击分层 NIH研究工作组提出的有关慢性腰痛的计划。提出的方案使用 影响分层评分（ISS），该评分是使用Promis-29中的9个项目计算得出的。我们将首先评估 ISS及其特性评估它们是否在不同样本中稳定，并确定是否 它们可以改进。最终确定了ISS的组件和计算后，我们将检查其 对慢性疼痛影响的影响（例如，与健康相关的生活质量，医疗保健利用，工人 生产力），以识别有意义的切点，用于将慢性疼痛患者分类为暴露的亚组 不同水平的慢性疼痛影响。 分析中将使用三种类型的数据来解决目标1和2：来自三个大型内部的数据 现有数据集，使用亚马逊的机械土耳其人从国家便利样本中收集的数据 （MTURK）众包平台以及来自基于概率的国家代表的数据 知识范围。 AIM 3将评估众包作为一种可靠，有效的方法来收集数据 通过将其结果与使用知识型的结果进行比较，患有慢性疼痛的个体。