Non-malignant Pain in Nursing Home Residents

项目总结/摘要 此应用程序响应PA-16-188“机制，模型，测量，和疼痛管理 研究（R 01）"。养老院的疼痛管理是次优的。62%的养老院 居民会感到疼痛。虽然癌症是养老院疼痛的重要原因，但关节炎和 超过四分之三的65岁以上的人患有肌肉骨骼疾病。尽管高 养老院居民经历的疼痛状况的患病率，养老院中的非恶性疼痛 还没有被彻底研究过。疼痛很少是一个孤立的症状，往往与 有/伴有其他常见症状。我们知道疼痛在护理中被低估了 家庭和记录时，其治疗往往是次优。对于养老院的居民来说， 存在“药典”-即，尽管人口不断增长，药物使用负担沉重， 老年疗养院居民被系统地排除在临床试验之外。由此造成的缺乏 信息需要严格的非实验性研究设计来量化药物的风险和益处 使用.这项研究从两个方面扩展了文献。首先，它旨在改善疼痛的测量。第二、 随着测量方法的改进，它试图扩大如何最好地缓解疼痛的知识， 药理学方法。该应用程序建立在我们团队以前和正在进行的工作基础上。我们 目前正在研究非恶性疼痛症状群的特征（横截面和纵向） 使用潜在变量建模方法。本申请中提出的工作将进一步完善这些 使用同期数据集的模型。我们将更新我们的内部数据集，以包括最新的 最小数据集3.0（MDS）和医疗保险资格和索赔数据（A部分和D部分）。的 具体目标是：1）在当前数据中识别疼痛症状群; 2）描述疼痛症状的相关性 集群; 3）描述疼痛症状集群的镇痛药使用;和4）量化药物治疗的程度 与诸如疼痛和不良事件（例如福尔斯/骨折， 住院）。先进的统计技术，包括潜在变量模型，边际结构模型， 将使用分位数回归。未经治疗、可能治疗不足和治疗不当的 恶性疼痛在疗养院环境中仍然很常见。非恶性疼痛，以及如何最好地缓解它， 在疗养院里做替补这是一个新的探索领域，将提供所需的 信息形成有效的临床策略的基础，以改善非恶性疼痛管理， 养老院

PROJECT SUMMARY/ABSTRACT This application responds to PA-16-188 "Mechanisms, Models, Measurement, & Management in Pain Research (R01)". Pain management in nursing homes is sub-optimal. Sixty-two percent of nursing home residents experience pain. Although cancer is an important reason for pain in nursing homes, arthritis and musculoskeletal problems affect over three quarters of persons over 65 years of age. Despite the high prevalence of painful conditions experienced by nursing home residents, non-malignant pain in nursing homes has not been thoroughly studied. Pain is seldom an isolated symptom and is often associated with/accompanied by other symptoms in common clusters. We do know that pain is under-reported in nursing homes and when documented, its treatment is often suboptimal. For nursing home residents, a “geriatric pharmacoparadox” exists – i.e., despite the growing population and the high burden of medication use, geriatric nursing home residents are systematically excluded from clinical trials. The resulting dearth of information requires rigorous non-experimental study designs to quantify the risks and benefits of medication use. This study extends the literature in two ways. First, it seeks to improve measurement of pain. Second, with improved measurement in hand, it seeks to expand knowledge on how best to relieve pain using pharmacologic approaches. This application builds on previous and ongoing work conducted by our team. We are currently working on characterizing non-malignant pain symptom clusters (cross-sectional and longitudinal) using latent variable modeling approaches. The work proposed in this application will further refine these models using a contemporaneous dataset. We will update our in-house data set to include the most recent data available (the Minimum Data Set 3.0 (MDS) and Medicare eligibility and claims data (Part A & D)). The specific aims are to: 1) Validate pain symptom clusters in current data; 2) Describe correlates of pain symptom clusters; 3) Describe analgesic use by pain symptom clusters; and 4) Quantify the extent to which medications are associated with outcomes such as improvements in pain and adverse events (e.g. falls/fractures, hospitalizations). Advanced statistical techniques including latent variable models, marginal structural models, and quantile regression will be used. Untreated, potentially undertreated and inappropriately treated non- malignant pain remains common in the nursing home setting. Non-malignant pain, and how best to relieve it, is understudied in the nursing home setting. This is a novel area of exploration that will provide needed information to form the basis of effective clinical strategies to improve non-malignant pain management in nursing homes.