Non-malignant Pain in Nursing Home Residents

项目摘要/摘要 此应用程序响应PA-16-188“疼痛中的机制、模型、测量和管理” 研究(R01)“。疗养院的疼痛管理是次优的。62%的疗养院 居民们感受到了痛苦。尽管癌症是疗养院疼痛的重要原因，但关节炎和 肌肉骨骼问题影响了超过四分之三的65岁以上的人。尽管有很高的 疗养院居民经历疼痛状况的患病率、养老院中的非恶性疼痛 还没有得到彻底的研究。疼痛很少是一种孤立的症状，而且经常与 在常见的聚集性中有/伴随有其他症状。我们确实知道，在护理中，疼痛被低估了。 当记录在案时，它的治疗往往是次优的。对于养老院的居民来说，这是一种“老年病” 存在“药典”--即，尽管人口不断增长，用药负担沉重， 老年疗养院居民被系统地排除在临床试验之外。造成的结果是缺乏 信息需要严格的非实验研究设计来量化药物的风险和好处 使用。本研究从两个方面对文献进行了扩展。首先，它寻求改善对疼痛的衡量。第二, 有了改进的测量方法，它寻求扩大关于如何最好地使用 药理学方法。此应用程序建立在我们团队之前和正在进行的工作的基础上。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) 使用潜变量建模方法。本申请中提出的工作将进一步提炼这些 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 可用的数据(最低数据集3.0(MDS)和联邦医疗保险资格和索赔数据(A&D部分))。这个 具体目标是：1)验证当前数据中的疼痛症状簇；2)描述疼痛症状的相关性 分类；3)按疼痛症状分类描述止痛药的使用；以及4)量化药物的使用程度 与疼痛改善和不良事件(如跌倒/骨折， 住院)。先进的统计技术，包括潜变量模型、边际结构模型、 并将使用分位数回归。未经处理、可能未得到充分处理和不适当处理的非 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，是 在疗养院学习。这是一个新的勘探领域，将提供所需的 信息构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.