A Clinical Prediction Tool to Guide Treatment of Osteoporosis in the Nursing Home

指导疗养院骨质疏松症治疗的临床预测工具

• 批准号: 8930041
• 负责人: Sarah Dyer Berry
• 金额: $ 45.19万
• 依托单位: HEBREW REHABILITATION CENTER FOR AGED
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-30 至 2018-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8930041
• 关键词: Accounting; Address; Algorithms; Calcitonin; Characteristics; Clinical; Clinical assessments; Cognitive; Communities; Consensus; Data; Data Set; Databases; Diagnostic Imaging; Drug Exposure; Dual-Energy X-Ray Absorptiometry; Elderly; Enrollment; Estrogens; Fee-for-Service Plans; Fracture; Geriatrics; Guidelines; Health; Health Care Costs; Health Expenditures; Hip Fractures; Hip region structure; Hour; Humeral Fractures; Incidence; Institution; Institutionalized Persons; Intervention; Knowledge; Length of Stay; Life Expectancy; Link; Medicare; Medicare Part A; Medicare claim; Morbidity - disease rate; Neurologic; Nursing Homes; Osteoporosis; Persons; Pharmaceutical Preparations; Pharmacoepidemiology; Pharmacy facility; Polypharmacy; Provider; Quality of Care; Raloxifene; Recording of previous events; Research; Resources; Risk; Risk Assessment; Risk Factors; Risk-Taking; Sampling; Specificity; Teriparatide; Time; Variant; Work; Wrist; aged; bisphosphonate; clinical risk; cost; day length; experience; falls; functional decline; functional status; humerus; improved; mortality; nursing home length of stay; osteoporosis with pathological fracture; prevent; prospective; screening; tool

DESCRIPTION: Major osteoporotic fractures are common, morbid, and costly among long-stay nursing home residents. Despite the importance of this problem, there are no guidelines to screen nursing home residents for osteoporosis, and it is unclear which osteoporosis medications prevent fractures in long-stay residents. To address these gaps of knowledge we propose the following specific aims: 1) develop and validate a prediction tool using clinical risk factors for falls and fracture that will estimate the 2 year absolute risk of hip fracture and the year absolute risk of major osteoporotic fracture (hip, humerus, and wrist combined) in long-stay nursing home residents; 2) determine whether osteoporosis medications (i.e., bisphosphonates, calcitonin, estrogen, raloxifene, and teriparatide) reduce the incidence of hip and major osteoporotic fracture in long-stay nursing home residents; and 3) determine the clinical thresholds of risk at which osteoporosis medications reduce the incidence of hip and major osteoporotic fracture by e 20% in long-stay residents. This project will leverage an existing database that has previously linked claims data from Medicare Parts A and B with pharmacy data (Medicare Part D), clinical characteristics (Minimum Data Set), and facility level characteristics (OSCAR). Using this database we will conduct a prospective analysis on all U.S. nursing home residents enrolled in a Medicare fee-for-service plan and with e 90 day length of stay between the years 2006-2011 (>700,000 residents annually). For specific aim 1, the prediction tools will be developed entirely from clinical information that is available for all U.S long-stay residents, such as cognitive and functional status, non-osteoporosis medication use, and recent history of falls. The prediction tools will account for the high mortality in nursing home residents. For specific aim 2a, we will determine whether osteoporosis medications reduce the incidence of hip and major osteoporotic fracture in long-stay residents by comparing the incidence of fracture among "new users" of an osteoporosis medication with the incidence of fracture in "non-users," matched by propensity scores. For specific aim 2b, we will determine a threshold for pharmacologic intervention by examining the efficacy of osteoporosis drugs according to baseline fracture risk, as estimated by the fracture prediction tool. The research team has experience in pharmacoepidemiology, geriatrics, and analysis of Medicare claims data and Minimum Data Set characteristics necessary to complete this project. Our findings will be highly significant as they will provide the first guidance on screening and treatment of osteoporosis in the nursing home setting. We anticipate that our findings will be easy for providers to implement because the fracture prediction tools will be comprised of clinical information that is already available for all U.S. nursing home residents. Knowledge gained from this study could ultimately result in a decreased rate of major osteoporotic fractures in the nursing home setting, with a subsequent reduction in morbidity and health care costs.

描述：长期疗养院居民中的主要骨质疏松性骨折是常见的，病态的，并且代价高昂。尽管有这个问题的重要性，但没有针对疗养院居民的骨质疏松症的指南，尚不清楚哪种骨质疏松药物可以防止长期居民的骨折。为了解决这些知识差距，我们提出了以下特定目的：1）使用临床风险因素来开发和验证预测工具，以估计长期在长期护理房屋居民的护理居民中，将估计髋部骨折的2年绝对风险，以及大骨质骨质骨折的绝对风险（hip，hip，hip，hip，hip，humerus和wristed）的绝对风险； 2）确定骨质疏松药物（即双膦酸盐，降钙素，雌激素，r氧化和teriparatide）是否会减少长期养老院居民中髋关节和主要骨质疏松性骨折的发生率； 3）确定骨质疏松症药物的临床阈值在长期居民中减少了20％的髋关节疏松症和主要骨质疏松性骨折的发生率。该项目将利用现有的数据库，该数据库以前已将Medicare A和B部分的索赔数据与药房数据（Medicare D部分），临床特征（最小数据集）和设施水平特征（OSCAR）联系起来。使用此数据库，我们将对所有参加Medicare费用服务计划的美国疗养院居民进行前瞻性分析，并在2006 - 2011年之间（每年> 70万居民）之间进行90天的住院时间。对于特定的目标1，预测工具将完全从美国所有长期居民（例如认知和功能状态，非遗传性疏松症药物的使用以及最近的跌倒史）中的临床信息中完全开发。预测工具将解释疗养院居民的高死亡率。对于特定的目标2a，我们将通过比较骨质疏松症的骨质疏松率是否会在长期居民中减少髋关节疏松性药物的发生率和骨质疏松症药物的骨折的发生率是否减少了骨质疏松药物的发生率与“非用户”中的骨折的发病率与“非用户”中的骨折的发病率。对于特定的目标2B，我们将通过根据骨折预测工具估计的基线骨折风险检查骨质疏松药物的功效来确定药物干预的阈值。研究团队在药物份学，老年医学和Medicare索赔分析数据和完成该项目所需的最低数据集特征方面具有经验。我们的发现将非常重要，因为它们将在疗养院环境中提供筛查和治疗骨质疏松症的第一个指导。我们预计我们的发现将容易为提供者实施，因为骨折预测工具将包含已用于所有美国疗养院居民的临床信息。从这项研究中获得的知识最终可能导致疗养院环境中主要骨质疏松性骨折的发生率降低，随后发病率和医疗保健成本降低。