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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

基本信息

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
项目类别：
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

项目摘要

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：严重的骨质疏松性骨折在长期入住疗养院的居民中很常见、病态且昂贵。尽管这个问题很重要，但没有筛查疗养院居民骨质疏松症的指南，也不清楚哪些骨质疏松药物可以预防长期居住的居民骨折。为了解决这些知识差距，我们提出以下具体目标：1）使用跌倒和骨折的临床风险因素开发和验证预测工具，该工具将估计长期入住疗养院居民的髋部骨折的 2 年绝对风险和严重骨质疏松性骨折（髋部、肱骨和腕部组合）的一年绝对风险； 2) 确定骨质疏松药物（即双磷酸盐、降钙素、雌激素、雷洛昔芬和特立帕肽）是否可以降低长期入住疗养院居民的髋部和主要骨质疏松性骨折的发生率； 3) 确定临床风险阈值，在该阈值下，骨质疏松药物可将长期住院居民的髋部和主要骨质疏松性骨折的发生率降低 20%。该项目将利用现有数据库，该数据库先前已将 Medicare A 部分和 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）和设施级别特征（OSCAR）相关联。使用该数据库，我们将对 2006 年至 2011 年期间参加 Medicare 按服务收费计划且入住时间为 90 天的所有美国疗养院居民（每年超过 700,000 名居民）进行前瞻性分析。对于具体目标 1，预测工具将完全根据所有美国长期居民可获得的临床信息开发，例如认知和功能状态、非骨质疏松药物的使用以及近期跌倒史。预测工具将解释疗养院居民的高死亡率。对于具体目标 2a，我们将通过比较骨质疏松药物“新使用者”的骨折发生率与“非使用者”的骨折发生率（并与倾向评分相匹配）来确定骨质疏松药物是否可以降低长期居住居民的髋部和主要骨质疏松性骨折的发生率。对于具体目标 2b，我们将根据骨折预测工具估计的基线骨折风险，通过检查骨质疏松症药物的疗效来确定药物干预的阈值。研究团队在药物流行病学、老年病学、医疗保险索赔数据分析以及完成该项目所需的最低数据集特征方面拥有丰富的经验。我们的研究结果非常重要，因为它们将为疗养院环境中骨质疏松症的筛查和治疗提供第一个指导。我们预计我们的研究结果将很容易为提供者实施，因为骨折预测工具将由所有美国疗养院居民已经可以获得的临床信息组成。从这项研究中获得的知识最终可能会降低疗养院环境中严重骨质疏松性骨折的发生率，从而降低发病率和医疗费用。