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THE AAOS ASSESSMENT TEAM STUDY OF THA - PLANNING GRANT

THE AAOS ASSESSMENT TEAM STUDY OF THA - PLANNING GRANT
AAOS 评估小组对 THA 的研究 - 规划拨款
批准号:
3098952
负责人:
FRED V FEATHERSTONE
金额:
$5.0万
依托单位国家:
美国
项目类别:
财政年份:
1989
资助国家:
美国
项目状态:
已结题
起止时间:
1989-09-07 至 1990-05-31

项目摘要

项目成果

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中文摘要
翻译
这项提议是对校外评估小组的RFP的回应 来自美国整形外科学会,该学会 代表了美国90%以上的整形外科医生。 全髋关节置换术(THA)的多学科团队评估 建议。对临屋区的小区域变化进行分析将使用 Medicare A和B文件,以确定利用率高和低的区域。 这些领域将通过招募整形外科医生进行详细研究, 风湿科医生和他们的患者髋部疼痛明显 软骨丢失。将开发一个决策分析马尔可夫模型 人工全髋关节置换术治疗终末期髋关节疾病的对比研究 另类治疗。公用事业将从量化的 综合文献,如果没有文献,则以协商一致的方式 专家们的意见。患者实用程序和首选项将从 选择人工全髋关节置换术和人工全髋关节置换术患者的研究 接受保守的管理。 研究地区的全髋关节置换术的结果将被反馈 为医生和患者努力减少总使用量 导致不良后果或不当的髋关节置换术 利用率。
英文摘要
This proposal is in response to an RFP for Extramural Assessment Teams and comes from the American Academy of Orthopaedic Surgeons which represents over 90% of orthopedic surgeons in the U.S.A. A multidisciplinary team assessment of total hip arthroplasty is (THA) proposed. An analysis of small area variation in THA will be done using Medicare A and B files to identify areas of high and low utilization. These areas will be studied in detail by recruiting orthopedic surgeons, rheumatologists, and their patients who have hip pain with significant cartilage loss. A decision analytical Markov model will be developed on treating endstage hip disease by total hip arthroplasty versus alternative treatments. Utilities will be derived from a quantitative synthesis of the literature and, when it is not available, by a consensus of experts. Patient utilities and preferences will be obtained from the study of the patients who have elected total hip arthroplasty or who are receiving conservative management. The results of total hip arthroplasty in the study areas will be fed back to physicians and patients in an effort to reduce utilization of total hip arthroplasty which results in adverse outcomes or inappropriate utilization.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
DOI: --
发表时间: 1991
期刊: The Journal of bone and joint surgery. American volume
影响因子: --
作者: [Liang,MH, Katz,JN, Phillips,C, Sledge,C, Cats-Baril,W]
通讯作者: Cats-Baril,W
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis