METHODS FOR SURVIVAL ANALYSIS IN OUTCOMES RESEARCH

美国的规模和成本增长的一个主要组成部分。的医疗保健 系统是越来越积极的治疗急性和慢性 在疾病的晚期阶段。 大部分的护理是 集中在医院，大部分位于重症监护室， 其规模和对医疗保健总成本的贡献正在增加 戏剧性地。 该提案的目标是提高基本的分析能力， 与生存分析或风险相关的卫生服务研究 预测接受治疗的重症住院成人（CIHA） 医院和ICU，并将这些发现与患者的评估联系起来， 结果、成本、护理质量、利用和实践模式， 最终，改善临床决策。 长期 目的是使用临床准确的数据库来探索局限性 以及目前在生存分析和风险方面的努力的缺点 预测并提出改进建议。 这一进展将是重大的。 有利于研究人员，CIHA的质量保证。 我们将通过利用两个当代的，临床上 包含详细疾病和生理信息的精确数据库 两万五千多个CIHA 在这些数据库中，我们将确定如何 缺失值的变化，选择患者进行治疗，以及 主要预测成分的相互作用影响整体 生存分析的解释力。 我们还将探讨各种 多变量技术和随访时间长度影响测定 质量、成本效益和适当的护理。 从这些 分析我们将提出分析方法，制定指导方针， 提出可用于评估证据质量的标准 从CIHA的机构间评价以及评价 个体患者结局预测的有用性 传统的临床决策。

A major component of the growth in size and cost of the U.S.'s health care system is the increasingly aggressive treatment of acute and chronic disease at more advanced stages of illness. Most of this care is concentrated in hospitals an much is located within Intensive Care Units, whose size and contribution to total health care costs is increasing dramatically. The goal of this proposal is to advance the analytic capabilities of basic health services research as they relate to survival analysis or risk prediction for critically ill hospitalized adults (CIHAs) treated in hospitals and ICUs and to link these findings to the evaluation of patient outcome, costs, quality of care, utilization and practice patterns and, ultimately, to the improvement of clinical decision making. The long term objective is to use clinically accurate data bases to explore limitations and shortcomings of current efforts at survival analysis and risk prediction and suggest improvements. Such progress will be of substantial benefit to researchers, quality assurance for CIHAs. We will accomplish this by making use of two contemporary, clinically accurate data bases containing detailed disease and physiologic information on over 25,000 CIHAs. Within these data bases we will determine how variations in missing values, selection of the patient for treatment, and the interaction of major predictive components influence the overall explanatory power of survival analyses. We will also explore how various multivariable techniques and length of follow up influence determinations of the quality, cost-efficiency and appropriateness of care. From these analyses we will propose analytic approaches, develop guidelines, and suggest standards that could be used to evaluate the quality of evidence rom inter-institutional evaluations of CIHA as well as evaluating the usefulness of individual patient outcome predictions for use in conjunction with traditional clinical decision making.