Structure, Process, and Outcomes in Cancer Surgery

癌症手术与高手术死亡率相关，特别是在低风险的医院。 程序卷。这些中心提高质量的努力受到缺乏 了解负责观察到的体积-结果关系的机制。 本研究将分三步探讨这一问题： 1.确定高容量和低容量医院之间的区别。使用100%国家 1994-2001年医疗保险数据库中的样本（n~ 800，000），我们将比较结构和 高容量和低容量医院的过程变量，每个过程8个。结构 癌症治疗的具体变量将包括放射和化学疗法的现场可用性 服务、医院参与癌症试验和外科医生在癌症手术中的“专业化”。 然后，我们将评估与患者选择和围手术期其他过程相关的变量 在乎 2.确定哪些因素有助于解释观察到的体积-结果关系。然后我们将检查 结构、过程和结局（手术死亡率）之间的关系， 程序.使用嵌套模型，我们将评估如何观察到数量与结果的关系 随着护理变量的各种结构和过程被添加到模型中，我们将 使用SEER-Medicare链接数据库重复这些分析，以更好地控制病例组合 （肿瘤分期）。 3.为研究护理的细节做好准备。为了更好地规划结构研究， 根据医疗记录或现场访问的结果，我们必须首先了解 各医院手术死亡率的差异是否可归因于 死亡我们将开发和测试一种基于图表的仪器，用于评估飞行员的死因 在北方新英格兰的两家医院学习。

Cancer surgery is associated with high operative mortality rates, particularly at hospitals with low procedure volumes. Efforts to improve quality at these centers are hindered by lack of understanding about mechanisms responsible for observed volume-outcome relationships. This study will approach this question in 3 steps: 1. Determine what's different between high volume and low volume hospitals. Using 100% national samples from the 1994-2001 Medicare database (n~800,000), we will compare structure and process variables at high and low volume hospitals with each of 8 procedures. Structural variables specific to cancer care will include on-site availability of radiation and chemotherapy services, hospital participation in cancer trials, and surgeon "specialization" in cancer surgery. We will then assess variables related to patient selection and other processes of perioperative care. 2. Identify which factors help explain observed volume-outcome relationships. We will then examine relationships between structure, process, and outcomes (operative mortality) with the 8 procedures. Using nested models, we will assess how observed volume-outcome relationships change as various structural and process of care variables are added to the model. We will repeat these analyses using the SEER-Medicare linked database to better control for case-mix (tumor stage). 3. Prepare the groundwork for studying the fine details of care. To best plan a study of structure, process, and outcomes based on medical records or site visits, we must first understand whether variation in operative mortality rates across hospitals is attributable to specific causes of death. We will develop and test a chart-based instrument for assessing cause of death in a pilot study at two hospitals in northern New England.