Structure, Process, and Outcomes in Cancer Surgery

描述(由申请人提供)：癌症手术与较高的手术死亡率有关，特别是在手术量较少的医院。由于缺乏对观察到的体积-结果关系的机制的了解，这些中心提高质量的努力受到阻碍。这项研究将分三个步骤探讨这个问题： 1.确定大容量和低容量医院之间的区别。使用1994-2001年医疗保险数据库中100%的全国样本(n约800,000)，我们将比较高容量和低容量医院的结构和流程变量与8种程序中的每一种。特定于癌症护理的结构性变量将包括放射和化疗服务的现场可获得性、医院参与癌症试验以及外科医生在癌症手术方面的“专门化”。然后，我们将评估与患者选择和其他围手术期护理过程相关的变量。 2.确定哪些因素有助于解释观察到的体积-结果关系。然后，我们将用这8个程序检查结构、过程和结果(手术死亡率)之间的关系。使用嵌套模型，我们将评估观察到的体积-结果关系如何随着各种结构和护理过程变量添加到模型中而发生变化。我们将使用SEER-Medicare关联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。为了更好地根据医疗记录或现场访问来规划对结构、过程和结果的研究，我们必须首先了解不同医院手术死亡率的差异是否可归因于特定的死亡原因。我们将在新英格兰北部的两家医院进行一项初步研究，开发并测试一种基于图表的死因评估工具。

DESCRIPTION (provided by applicant): 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 approximately 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.