HEALTH CARE ORGANIZATION AND THE USE OF CESAREAN SECTION

该研究旨在确定机构 导致医疗实践变化的特征 模式. 这一目标将通过调查 卫生保健组织的要素与 使用剖腹产。 非常适合评估 实践模式，剖宫产是最常见的手术 美国医院的手术。 相当大的争议围绕着 越来越多的使用。 过去的研究表明， 组织对剖宫产有很大的影响 利用率 然而，以前的研究未能确定 卫生保健组织变量的独立影响， 很少控制患者的混杂效应， 特色 目前的研究将通过一项 创新的方法来分析剖宫产的使用。 一 将通过以下方式建立产科实践数据库： 来自出院摘要和出生记录的信息 1985年在加州发生的47万次分娩。 这些 需要两个数据源，因为每个数据源都包含重要的 另一个不存在的变量。 尽管存在潜在的缺点， 使用现有的公共数据既有效率， 强大. 剖宫产使用的多变量模型， 将开发逻辑回归，以确定独立的 医疗机构变量的影响。 病例组合 调整将包括病人的医疗特点， 与仅使用人口特征相比， 剖宫产风险的替代指标。 这项研究将有助于研究医学上的变化， 实践 它还将澄清目前关于模式的混乱 剖宫产的使用，评估潜在的政策策略， 控制越来越多的使用剖宫产，并制定 卫生服务中使用公共数据的一般方法 research.

The proposed research seeks to determine the institutional characteristics that lead to variations in medical practice patterns. This objective will be achieved by investigating the relationship between elements of health care organization and the use of cesarean section. Ideal for evaluating variations in practice patterns, cesarean section is the most common surgical procedure in U.S. hospitals. Considerable controversy surrounds its increasing use. Past research suggests that health care organization has a strong influence on cesarean section utilization. Previous studies, however, have failed to determine the independent effects of health care organization variables and have rarely controlled for the confounding effects of patient characteristics. The current study will fill an unmet need for research through an innovative approach to the analysis of cesarean section use. A database on obstetrical practices will be developed by combining information from hospital discharge abstracts and birth records for the 470,000 deliveries occurring in California in 1985. These two data sources are necessary because each contains important variables absent from the other. Despite potential drawbacks, the use of existing public data is both efficient and statistically powerful. A multivariate model of cesarean section use based on logistic regression will be developed to determine the independent effects of health care organization variables. Case-mix adjustment will include the medical characteristics of patients, an improvement over the use of demographic characteristics alone as proxies for the risk of cesarean section. This research will contribute to the study of variations in medical practice. It will also clarify current confusion regarding patterns of cesarean section use, evaluate potential policy strategies for controlling the increasing use of cesarean section, and develop general methods for employing public data in health services research.