ECONOMIC INFLUENCES (ESPECIALLY HMOS) ON CESAREANS

多元回归分析将被用来检验假设 最近美国剖腹产率的急剧上升是由于艺术 经济因素。有两个经济影响非常突出： 医疗事故诉讼；以及医生和医院的自身利益。这个 建议对前者进行研究控制，并将重点放在后者。一 研究假设是，在产科医生比例较高的地区 出生，和/或产科病房的高空置率，剖腹产率较高 将补偿提供者否则将是较低的收入。一个 需要检验的相关假设是，剖腹产率在以下情况下更高 近年来，出生人口数量有所下降。这是一种假设 拟议项目的核心是HMO(健康维护 组织)产科分娩的剖腹产率将低于 按服务收费的做法(控制其他因素)，因为卫生保健组织必须 吸收与剖腹产相关的额外费用，而其他 供应商将从中受益。 申请人已经收集了一个由30,000名活产婴儿组成的数据集 1982年、1983年、1984年和1985年在纽约州发生的 有保健组织在运营和提供产科服务。大致 三分之一的婴儿出生在医疗保健机构。这些数据包括，每一次出生， 母亲的人口统计和背景数据；她的住所和所在地 分娩；产次、孕妇、分娩方法；产前护理；出生体重 和出生结局；医院；以及医疗保健组织/非医疗保健组织。区域数据，包括 市场状况(如产科能力与需求的关系)，以及 产科医疗事故诉讼也将被使用。 在统计分析中，将使用两个不同的因变量。 在一组分析中，因变量将是交付方法， 剖腹产或经阴道。然而，由于这些方程很可能是 由反映诊断的独立变量主导(臀位 表现、难产等)，在另一组分析中诊断本身 将被用作因变量。 这项研究将大大增加关于提供者诱导的文献 对医疗保健的需求；保健组织；以及 剖腹产的决定因素。它具有成本控制、医疗和伦理方面的优势 这意味着什么。

Multiple regression analysis will be used to test the hypothesis that the recent dramatic increases in the U.S. cesarean rate is due in art to economic factors. Two economic influences stand out: the threat of a malpractice suit; and the self-interest of doctors and hospitals. The proposed research controls for the former and focuses on the latter. One research hypothesis is that in areas with high ratios of obstetricians to births, and/or high vacancy rates in obstetric wards, higher cesarean rates will compensate providers for what would other wise be lower incomes. A related hypothesis to be tested is that c-section rates are higher where the numbers of births have fallen in recent years. The hypothesis which is central to the proposed project is that HMO (health maintenance organization) obstetric deliveries will have a lower cesarean rate than fee-for-service practice (controlling for other factors), as HMOs have to absorb the additional costs associated with c-sections, while other providers stand to gain from them. The applicant has assembled a data set consisting of 30,000 live births occurring in New York state in 1982, 1983, 1984, and 1985 in areas which there were HMOs operating and providing obstetric services. Approximately one-third of the births are in HMOs. The data include, for each birth, demographic and background data for the mother; her residence and place of delivery; parity, gravida, method of delivery; prenatal care; birthweight and birth outcomes; hospital; and HMO/non-HMO. Regional data, including market conditions (such as obstetric capacity in relation to demand), and obstetric malpractice suits will also be used. In the statistical analysis two different dependent variables will be used. In one set of analyses, the dependent variable will be method of delivery, cesarean or vaginal. However, as these equations are likely to be dominated by independent variables reflecting diagnosis (breech presentation, dystocia, etc.), in another set of analyses diagnosis itself will be used as the dependent variable. The research will add significantly to the literature on provider-induced demand for medical care; health maintenance organizations; and the determinants of cesareans. It has cost-control, medical, and ethical implications.