REGIONALIZATION, MARKET FORCES, AND NEONATAL MORTALITY

20世纪80年代和90年代，新生儿重症监护病房(NICU)迅速扩散到社区医院，相关的高危病例从区域NICU转移到这些社区医院。这些较新的NICU大多是较小的中级NICU，不能为危重婴儿提供全方位的护理。虽然以前的研究发现，在设有区域(III级)NICU的医院分娩的婴儿死亡率较低，这些医院可以为婴儿提供全方位的重症监护服务，但关于这些差异仍有许多需要了解。具体地说，这些研究都没有研究不同水平的NICU的相对表现是如何随着时间的推移而变化的，而且以前的大多数研究都没有对临床风险进行控制。在这段时间里，健康维护组织(HMO)和其他形式的管理性医疗也迅速增长，医院面临的财务压力也越来越大。但没有研究考察医院竞争、医院的财务压力或管理式护理如何影响NICU的增长、高危新生儿的护理或新生儿结局。在以前的研究中，我们已经开始开发使用一年的数据来更全面地控制临床风险的模型(Phibbs，1996)。最引人注目的发现是：1)无论病人数量如何，在设有中等和扩大中等水平NICU的医院出生的婴儿的死亡率与没有NICU的医院出生的婴儿没有什么不同；以及2)由医疗保健组织和医疗补助计划投保的患者死亡率更高。但是，这项研究只基于一年(1990年)的数据，来自一个州(加利福尼亚州)，它没有提供这些差异如何随着时间的推移而变化的信息。这些影响是如何随时间改变(或不改变)的，具有非常重要的政策含义。如果这些差异持续存在，或者正在变得越来越大，那么政策干预可能是必要的，因为潜在的可预防死亡人数将非常多。相反，如果这些差异随着时间的推移而稳步缩小，那么破坏性的政策干预可能就没有必要了。这项建议将建立在我们已经使用加州出生证明与母亲和婴儿的出院摘要的联系进行的分析的基础上，将联系的数据扩展到1983-1998年。它还将包括其他州(佛罗里达州、纽约州、华盛顿州和威斯康星州)不同时间段的数据。这一大组数据将使我们能够仔细检查NICU的普及和管理护理的增长如何影响新生儿死亡率。我们将使用Logistic回归模型，包括考虑数据的时间序列性质的模型来检查NICU护理水平、市场力量和新生儿死亡率之间的关联，控制关联数据中可用的广泛风险因素。

The 1980S and 1990s have seen a rapid diffusion of neonatal intensive care units (NICUs) into community hospitals, and an associated shift of high-risk cases from regional NICUs to these community hospitals. Most of these newer NICUs are smaller, intermediate level NICUs that do not provide a full range of care for critically ill infants. While previous studies have found lower mortality for births that occur at hospitals with regional (level III) NICUs that can provide the full range of intensive care services for infants, much remains to be learned about these differences. Specifically, none of these studies have examined how the relative performance of different levels of NICUs is changing over time and most of the previous studies did not control for clinical risks. This time period has also seen rapid growth in health maintenance organizations (HMOs) and other forms of managed care, and increasing financial pressures on hospitals. But there are no studies that examine how hospital competition, financial pressures on hospitals, or managed care effect NICU growth, care for high-risk newborns, or neonatal outcomes. In previous research we have begun to develop models that control much more fully for clinical risks using a single year of data (Phibbs, 1996). The most striking findings were: 1) births in hospitals with intermediate and expanded intermediate level NICUs, regardless of patient volume, had mortality that was no different than births at hospitals without NICUs; and 2) patient insured by HMOs and Medicaid had higher mortality. But, this study was based on data from only one year (1990), from a single state (California), and it provides no information on how these differences are changing over time. How these effects are changing (or not changing) over time has very important policy implications. If these differences persist, or are growing larger, then policy interventions may be necessary since the number of potentially preventable deaths would be very large. Conversely, if these differences are steadily diminishing over time, then disruptive policy interventions may be unnecessary. This proposal will build on the analyses we have already done using the California linkage of the birth certificates with the discharge abstracts for the mothers and infants, extending the linked data to the years 1983-1998. It will also include data from other states (Florida, New York, Washing, and Wisconsin) for varying time periods. This large panel of data will allow a careful examination of how the diffusion of NICUs and the growth of managed care have effected neonatal mortality. We will use logistic regression models, including models that account for the time series nature of the data to examine the association between levels of NICU care, market forces, and neonatal mortality, controlling for the wide range of risk factors that are available in the linked data.