Despite longstanding efforts to improve newborn care, the ability of neonatology and the public to monitor and influence the quality, outcomes, and efficiency of care has been mixed. On the bright side, the Vermont-Oxford Network has pioneered the comparative measurement of care processes and outcomes primarily for very low-birth-weight newborns through benchmarking, research, and quality improvement initiatives. Statewide perinatal collaborative efforts, most notably the California Perinatal Quality Care Collaborative and the California Children’s Services (CPQCC/ CCS), have expanded the range of newborn care data and provided further stimulus to improvement activities. While these efforts remain important, the growth of neonatal intensive care unit (NICU) care has overtaken these data used by these initiatives, leaving the care and outcomes of most newborns in the dark. Currently, to our knowledge, no entity is responsible or has the means to monitor medical care for the total birth cohort in the United States, and only limited data sets are available at the state level. It is a striking truth that in 2012, more than threequarters of US NICU admissions were heavier than the usual 1500 g threshold (ie, very low birth weight) for data reporting in Vermont-Oxford Network member units, and the most common NICU admission was a normal-birth-weight newborn.1 The CPQCC/CCS captures data for almost all California newborns admitted to NICUs, including those heavier than 1500 g with high illness acuity. While the data collection is minimal for the 88% of NICU admitted newborns with lower illness acuity, there is just enough information to underscore the critical importance of shedding light on the care of larger and less premature newborns. In this issue of JAMA Pediatrics, Schulman et al2 report near population–based NICU admission rates in California, with a focus on those with 34 or more weeks’ gestation, representing 97% of all 2015 California births and 79% of all NICU admissions. The investigators found that inborn admission rates varied markedly across hospitals, with high rates in both regional-level and nonregional-level units (eg, community and intermediate, respectively). By itself, this is not surprising— levels of high illness acuity in newborns varied across hospitals just as much. What is striking is that hospitals with higher NICU admission rates had a lower proportion of admitted newborns with high illness acuity. This troubling finding suggests that the illness acuity level for NICU admissions differs from one hospital to the next, raising the possibility that it is not adequately known which newborns will benefit from NICU care and/or that a great deal of NICU care is provided needlessly. Equally concerning is that it has taken many years for these patterns of care to become visible. In the bright light of the Vermont-Oxford Network and CPQCC/CCS efforts, it seems that we have forgotten the less ill newborns that now dominate NICU care and the severe data limitations that hinder further research. The methods used in the study by Schulman et al2 provide a glimpse of the difficulties this causes. If asked as a hypothetical—design a study to measure the relationship between inborn newborn illness acuity and NICU admission rates across hospitals in California— one would choose a birth cohort design that includes all newborns. The data set would include maternal and newborn characteristics up to the point of care initiation, recognizing that diagnostic labeling can be biased by the quantity and type of medical care received by the newborn.3,4 Neonatal intensive care unit admission rates could then be compared across hospitals for gestational age and illness acuity levels. Health outcomes and postdischarge use associated with the varying NICU admission rates could also be assessed. Instead, the paucity of data available to CPQCC/CCS forced Schulman et al2 to use a narrow set of acuity measures, falling short of the full range of reasonable indications for NICU care, but they did include “early bacterial sepsis,” which may be biased in its diagnostic assignment. These limitations do not threaten the conclusion that admission criteria vary irrationally across hospitals, but the study cannot provide insight into the magnitude of the problem, the characteristics of newborns affected, or the consequences of the practice patterns. Knowledge of the full scope of neonatal care will require additional care and outcome measures for a wider set of births than exists today. Although they often fall short of all live births, the population-based newborn data sets include the US birthlinked death file, state all-payer claims data, and state Medicaid files. The birth-linked death file includes the entire US birth cohort with generally reliable information about each newborn and its mother, including infant deaths in the first year of life. Importantly, the file has an indicator for NICU admission for those states using the 2003 revised birth certificate form, but little other information about medical care is provided. Geographic identifiers are limited to counties. An alternative data set is all-payer claims data files. These are available to researchers for a few states. The files include both hospital and professional services from birth to beyond the initial hospital care episode. Medicaid is another Related article Opinion

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新生儿重症监护病房扩大时代的数据缺失

尽管长期以来努力改善新生儿护理，但新生儿科和公众监测和影响护理质量、结果和效率的能力参差不齐。从好的方面来说，佛蒙特-牛津网络率先通过基准测试、研究和质量改进计划，对主要针对极低出生体重新生儿的护理过程和结果进行比较测量。全州围产期协作努力，尤其是加州围产期优质护理协作组织和加州儿童服务中心 (CPQCC/CCS)，扩大了新生儿护理数据的范围，并为改进活动提供了进一步的刺激。虽然这些努力仍然很重要，但新生儿重症监护病房 (NICU) 护理的增长已经超过了这些举措使用的这些数据，让大多数新生儿的护理和结果一无所知。目前，据我们所知，没有任何实体负责或有能力监控美国整个出生队列的医疗保健，并且只有有限的州级数据集可用。一个惊人的事实是，2012 年，超过四分之三的美国 NICU 入院率高于佛蒙特-牛津网络成员单位的数据报告通常的 1500 克阈值（即极低出生体重），并且最常见的 NICU 入院率是出生体重正常的新生儿。1 CPQCC/CCS 收集了几乎所有入住 NICU 的加州新生儿的数据，包括体重超过 1500 克且病情严重的新生儿。虽然 88% 的新生儿重症监护病房收治的新生儿疾病敏锐度较低，但数据收集很少，有足够的信息来强调阐明照顾较大和较少早产儿的重要性的重要性。在本期 JAMA Pediatrics 中，Schulman 等人 2 报告了加利福尼亚州接近基于人口的 NICU 入院率，重点关注妊娠 34 周或以上者，占 2015 年加利福尼亚所有新生儿的 97%，占所有 NICU 入院人数的 79%。研究人员发现，不同医院的先天性入院率存在显着差异，地区级和非地区级单位（例如，分别为社区和中级）的住院率都很高。就其本身而言，这并不奇怪——新生儿的高疾病敏锐度水平因医院而异。令人吃惊的是，新生儿重症监护病房入院率较高的医院收治高疾病敏锐度的新生儿的比例较低。这一令人不安的发现表明，每家医院 NICU 入院的疾病严重程度不同，这增加了可能无法充分了解哪些新生儿将从 NICU 护理中受益和/或大量 NICU 护理是不必要的。同样令人担忧的是，这些护理模式花了很多年才变得可见。在佛蒙特-牛津网络和 CPQCC/CCS 努力的亮光下，我们似乎忘记了现在主导 NICU 护理的病情较轻的新生儿以及阻碍进一步研究的严重数据限制。Schulman 等人 2 的研究中使用的方法提供了由此造成的困难的一瞥。如果被问到假设——设计一项研究来衡量加州各医院的先天性新生儿疾病敏锐度与 NICU 入住率之间的关系——人们会选择包括所有新生儿的出生队列设计。数据集将包括直到护理开始时的孕产妇和新生儿特征，认识到诊断标签可能会因新生儿接受的医疗护理的数量和类型而有所偏差。 3,4 然后可以比较新生儿重症监护病房的入院率跨医院的胎龄和疾病敏锐度水平。还可以评估与不同 NICU 入住率相关的健康结果和出院后使用情况。相反，CPQCC/CCS 可用数据的缺乏迫使 Schulman 等人 2 使用一组狭窄的敏锐度测量，未达到 NICU 护理的全部合理指征，但它们确实包括“早期细菌性败血症”，这在其诊断分配中可能存在偏差。这些限制并不影响入院标准因医院而异的结论，但该研究无法深入了解问题的严重程度、受影响新生儿的特征或实践模式的后果。了解新生儿护理的全部范围将需要额外的护理和结果措施，以处理比现在更广泛的分娩。尽管它们经常达不到所有活产儿，但基于人口的新生儿数据集包括美国与出生相关的死亡档案、州所有支付者索赔数据和州医疗补助文件。与出生相关的死亡档案包括整个美国出生队列，其中包含关于每个新生儿及其母亲的普遍可靠的信息，包括出生后第一年的婴儿死亡。重要的是，该文件包含使用 2003 年修订的出生证明表格的州的 NICU 入院指标，但几乎没有提供有关医疗保健的其他信息。地理标识符仅限于县。另一种数据集是所有付款人索赔数据文件。这些可供一些州的研究人员使用。这些文件包括从出生到最初的医院护理事件之后的医院和专业服务。医疗补助是另一篇相关文章 意见 该文件包含使用 2003 年修订版出生证明表格的州的 NICU 入住指标，但几乎没有提供有关医疗保健的其他信息。地理标识符仅限于县。另一种数据集是所有付款人索赔数据文件。这些可供一些州的研究人员使用。这些文件包括从出生到最初的医院护理事件之后的医院和专业服务。医疗补助是另一篇相关文章 意见 该文件包含使用 2003 年修订版出生证明表格的州的 NICU 入住指标，但几乎没有提供有关医疗保健的其他信息。地理标识符仅限于县。另一种数据集是所有付款人索赔数据文件。这些可供一些州的研究人员使用。这些文件包括从出生到最初的医院护理事件之后的医院和专业服务。医疗补助是另一篇相关文章 意见