Richardson D, Tarnow-Mordi W O, Lee S K
Joint Program in Neonatology (Beth Israel Deaconess Medical Center, Brigham and Women's Hospital, Children's Hospital and Harvard Medical School) and Harvard School of Public Health, Boston, MA, USA.
Pediatrics. 1999 Jan;103(1 Suppl E):255-65.
We can learn what is achievable with current technologies by comparing our neonatal intensive care unit outcomes with others. Because neonatal intensive care units may vary with respect to their case-mix, risk adjustment is essential to making fair comparisons in any research that does not equalize risks through randomization. Risk adjustment first requires strict definition of each specific outcome. Then each risk factor is measured and weighted accordingly. Severity of illness scores are a special form of risk adjustment. The leading newborn illness severity scores rely on physiology-based items from bedside vital signs and laboratory tests. The mechanics of score development are discussed including item selection, definition, collection, and potential biases. The process of weighting risk factors usually involves building multivariate models. Issues of derivation, validation, discrimination, calibration, and reliability affect the utility of all scores. Once a comparison is appropriately risk-adjusted, there are important cautions about interpretation, including the source of the reference (benchmark) population, sample size, and biases from incomplete risk adjustment. Nonetheless, these findings can spur quality improvement efforts that can lead to dramatic, system-wide improvements in outcomes.
通过将我们新生儿重症监护病房的治疗结果与其他病房进行比较，我们可以了解当前技术所能达到的效果。由于新生儿重症监护病房的病例组合可能存在差异，在任何未通过随机化使风险均衡的研究中，风险调整对于进行公平比较至关重要。风险调整首先需要对每个特定结果进行严格定义。然后对每个风险因素进行测量并相应加权。疾病严重程度评分是风险调整的一种特殊形式。主要的新生儿疾病严重程度评分依赖于床边生命体征和实验室检查中基于生理学的项目。讨论了评分制定的机制，包括项目选择、定义、收集和潜在偏差。对风险因素进行加权的过程通常涉及构建多变量模型。推导、验证、区分、校准和可靠性等问题会影响所有评分的效用。一旦比较进行了适当的风险调整，在解释时就有一些重要的注意事项，包括参考（基准）人群的来源、样本大小以及不完全风险调整导致的偏差。尽管如此，这些发现可以推动质量改进工作，从而带来显著的、全系统范围的结果改善。
