Department of Intensive Care Medicine, The Queen Elizabeth Hospital, Woodville SA 5011, Australia.
BMC Med Res Methodol. 2010 Apr 19;10:32. doi: 10.1186/1471-2288-10-32.
Controversy has attended the relationship between risk-adjusted mortality and process-of-care. There would be advantage in the establishment, at the data-base level, of global quantitative indices subsuming the diversity of process-of-care.
A retrospective, cohort study of patients identified in the Australian and New Zealand Intensive Care Society Adult Patient Database, 1993-2003, at the level of geographic and ICU-level descriptors (n = 35), for both hospital survivors and non-survivors. Process-of-care indices were established by analysis of: (i) the smoothed time-hazard curve of individual patient discharge and determined by pharmaco-kinetic methods as area under the hazard-curve (AUC), reflecting the integrated experience of the discharge process, and time-to-peak-hazard (TMAX, in days), reflecting the time to maximum rate of hospital discharge; and (ii) individual patient ability to optimize output (as length-of-stay) for recorded data-base physiological inputs; estimated as a technical production-efficiency (TE, scaled [0,(maximum)1]), via the econometric technique of stochastic frontier analysis. For each descriptor, multivariate correlation-relationships between indices and summed mortality probability were determined.
The data-set consisted of 223129 patients from 99 ICUs with mean (SD) age and APACHE III score of 59.2(18.9) years and 52.7(30.6) respectively; 41.7% were female and 45.7% were mechanically ventilated within the first 24 hours post-admission. For survivors, AUC was maximal in rural and for-profit ICUs, whereas TMAX (>or= 7.8 days) and TE (>or= 0.74) were maximal in tertiary-ICUs. For non-survivors, AUC was maximal in tertiary-ICUs, but TMAX (>or= 4.2 days) and TE (>or= 0.69) were maximal in for-profit ICUs. Across descriptors, significant differences in indices were demonstrated (analysis-of-variance, P <or= 0.0001). Total explained variance, for survivors (0.89) and non-survivors (0.89), was maximized by combinations of indices demonstrating a low correlation with mortality probability.
Global indices reflecting process of care may be formally established at the level of national patient data-bases. These indices appear orthogonal to mortality outcome.
风险调整死亡率与治疗过程之间的关系存在争议。在数据库级别建立包含治疗过程多样性的全局定量指标将具有优势。
这是一项回顾性队列研究，对 1993 年至 2003 年澳大利亚和新西兰重症监护学会成人患者数据库中确定的患者（n=35）进行研究，这些患者按地理位置和 ICU 水平描述符进行分层，包括医院幸存者和非幸存者。通过分析个体患者出院的平滑时间风险曲线来建立治疗过程指标，并通过药代动力学方法确定曲线下面积（AUC），反映出院过程的综合经验，以及达到风险高峰的时间（TMAX，以天为单位），反映医院出院的最大速率达到时间；以及（ii）个体患者优化记录数据库生理输入的输出（以住院时间表示）的能力；通过随机前沿分析的计量经济学技术估计为技术生产效率（TE，缩放到[0，（最大）1]）。对于每个描述符，确定了指标与总和死亡率概率之间的多变量相关关系。
数据集包含来自 99 个 ICU 的 223129 名患者，平均（SD）年龄和 APACHE III 评分为 59.2（18.9）岁和 52.7（30.6），分别为 41.7%为女性，45.7%在入院后 24 小时内接受机械通气。对于幸存者，AUC 在农村和营利性 ICU 中最大，而 TMAX（≥7.8 天）和 TE（≥0.74）在三级 ICU 中最大。对于非幸存者，AUC 在三级 ICU 中最大，但 TMAX（≥4.2 天）和 TE（≥0.69）在营利性 ICU 中最大。在所有描述符中，均证明了指标之间存在显著差异（方差分析，P≤0.0001）。幸存者（0.89）和非幸存者（0.89）的总解释方差通过组合表现出与死亡率概率低相关性的指标达到最大化。
可以在国家患者数据库级别正式建立反映治疗过程的全局指标。这些指标似乎与死亡率结果正交。
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