基于病例组合分组的诊断评分的推导与验证，以预测30天内死亡或紧急再入院情况。

Derivation and validation of a diagnostic score based on case-mix groups to predict 30-day death or urgent readmission.

作者信息

van Walraven Carl, Wong Jenna, Forster Alan J

机构信息

Ottawa Hospital Research Institute, Administrative Services Building, Room 1003, 1053 Carling Avenue, Ottawa, ON K1Y 4E9, Canada.

出版信息

Open Med. 2012 Jul 19;6(3):e90-e100. Print 2012.

PMID:23687525

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3654506/

Abstract

BACKGROUND

Between 5% and 10% of patients die or are urgently readmitted within 30 days of discharge from hospital. Readmission risk indexes have either excluded acute diagnoses or modelled them as multiple distinct variables. In this study, we derived and validated a score summarizing the influence of acute hospital diagnoses and procedures on death or urgent readmission within 30 days.

METHODS

From population-based hospital abstracts in Ontario, we randomly sampled 200 000 discharges between April 2003 and March 2009 and determined who had been readmitted urgently or died within 30 days of discharge. We used generalized estimating equation modelling, with a sample of 100 000 patients, to measure the adjusted association of various case-mix groups (CMGs-homogenous groups of acute care inpatients with similar clinical and resource-utilization characteristics) with 30-day death or urgent readmission. This final model was transformed into a scoring system that was validated in the remaining 100 000 patients.

RESULTS

Patients in the derivation set belonged to 1 of 506 CMGs and had a 6.8% risk of 30-day death or urgent readmission. Forty-seven CMG codes (more than half of which were directly related to chronic diseases) were independently associated with this outcome, which led to a CMG score that ranged from -6 to 7 points. The CMG score was significantly associated with 30-day death or urgent readmission (unadjusted odds ratio for a 1-point increase in CMG score 1.52, 95% confidence interval [CI] 1.49-1.56). Alone, the CMG score was only moderately discriminative (C statistic 0.650, 95% CI 0.644-0.656). However, when the CMG score was added to a validated risk index for death or readmission, the C statistic increased to 0.759 (95% CI 0.753-0.765). The CMG score was well calibrated for 30-day death or readmission.

INTERPRETATION

In this study, we developed a scoring system for acute hospital diagnoses and procedures that could be used as part of a risk-adjustment methodology for analyses of postdischarge outcomes.

摘要

背景

5%至10%的患者在出院后30天内死亡或被紧急再次入院。再入院风险指数要么排除急性诊断，要么将其建模为多个不同变量。在本研究中，我们推导并验证了一个分数，该分数总结了急性医院诊断和治疗对30天内死亡或紧急再入院的影响。

方法

从安大略省基于人群的医院摘要中，我们随机抽取了2003年4月至2009年3月期间的20万例出院病例，并确定了哪些患者在出院后30天内被紧急再次入院或死亡。我们使用广义估计方程模型，以10万例患者为样本，测量各种病例组合组（CMG——具有相似临床和资源利用特征的急性护理住院患者的同质组）与30天死亡或紧急再入院的调整后关联。这个最终模型被转化为一个评分系统，并在其余10万例患者中进行了验证。

结果

推导集中的患者属于506个CMG中的1个，30天死亡或紧急再入院风险为6.8%。47个CMG编码（其中一半以上与慢性病直接相关）与这一结果独立相关，并得出了一个CMG分数，范围从-6分到7分。CMG分数与3G天死亡或紧急再入院显著相关（CMG分数每增加1分，未调整优势比为1.52，95%置信区间[CI]1.49-1.56）。单独来看，CMG分数的区分度仅为中等（C统计量为0.650，95%CI为0.644-0.656）。然而，当将CMG分数添加到已验证的死亡或再入院风险指数中时，C统计量增加到0.759（95%CI为0.753-0.765）。CMG分数在30天死亡或再入院方面校准良好。