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择期行颅肿物切除术患者的住院和出院后结局。

Inpatient and Postdischarge Outcomes Following Elective Craniotomy for Mass Lesions.

机构信息

MPA Healthcare Solutions, Chicago, Illinois.

Department of Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois.

出版信息

Neurosurgery. 2019 Jul 1;85(1):E109-E115. doi: 10.1093/neuros/nyy396.

Abstract

BACKGROUND

Interpretation of hospital quality requires objective evaluation of both inpatient and postdischarge adverse outcomes (AOs).

OBJECTIVE

To develop risk-adjusted predictive models for inpatient and 90-d postdischarge AOs in elective craniotomy and apply those models to individual hospital performance to provide benchmarks to improve care.

METHODS

The Medicare Limited Dataset (2012-2014) was used to define all elective craniotomy procedures for mass lesions in patients ≥65 yr. Predictive logistic models were designed for inpatient mortality, inpatient prolonged length of stay, 90-d postdischarge deaths without readmission, and 90-d readmissions after exclusions. The total observed patients with one or more AOs were then compared to predicted AO values, and z-scores were computed for each hospital that met minimum volume requirements. Risk-adjusted AO rates allowed stratification of eligible hospitals into deciles of performance.

RESULTS

The hospital evaluation was performed for 223 facilities with 7624 patients that met criteria. A total of 849 patients (11.1%) died inclusive of 90 d postdischarge; 635 (8.3%) were 3σ length-of-stay outliers; and 1928 patients (25.3%) with one or more 90-d readmissions; 2716 patients experienced one or more AOs (35.6%). Six hospitals were 2 z-scores better than average, and 8 were 2 z-scores poorer. The median risk-adjusted AO rate was 18% for the first decile and 53.4% for the 10th decile.

CONCLUSION

There was a 35% difference between best and suboptimal performing hospitals for this operation. Hospitals must know their risk-adjusted AO rates and benchmark their results to inform processes of care redesign.

摘要

背景

医院质量的评估需要客观地评估住院和出院后不良事件(AO)。

目的

为择期开颅术的住院和 90 天出院后不良事件建立风险调整预测模型,并将这些模型应用于医院的个体绩效,以提供改善护理的基准。

方法

使用医疗保险有限数据集(2012-2014 年)定义所有 65 岁以上患者因肿块进行的择期开颅术。为住院死亡率、住院时间延长、90 天无再入院的出院后死亡、90 天再入院进行了预测逻辑模型设计,排除后。然后将观察到的有一个或多个 AO 的患者总数与预测的 AO 值进行比较,并为符合最低容量要求的每个医院计算 z 分数。风险调整后的 AO 率允许将合格的医院分层为表现的十分位数。

结果

对符合标准的 223 家医院中的 7624 名患者进行了医院评估。共有 849 名患者(11.1%)死亡,包括 90 天出院后;635 名患者(8.3%)为 3σ 住院时间过长的离群值;1928 名患者(25.3%)在 90 天内有一次或多次再入院;2716 名患者经历了一次或多次 AO(35.6%)。6 家医院的表现比平均水平高出 2 个 z 分数,8 家医院的表现比平均水平低 2 个 z 分数。第一个十分位数的风险调整 AO 率中位数为 18%,第十个十分位数的风险调整 AO 率中位数为 53.4%。

结论

对于这项手术,最好和表现不佳的医院之间存在 35%的差异。医院必须了解其风险调整后的 AO 率,并将其结果作为基准,以告知护理流程的重新设计。

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