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应用 10 组分类系统的两家德国医院剖宫产率分析。

Analysis of cesarean section rates in two German hospitals applying the 10-Group Classification System.

机构信息

Department of Obstetrics and Prenatal Medicine, University Hospital Bonn, Bonn, Germany.

Department of Gynecology and Obstetrics, Porz am Rhein Hospital, Cologne, Germany.

出版信息

J Perinat Med. 2021 Apr 8;49(7):818-829. doi: 10.1515/jpm-2020-0505. Print 2021 Sep 27.

Abstract

OBJECTIVES

In Germany, cesarean section (CS) rates more than doubled within the past two decades. For analysis, auditing and inter-hospital comparison, the 10-Group Classification System (TGCS) is recommended. We used the TGCS to analyze CS rates in two German hospitals of different levels of care.

METHODS

From October 2017 to September 2018, data were prospectively collected. Unit A is a level three university hospital, unit B a level one district hospital. The German birth registry was used for comparison with national data. We performed two-sample Z tests and bootstrapping to compare aggregated (unit A + B) with national data and unit A with unit B.

RESULTS

In both datasets (national data and aggregated data unit A + B), Robson group (RG) 5 was the largest contributor to the overall CS rate. Compared to national data, group sizes in RG 1 and 3 were significantly smaller in the units under investigation, RG 8 and 10 significantly larger. Total CS rates between the two units differed (40.7 vs. 28.4%, p<0.001). The CS rate in RG 5 and RG 10 was different (p<0.01 for both). The most relative frequent RG in both units consisted of group 5, followed by group 10 and 2a.

CONCLUSIONS

The analysis allowed us to explain different CS rates with differences in the study population and with differences in the clinical practice. These results serve as a starting point for audits, inter-hospital comparisons and for interventions aiming to reduce CS rates.

摘要

目的

在过去的二十年中,德国的剖宫产率翻了一番多。为了进行分析、审核和医院间比较,推荐使用 10 组分类系统(TGCS)。我们使用 TGCS 分析了两家不同级别护理的德国医院的剖宫产率。

方法

从 2017 年 10 月到 2018 年 9 月,前瞻性地收集数据。A 单位是三级大学医院,B 单位是一级地区医院。使用德国出生登记处与国家数据进行比较。我们进行了两样本 Z 检验和自举法,比较了(A+B 单位)汇总数据与国家数据以及 A 单位与 B 单位。

结果

在两个数据集(国家数据和 A+B 单位汇总数据)中,Robson 组(RG)5 是总体剖宫产率的最大贡献者。与国家数据相比,研究单位中 RG 1 和 3 的组大小明显较小,RG 8 和 10 明显较大。两个单位的总剖宫产率不同(40.7%比 28.4%,p<0.001)。RG 5 和 RG 10 的剖宫产率也不同(两者均为 p<0.01)。两个单位中最常见的 RG 均为 5 组,其次是 10 组和 2a 组。

结论

分析表明,不同的研究人群和不同的临床实践导致了剖宫产率的不同。这些结果为审核、医院间比较以及旨在降低剖宫产率的干预措施提供了起点。

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