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Ingef 研究数据库的抽样策略、特征和代表性。

Sampling strategy, characteristics and representativeness of the InGef research database.

机构信息

InGef - Institute for Applied Health Research Berlin GmbH [Institut für angewandte Gesundheitsforschung Berlin GmbH], Germany.

InGef - Institute for Applied Health Research Berlin GmbH [Institut für angewandte Gesundheitsforschung Berlin GmbH], Germany.

出版信息

Public Health. 2022 May;206:57-62. doi: 10.1016/j.puhe.2022.02.013. Epub 2022 Apr 1.

Abstract

OBJECTIVES

The aim of this study was to describe the sampling strategy as well as characteristics and the external validity of a representative sample database drawn from the German InGef research database.

STUDY DESIGN

This is a retrospective cohort study using anonymized claims data for the year 2019.

METHODS

The InGef research database is an anonymized healthcare database with longitudinal claims data from approximately 8.8 Mio insurees. A sample of four million insurees was drawn intended to be representative for the German population with respect to age, sex and region. In addition to demographic information, data on hospitalization rates, mortality rates and drug prescription rates were analysed from the InGef sample database for the year 2019 to demonstrate validity and representativeness. Corresponding national reference data were obtained from official sources.

RESULTS

The distributions of sex and age were similar in the InGef sample database and Germany (proportion of women: 50.8% vs 50.7%; mean age: 44.1 vs 43.9 years). The proportion of insurees living in the eastern part of Germany was lower in the InGef sample database (16.5% vs 19.5%). There was good accordance with German reference data with respect to hospitalization rates and overall mortality rates. Prescription rates for the 20 most often reimbursed drug classes were slightly higher in the InGef sample database.

CONCLUSIONS

The InGef sample database shows good overall agreement with the German population on measures of morbidity, mortality and drug usage.

摘要

目的

本研究旨在描述德国 InGef 研究数据库中代表性样本数据库的抽样策略以及特征和外部有效性。

研究设计

这是一项使用 2019 年匿名索赔数据的回顾性队列研究。

方法

Ingef 研究数据库是一个匿名的医疗保健数据库,包含来自约 880 万被保险人的纵向索赔数据。抽取了四百万名被保险人的样本,旨在在年龄、性别和地区方面代表德国人口。除了人口统计信息外,还从 InGef 样本数据库中分析了 2019 年的住院率、死亡率和药物处方率数据,以证明有效性和代表性。相应的国家参考数据从官方来源获得。

结果

Ingef 样本数据库和德国的性别和年龄分布相似(女性比例:50.8%对 50.7%;平均年龄:44.1 对 43.9 岁)。Ingef 样本数据库中居住在德国东部的被保险人比例较低(16.5%对 19.5%)。在住院率和总体死亡率方面,与德国参考数据有很好的一致性。Ingef 样本数据库中 20 种最常报销药物类别的处方率略高。

结论

在发病率、死亡率和药物使用方面,Ingef 样本数据库与德国人口总体上具有良好的一致性。

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