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[医院出院数据中医院标识符的连续性——对2005年至2013年德国全国疾病诊断相关分组统计数据的分析]

[Continuity of hospital identifiers in hospital discharge data - Analysis of the nationwide German DRG Statistics from 2005 to 2013].

作者信息

Nimptsch Ulrike, Wengler Annelene, Mansky Thomas

机构信息

Technische Universität Berlin, Fachgebiet Strukturentwicklung und Qualitätsmanagement im Gesundheitswesen, Berlin, Deutschland.

Technische Universität Berlin, Fachgebiet Strukturentwicklung und Qualitätsmanagement im Gesundheitswesen, Berlin, Deutschland.

出版信息

Z Evid Fortbild Qual Gesundhwes. 2016 Nov;117:38-44. doi: 10.1016/j.zefq.2016.07.009. Epub 2016 Sep 2.

Abstract

BACKGROUND

In Germany, nationwide hospital discharge data (DRG statistics provided by the research data centers of the Federal Statistical Office and the Statistical Offices of the 'Länder') are increasingly used as data source for health services research. Within this data hospitals can be separated via their hospital identifier ([Institutionskennzeichen] IK). However, this hospital identifier primarily designates the invoicing unit and is not necessarily equivalent to one hospital location. Aiming to investigate direction and extent of possible bias in hospital-level analyses this study examines the continuity of the hospital identifier within a cross-sectional and longitudinal approach and compares the results to official hospital census statistics.

METHODS

Within the DRG statistics from 2005 to 2013 the annual number of hospitals as classified by hospital identifiers was counted for each year of observation. The annual number of hospitals derived from DRG statistics was compared to the number of hospitals in the official census statistics 'Grunddaten der Krankenhäuser'. Subsequently, the temporal continuity of hospital identifiers in the DRG statistics was analyzed within cohorts of hospitals.

RESULTS

Until 2013, the annual number of hospital identifiers in the DRG statistics fell by 175 (from 1,725 to 1,550). This decline affected only providers with small or medium case volume. The number of hospitals identified in the DRG statistics was lower than the number given in the census statistics (e.g., in 2013 1,550 IK vs. 1,668 hospitals in the census statistics). The longitudinal analyses revealed that the majority of hospital identifiers persisted in the years of observation, while one fifth of hospital identifiers changed.

CONCLUSION

In cross-sectional studies of German hospital discharge data the separation of hospitals via the hospital identifier might lead to underestimating the number of hospitals and consequential overestimation of caseload per hospital. Discontinuities of hospital identifiers over time might impair the follow-up of hospital cohorts. These limitations must be taken into account in analyses of German hospital discharge data focusing on the hospital level.

摘要

背景

在德国,全国性医院出院数据(由联邦统计局和各州统计局的研究数据中心提供的疾病诊断相关分组统计数据)越来越多地被用作卫生服务研究的数据源。在这些数据中,医院可以通过其医院标识符([机构标识]IK)进行区分。然而,这个医院标识符主要指定开票单位,并不一定等同于一个医院地点。为了调查医院层面分析中可能存在的偏差的方向和程度,本研究采用横断面和纵向方法研究医院标识符的连续性,并将结果与官方医院普查统计数据进行比较。

方法

在2005年至2013年的疾病诊断相关分组统计数据中,统计每年观察期内按医院标识符分类的医院数量。将疾病诊断相关分组统计数据得出的医院年度数量与官方普查统计数据“医院基本数据”中的医院数量进行比较。随后,在医院队列中分析疾病诊断相关分组统计数据中医院标识符的时间连续性。

结果

到2013年,疾病诊断相关分组统计数据中的医院标识符年度数量减少了175个(从1725个降至1550个)。这种下降仅影响病例量小或中等的提供者。疾病诊断相关分组统计数据中确定的医院数量低于普查统计数据中的数量(例如,2013年为1550个IK,而普查统计数据中有1668家医院)。纵向分析显示,大多数医院标识符在观察期内持续存在,而五分之一的医院标识符发生了变化。

结论

在对德国医院出院数据的横断面研究中,通过医院标识符区分医院可能导致低估医院数量,并进而高估每家医院的病例量。医院标识符随时间的不连续性可能会损害医院队列的随访。在关注医院层面的德国医院出院数据分析中,必须考虑这些局限性。

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