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[Continuity of hospital identifiers in hospital discharge data - Analysis of the nationwide German DRG Statistics from 2005 to 2013]. / Kontinuität der Institutionskennzeichen in Krankenhausabrechnungsdaten ­ Analyse der bundesweiten DRG-Statistik von 2005 bis 2013.
Nimptsch, Ulrike; Wengler, Annelene; Mansky, Thomas.
Afiliação
  • Nimptsch U; Technische Universität Berlin, Fachgebiet Strukturentwicklung und Qualitätsmanagement im Gesundheitswesen, Berlin, Deutschland. Electronic address: ulrike.nimptsch@tu-berlin.de.
  • Wengler A; Technische Universität Berlin, Fachgebiet Strukturentwicklung und Qualitätsmanagement im Gesundheitswesen, Berlin, Deutschland.
  • Mansky T; Technische Universität Berlin, Fachgebiet Strukturentwicklung und Qualitätsmanagement im Gesundheitswesen, Berlin, Deutschland.
Z Evid Fortbild Qual Gesundhwes ; 117: 38-44, 2016 Nov.
Article em De | MEDLINE | ID: mdl-27938728
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.
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Texto completo: 1 Temas: ECOS / Aspectos_gerais Bases de dados: MEDLINE Assunto principal: Alta do Paciente / Grupos Diagnósticos Relacionados Tipo de estudo: Observational_studies / Prevalence_studies / Risk_factors_studies Limite: Humans País/Região como assunto: Europa Idioma: De Revista: Z Evid Fortbild Qual Gesundhwes Assunto da revista: MEDICINA Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Temas: ECOS / Aspectos_gerais Bases de dados: MEDLINE Assunto principal: Alta do Paciente / Grupos Diagnósticos Relacionados Tipo de estudo: Observational_studies / Prevalence_studies / Risk_factors_studies Limite: Humans País/Região como assunto: Europa Idioma: De Revista: Z Evid Fortbild Qual Gesundhwes Assunto da revista: MEDICINA Ano de publicação: 2016 Tipo de documento: Article