Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)) · 2026
[Good Practice Secondary Data Analysis: Guidelines and Recommendations, Version 4].
Аннотация на английскомСтатьяНазвание и аннотация: Перевод в очереди
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Swart E, Alibone M, Epping J, Grobe T G, Hoffmann F, Horenkamp-Sonntag D, Ihle P, March S, Rommel A, Stallmann C, Tesch F, Gothe H
Аннотация
ABSTRACT: The Good Practice Guidelines (GPS) for Secondary Data Analysis were first published in 2005. Following a further revision in 2025, Version 4 is now being released. The revision of the GPS was carried out by the Working Group on the Collection and Use of Secondary Data (AGENS) of the German Society for Social Medicine and Prevention (DGSMP) and the German Society for Epidemiology (DGEpi), as well as the Working Group on the Validation and Linkage of Secondary Data of the German Network for Health Services Research (DNVF).
ABSTRACT: Compared to the previous version, in addition to clarifications and updates to the content, some recommendations have also been added. These include recommendations on the study population (recommendation 3.3), analysis strategy (3.6), registration (3.8), the interaction between data analysis, clinical expertise, and the patient perspective (5.3), data dictionary (6.8), interim analyses (7.3), distributed computing (7.4), documentation of analysis steps (7.6), use of pooled data and analyses of data distributed across different locations (8.12), legal framework (9.1), and scientific communication (11.4).
ABSTRACT: The GPS establish a standard for conducting secondary data analyses in accordance with scientific principles. It specifically complements other good practice guidelines and reporting standards in the fields of epidemiology and health services research (GEP, Good Practice Data Linkage, STROSA reporting standard). The GPS is intended as a guideline for the planning, conducting, and analysis of studies based on secondary data, in accordance with current legal frameworks. Specific study conditions and the specific characteristics of certain data may necessitate deviations from the GPS recommendations, provided such deviations are justified.
ABSTRACT: The GPS is intended for all researchers who use scientific methods to study, analyze and interpret secondary data. The GPS focus on health-related data in Germany, i. e., typically healthcare-related data such as routine data from statutory health, long-term care, pension, and accident insurance (social data), outpatient and inpatient care facilities, and registry data.
ABSTRACT: Compared to the previous version, in addition to clarifications and updates to the content, some recommendations have also been added. These include recommendations on the study population (recommendation 3.3), analysis strategy (3.6), registration (3.8), the interaction between data analysis, clinical expertise, and the patient perspective (5.3), data dictionary (6.8), interim analyses (7.3), distributed computing (7.4), documentation of analysis steps (7.6), use of pooled data and analyses of data distributed across different locations (8.12), legal framework (9.1), and scientific communication (11.4).
ABSTRACT: The GPS establish a standard for conducting secondary data analyses in accordance with scientific principles. It specifically complements other good practice guidelines and reporting standards in the fields of epidemiology and health services research (GEP, Good Practice Data Linkage, STROSA reporting standard). The GPS is intended as a guideline for the planning, conducting, and analysis of studies based on secondary data, in accordance with current legal frameworks. Specific study conditions and the specific characteristics of certain data may necessitate deviations from the GPS recommendations, provided such deviations are justified.
ABSTRACT: The GPS is intended for all researchers who use scientific methods to study, analyze and interpret secondary data. The GPS focus on health-related data in Germany, i. e., typically healthcare-related data such as routine data from statutory health, long-term care, pension, and accident insurance (social data), outpatient and inpatient care facilities, and registry data.