[Individual linkage of primary data with secondary and registry data within large cohort studies - capabilities and procedural proposals]

Bausteine und Strukturen für eine leistungsfähige Real-World-Data-Analyse

Hintergrund

Die Real-World-Data (RWD)-Analyse hat in den vergangenen Jahren eine erhebliche Dynamik entwickelt, gefördert durch gestiegene Möglichkeiten der (explorativen) Analyse großer Datenmengen und parallel durch die zunehmende Verfügbarkeit bislang für die Wissenschaft nicht zugänglicher Datenkörper.

Ziel der Arbeit

Der nächste Entwicklungsschritt der RWD-Analyse ist ihre wissenschaftliche Etablierung in Form von Netzwerkbildung und formeller Organisation sowie Generierung spezifischer Methoden. Auf diesem Weg können Erfahrungen aus der Entwicklung der Sekundärdatenanalyse als Teil der RWD-Analyse hilfreich sein. Es wird diskutiert, inwieweit maßgebliche Schritte in diesem Prozess und dabei entstandene wissenschaftliche Produkte als Vorbild für die RWD-Analyse dienen können, exemplarisch dargestellt an den Aktivitäten der Arbeitsgruppe Erhebung und Nutzung von Sekundärdaten (AGENS).

Material und Methoden

Aus maßgeblichen Entwicklungsphasen der AGENS in den vergangenen 25 Jahren werden potenzielle Prozesse und Strukturen für eine Fortentwicklung der RWD-Analyse abgeleitet.

Ergebnisse

Die wesentlichen Charakteristika der aktuellen Arbeit der AGENS und damit auch der Strukturen der Sekundärdatenanalyse sind: a) Netzwerkbildung von Wissenschaftler:innen aus Forschung und Entwicklung sowie Vertreter:innen der Dateneigner:innen, b) Entwicklung spezifischer wissenschaftlicher Standards, c) die wissenschaftliche Sichtbarkeit durch Schwerpunktbeiträge, Journale und Tagungsformate, d) eigenständige Angebote für Aus- und Weiterbildung von Nachwuchswissenschaftler:innen, e) die laufende Verbesserung des Forschungsfelds durch Erschließung neuer Datenkörper.

Schlussfolgerung

Die Entwicklung der Sekundärdatenanalyse als wichtiger Teil der RWD-Analyse liefert Ansatzpunkte für deren Etablierung als eigenständiger Wissenschaftszweig.

Record linkage of claims and cancer registries data-Evaluation of a deterministic linkage approach based on indirect personal identifiers

PURPOSE

In Germany, record linkage of claims and cancer registry data is cost- and time-consuming, since up until recently no unique personal identifier was available in both data sources. The aim of this study was to evaluate the feasibility and performance of a deterministic linkage procedure based on indirect personal identifiers included in the data sources.

METHODS

We identified users of glucose-lowering drugs with residence in four federal states in Northern and Southern Germany (Bavaria, Bremen, Hamburg, Lower Saxony) in the German Pharmacoepidemiological Research Database (GePaRD) and assessed colorectal and thyroid cancer cases. Cancer registries of the federal states selected all colorectal and thyroid cancer cases between 2004 and 2015. A deterministic linkage approach was performed based on indirect personal identifiers such as year of birth, sex, area of residence, type of cancer and an absolute difference between the dates of cancer diagnosis in both data sources of at most 90 days. Results were compared to a probabilistic linkage using "direct" personal identifiers (gold standard).

RESULTS

The deterministic linkage procedure yielded a sensitivity of 71.8% for colorectal cancer and 66.6% for thyroid cancer. For thyroid cancer, the sensitivity improved when using only inpatient diagnosis to define cancer in GePaRD (71.4%). Specificity was always above 99%. Using the probabilistic linkage to define cancer cases, the risk for colorectal cancer was estimated 10 percentage points lower than when using the deterministic approach.

CONCLUSIONS

Sensitivity of the deterministic linkage approach appears to be too low to be considered as reasonable alternative to the probabilistic linkage procedure.

[Sustainable Infrastructure for Health Services Research: Development of a Regional SHI Routine Database]

AIM

The scientific use of SHI routine data is increasing, especially in the field of health services research. This also raises new questions with regard to the development of databases, which make it possible to store these data for longitudinal analyses over a longer period of time and by combining data from different SHI companies. On the basis of the experience gained in setting up the CoRe-Net database, we want to show that it is possible to install such a research infrastructure and make it usable in the long term.

METHODOLOGY/RESULTS

On the basis of the current regulatory framework (e. g. the added specification of § 75 SGB X) and taking into account strict data protection criteria, it is possible to set up a database covering several health insurance funds: In CoRe-Net, a pseudonymisation centre and a trust centre were implemented for this purpose. At the same time, multiple pseudonymisation was carried out using a one-way hash procedure. Data analysis are only possible after approval by the participating health insurance funds and if valid approval has been obtained from relevant ethics committees.

CONCLUSION

The amendment of § 75 SGB X in 2018 creates a legal framework for the collection and storage of SHI routine data within the framework of a research project for future questions within a defined research area.

Good Practice Data Linkage (GPD): A Translation of the German Version

The data linkage of different data sources for research purposes is being increasingly used in recent years. However, generally accepted methodological guidance is missing. The aim of this article is to provide methodological guidelines and recommendations for research projects that have been consented to across different German research societies. Another aim is to endow readers with a checklist for the critical appraisal of research proposals and articles. This Good Practice Data Linkage (GPD) was already published in German in 2019, but the aspects mentioned can easily be transferred to an international context, especially for other European Union (EU) member states. Therefore, it is now also published in English. Since 2016, an expert panel of members of different German scientific societies have worked together and developed seven guidelines with a total of 27 practical recommendations. These recommendations include (1) the research objectives, research questions, data sources, and resources; (2) the data infrastructure and data flow; (3) data protection; (4) ethics; (5) the key variables and linkage methods; (6) data validation/quality assurance; and (7) the long-term use of data for questions still to be determined. The authors provide a rationale for each recommendation. Future revisions will include new developments in science and updates of data privacy regulations.

[The investigation of health outcomes in the German National Cohort: the most relevant endpoints and their assessment]

The focus of the German National Cohort, the largest population-based cohort study in Germany to date, is the investigation of the most important widespread diseases, such as cardiovascular diseases, diabetes, cancer, neurological and psychiatric disorders, and frequent respiratory and infectious diseases. This cohort will answer questions on the development of these diseases and on the impact of genetic, environmental and lifestyle-related risk factors. Another focus is on the identification of early, subclinical markers of emerging diseases. To answer these questions, a comprehensive assessment of these health outcomes as well as of all potential determinants and precursors is mandatory.This paper describes the various health outcomes that are assessed in the German National Cohort, as well as the examination modules that are applied for deep phenotyping of study participants. Repeated collection of biosamples as well as functional measurements and application of modern imaging techniques at various time points allow for assessing the dynamics of physiological changes related to the individuals' health status. The prognostic value of these changes for disease development will be explored and translated to novel approaches for prevention and personalised medicine. Incident diseases are being assessed through self-reports by study participants and through record linkage with data from health insurances and cancer registries. Additional information about clinical diagnoses is obtained from the treating physicians to ensure the highest possible validity.

Individual Data Linkage of Survey Data with Claims Data in Germany-An Overview Based on a Cohort Study

Research based on health insurance data has a long tradition in Germany. By contrast, data linkage of survey data with such claims data is a relatively new field of research with high potential. Data linkage opens up new opportunities for analyses in the field of health services research and public health. Germany has comprehensive rules and regulations of data protection that have to be followed. Therefore, a written informed consent is needed for individual data linkage. Additionally, the health system is characterized by heterogeneity of health insurance. The lidA-living at work-study is a cohort study on work, age and health, which linked survey data with claims data of a large number of statutory health insurance data. All health insurance funds were contacted, of whom a written consent was given. This paper will give an overview of individual data linkage of survey data with German claims data on the example of the lidA-study results. The challenges and limitations of data linkage will be presented. Despite heterogeneity, such kind of studies is possible with a negligibly small influence of bias. The experience we gain in lidA will be shown and provide important insights for other studies focusing on data linkage.

[Linkage of large secondary and registry data sources with data of cohort studies : usage of a dual potential]

Cohort studies provide the best evidence of all epidemiological observational studies for the identification of causal relationships between risk factors and diseases. However, this design may lead to drawbacks that may affect the validity and reliability of the results. This follows in particular from systematic errors, such as selection bias or recall bias. One possibility to avoid or counteract some of these drawbacks is to link primary data from cohort studies with secondary and register data. The linkage of these data may also be used for mutual validations. Data that were previously linked with primary data within the context of cohort studies in Germany were obtained from statutory health insurances and pensions as well as data from the Federal Employment Agency and cancer registries. All these data have two features in common: First, they all cover detailed information about a large population and over a long period of time. Second, all sources are in principle able to provide data on an individual level such that an individual data linkage, e.g. with primary data, is possible. However, use and linkage of each of these data sources are restricted by several limitations. These have to be accounted for as well as numerous legal restrictions that exist in Germany to especially prevent the misuse of social data.