Early comprehensive care of preterm infants - effects on quality of life, childhood development, and healthcare utilization: study protocol for a cohort study linking administrative healthcare data with patient reported primary data

Background About 9 % of all children in Germany are born preterm. Despite significant improvements of medical care, preterm infants are at a greater risk to develop short and long term health complications. Negative consequences of preterm birth include neurodevelopmental disabilities, behavioral problems or learning disorders. Most data on effects of prematurity are derived from single or multi-center studies and not population-based. Since some of the long term problems of preterm delivery are associated with a disturbed parent-child interaction originating in the neonatal period, several intervention programs became available aiming to strengthen the early parent-child relationship. However, there is insufficient knowledge regarding the psychosocial and socioeconomic impact of these interventions. Prior to introducing them into routine care, those effects have to be rigorously evaluated. The population-based cohort study EcoCare-PIn (Early comprehensive Care of Preterm Infants—effects on quality of life, childhood development, and healthcare utilization) will investigate the following primary research questions: 1) What are the short- and long-term consequences of preterm birth with regard to parental stress, parent-child relationship, childhood development, quality of life and healthcare utilization including costs? 2) Does early family-centered psychosocial care prevent the hypothesized negative consequences of preterm birth on the above mentioned outcomes? Methods/Design EcoCare-PIn examines the research questions by means of a linkage of a) pseudonymized administrative individual-level claims data from the German statutory health insurance AOK PLUS on approximately 140,000 children born between 2007 and 2013 in Saxony, and b) primary data collected from the parents/caregivers of all very low birth weight (<1,500 g; n = 1,000) and low birth weight infants (1,500 to 2,500 g; n = 5,500) and a matched sample of infants above 2,500 g birth weight (n = 10,000). Discussion In Saxony, approximately 50 % of all individuals are insured at the AOK PLUS. The linkage of patient-level administrative and primary data is a novel approach in neonatal research and probably the only way to overcome shortcomings of studies solely relying on one data source. The study results are based on an observation period of up to 8 years and will directly inform perinatal healthcare provision in Saxony and Germany as a whole

Gute Praxis Datenlinkage (GPD) : Good Practice Data Linkage

Das personenbezogene Verknüpfen verschiedener Datenquellen (Datenlinkage) für Forschungszwecke findet in den letzten Jahren in Deutschland zunehmend Anwendung. Jedoch fehlen hierfür konsentierte methodische Standards. Ziel dieses Beitrages ist es, solche Standards für Forschungsvorhaben zu definieren. Eine weitere Intention ist es, dem Lesenden eine Checkliste zur Bewertung geplanter Forschungsvorhaben und Artikel bereitzustellen. Zu diesem Zweck hat eine aus Mitgliedern verschiedener Fachgesellschaften zusammengesetzte Expertengruppe seit 2016 insgesamt 7 Leitlinien mit 27 konkreten Empfehlungen erstellt. Die Gute Praxis Datenlinkage beinhaltet die folgenden Leitlinien: (1) Forschungsziele, Fragestellung, Datenquellen und Ressourcen, (2) Dateninfrastruktur und Datenfluss, (3) Datenschutz, (4) Ethik, (5) Schlüsselvariablen und Linkageverfahren, (6) Datenprüfung/Qualitätssicherung sowie (7) Langfristige Datennutzung für noch festzulegende Fragestellungen. Jede Leitlinie wird ausführlich diskutiert. Zukünftige Aktualisierungen werden wissenschaftliche und datenschutzrechtliche Entwicklungen berücksichtigen

Framework and baseline examination of the German National Cohort (NAKO)

The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19–74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2–3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4–5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10654-022-00890-5

Die Basiserhebung der NAKO Gesundheitsstudie: Teilnahme an den Untersuchungsmodulen, Qualitätssicherung und Nutzung von Sekundärdaten

BACKGROUND: The German National Cohort (NAKO) is an interdisciplinary health study aimed at elucidating causes for common chronic diseases and detecting their preclinical stages. This article provides an overview of design, methods, participation in the examinations, and their quality assurance based on the midterm baseline dataset (MBD) of the recruitment. METHODS: More than 200,000 women and men aged 20–69 years derived from random samples of the German general population were recruited in 18 study centers (2014–2019). The data collection comprised physical examinations, standardized interviews and questionnaires, and the collection of biomedical samples for all participants (level 1). At least 20% of all participants received additional in-depth examinations (level 2), and 30,000 received whole-body magnet resonance imaging (MRI). Additional information will be collected through secondary data sources such as medical registries, health insurances, and pension funds. This overview is based on the MBD, which included 101,839 participants, of whom 11,371 received an MRI. RESULTS: The mean response proportion was 18%. The participation in the examinations was high with most of the modules performed by over 95%. Among MRI participants, 96% completed all 12 MRI sequences. More than 90% of the participants agreed to the use of complementary secondary and registry data. DISCUSSION: Individuals selected for the NAKO were willing to participate in all examinations despite the time-consuming program. The NAKO provides a central resource for population-based epidemiologic research and will contribute to developing innovative strategies for prevention, screening and prediction of chronic diseases.HINTERGRUND: Die NAKO Gesundheitsstudie ist ein bundesweites interdisziplinäres Forschungsvorhaben mit dem Ziel, die Ursachen für chronische Krankheiten und deren vorklinische Stadien zu untersuchen. Der Artikel gibt einen Überblick über das Studiendesign, die Methoden, die Teilnahme an den Untersuchungen und ihre Qualitätssicherung zur Halbzeit der Basiserhebung. METHODEN: Für die Basiserhebung wurden mehr als 200.000 Frauen und Männer im Alter von 20–69 Jahren aus Zufallsstichproben der Allgemeinbevölkerung in 18 Studienzentren rekrutiert (2014–2019). Die Basiserhebung beinhaltet Untersuchungen, Befragungen und Biomaterialien für alle Teilnehmerinnen und Teilnehmer (Level 1), ein erweitertes Programm für mindestens 20 % (Level 2) und eine Magnetresonanztomografie (MRT) für 30.000 Teilnehmerinnen und Teilnehmer. Sekundär- und Registerdaten werden über Krankheitsregister, Kranken- und Rentenversicherungen erhoben. Die Auswertung bezieht die Datenbasis zur Halbzeit der Basiserhebung mit 101.839 Teilnehmerinnen und Teilnehmern ein, davon 11.371 mit einer MRT-Untersuchung. ERGEBNISSE: Die mittlere Responsequote zur Halbzeit betrug insgesamt 18 %. Die Teilnahme an den Untersuchungen lag überwiegend bei mehr als 95 %. Bei 96 % der MRT-Teilnehmerinnen und Teilnehmer konnten alle 12 MRT-Sequenzen vollständig durchgeführt werden. Der Erschließung und wissenschaftlichen Nutzung ergänzender Sekundär- und Registerdaten stimmten mehr als 90 % der Teilnehmerinnen und Teilnehmer zu. DISKUSSION: Die Bereitschaft, möglichst alle Untersuchungsmodule durchzuführen, war trotz des zeitlichen Aufwandes außerordentlich hoch. Dadurch wird die NAKO zu einer zentralen Ressource für die epidemiologische Forschung in Deutschland. Sie wird es ermöglichen, neue Strategien zur Früherkennung, Vorhersage und Primärprävention chronischer Krankheiten zu entwickeln

Using administrative and claims data in the GNC-study – how to overcome legal restrictions

ABSTRACT Objectives The German GNC-Health Study (GNC) will have duration of at least ten years and will compile medical examinations, biomaterials and computer assisted interviews of intended 200.000 participants (funding code: 01ER1301A). For the first time, this data collection will be supplemented with a multitude of administrative and claims data such as data of statutory health insurance funds, statutory pension funds as well as the Federal Employment Agency. The GNC extends this field of research to private health insurance funds, epidemiologic and clinical cancer and mortality registers. This supplementary use of claims data is strictly regulated by legal requirements. The challenges and solutions for scientific use of such data in Germany will be described. Approach The Social Security Code and data protection rules govern the scientific use of administrative data. These rules include requirements for the wording of important documents such as informed consent, release from confidentiality, participants’ information, data protection concept etc. and often an authorization process by the supervisory authority of the data owner. These complex tasks, which are time consuming costly and labour intensive, are tied into the GNC-Competence Network for secondary and registry data (CNSRD). Results The GNC-CNSRD has helped to formulate legal informed consent for each data source, which describes the use of the information provided by the participants, as well as the period and limitation of its retro- and prospective use. Furthermore, only the GNC-trust agency is allowed to save the social security number but not the local study center. The modular consent process and the IT- and data protection concept of the GNC is a prototype to enable the large scale use of administrative and claims data of future epidemiologic studies in Germany. Conclusion Unfortunately, one of the biggest obstacles for the scientific use of administrative and claims data still remains unsolved. The application for data use at the local supervisory authority of the data owner requires the description and limitation of the research question and the period of use of this data. This is in conflict with the modern longitudinal design of GNC because it wants to establish a research structure and data base in order to answer a variety of future and unspecified research questions. Hence, current legal requirements in Germany prevent the full utilization of the potential of administrative and claims data. Therefore, the German Federal Commissioner for Data Protection and Freedom of Information recommended an amendment to the social law

What do We Mean by Secondary Data? - A Keynote Contribution to the Terminological Classification and Definition

Zusammenfassung Daten sind fur die Versorgungsforschung Material und Produkt zugleich. Als Substrat oder Ausgangsbasis von gesundheitsbezogenen Analysen haben sie in den vergangenen Dekaden immens an Bedeutung gewonnen. Fur die Beurteilung von Leistungen des Gesundheitssystems, fur dessen Steuerung und Entwicklung sind Daten ein essenzieller Rohstoff. Im wissenschaftlichen Alltag und in Forschungsarbeiten, die diesen Rohstoff nutzen, kommt der Bedeutungsgehalt des Begriffs Daten - insbesondere Sekundardaten - oft zu kurz. Der vorliegende Beitrag mochte den Bedeutungskontext der beiden Begriffe vertiefend beleuchten und den Versuch unternehmen, den Begriff Sekundardaten terminologisch einzuordnen. Abstract Data are both material and product for health services research. As a substrate or starting point for health-related analyses, they have gained immense importance in recent decades. Data are an essential raw material for the assessment of services in the health care system, for its control and development. In everyday scientific life and in research work that uses this raw material, the meaning of the term data - especially secondary data - is often neglected. This article aims to shed more light on the context of meaning of the two terms and to attempt to classify the term secondary data terminologically