Routinely collected health data, obtained for administrative and clinical purposes without specific a priori research goals, are increasingly used for research. The rapid evolution and availability of these data have revealed issues not addressed by existing reporting guidelines, such as Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). The REporting of studies Conducted using Observational Routinely collected health Data (RECORD) statement was created to fill these gaps. RECORD was created as an extension to the STROBE statement to address reporting items specific to observational studies using routinely collected health data. RECORD consists of a checklist of 13 items related to the title, abstract, introduction, methods, results, and discussion section of articles, and other information required for inclusion in such research reports. This document contains the checklist and explanatory and elaboration information to enhance the use of the checklist. Examples of good reporting for each RECORD checklist item are also included herein. This document, as well as the accompanying website and message board (http://www.record-statement.org), will enhance the implementation and understanding of RECORD. Through implementation of RECORD, authors, journals editors, and peer reviewers can encourage transparency of research reporting.

Background: The Danish National Patient Registry (DNPR) is one of the world's oldest nationwide hospital registries and is used extensively for research. Many studies have validated algorithms for identifying health events in the DNPR, but the reports are fragmented and no overview exists. Objectives: To review the content, data quality, and research potential of the DNPR. Methods: We examined the setting, history, aims, content, and classification systems of the DNPR. We searched PubMed and the Danish Medical Journal to create a bibliography of validation studies. We included also studies that were referenced in retrieved papers or known to us beforehand. Methodological considerations related to DNPR data were reviewed. Results: During 1977–2012, the DNPR registered 8,085,603 persons, accounting for 7,268,857 inpatient, 5,953,405 outpatient, and 5,097,300 emergency department contacts. The DNPR provides nationwide longitudinal registration of detailed administrative and clinical data. It has recorded information on all patients discharged from Danish nonpsychiatric hospitals since 1977 and on psychiatric inpatients and emergency department and outpatient specialty clinic contacts since 1995. For each patient contact, one primary and optional secondary diagnoses are recorded according to the International Classification of Diseases. The DNPR provides a data source to identify diseases, examinations, certain in-hospital medical treatments, and surgical procedures. Long-term temporal trends in hospitalization and treatment rates can be studied. The positive predictive values of diseases and treatments vary widely (<15%–100%). The DNPR data are linkable at the patient level with data from other Danish administrative registries, clinical registries, randomized controlled trials, population surveys, and epidemiologic field studies – enabling researchers to reconstruct individual life and health trajectories for an entire population. Conclusion: The DNPR is a valuable tool for epidemiological research. However, both its strengths and limitations must be considered when interpreting research results, and continuous validation of its clinical data is essential.

Introduction: Individual-level data on all prescription drugs sold in Danish community pharmacies has since 1994 been recorded in the Register of Medicinal Products Statistics of the Danish Medicines Agency. Content: The register subset, termed the Danish National Prescription Registry (DNPR), contains information on dispensed prescriptions, including variables at the level of the drug user, the prescriber, and the pharmacy. Validity and coverage: Reimbursement-driven record keeping, with automated bar-code-based data entry provides data of high quality, including detailed information on the dispensed drug. Conclusion: The possibility of linkage with many other nationwide individual-level data sources renders the DNPR a very powerful pharmacoepidemiological tool.

Little is known about the prognosis of cancer discovered during or after an episode of venous thromboembolism.

Denmark has a large network of population-based medical databases, which routinely collect high-quality data as a by-product of health care provision. The Danish medical databases include administrative, health, and clinical quality databases. Understanding the full research potential of these data sources requires insight into the underlying health care system. This review describes key elements of the Danish health care system from planning and delivery to record generation. First, it presents the history of the health care system, its overall organization and financing. Second, it details delivery of primary, hospital, psychiatric, and elderly care. Third, the path from a health care contact to a database record is followed. Finally, an overview of the available data sources is presented. This review discusses the data quality of each type of medical database and describes the relative technical ease and cost-effectiveness of exact individual-level linkage among them. It is shown, from an epidemiological point of view, how Denmark's population represents an open dynamic cohort with complete long-term follow-up, censored only at emigration or death. It is concluded that Denmark's constellation of universal health care, long-standing routine registration of most health and life events, and the possibility of exact individual-level data linkage provides unlimited possibilities for epidemiological research.