8. Data sources for pharmacoepidemiological research

The term registry is defined both as recording or registering and as the record or entry itself. In epidemiology it designates the data concerning all cases of a particular disease or similar health relevant condition in a defined population so that the cases can be related to a population base. Features of a well-designed registry focus on system specifications in order to ensure continuous, efficient and collaborative data collection, safe data hosting and availability of retrievable, interoperable and re-usable data.

Registries can be used as a source of participants for studies based on either primary data collection (where the items of interest for the study are collected directly from the patients, caregivers, healthcare professionals) or secondary use of data already collected (e.g., analogous to the use of electronic healthcare records). For this purpose, registry data can be complemented with additional information on outcomes, lifestyle data, immunisation or mortality information obtained from linkage to existing databases such as national disease registries, prescription databases or mortality records. A registry-based study often uses a patient registry (see below) for patient recruitment and data collection.

Registries are further useful for:

• improvement of patient management and record-keeping
• evaluation and planning of healthcare services
• insights into risk factors for adverse outcomes
• documentation of the effectiveness of therapies in real-world settings
• provision of insight into the nature of diseases and benefit of treatments in subgroups of patients
• and provision of comparative benchmark reports to a variety of stakeholders.

When utilizing existing registries in pharmacoepidemiology research, it is important to observe the following factors which affect the value and validity of registries and databases: (1) the comprehensiveness of registration of all individuals under study and the registered data, (2) the size of the data source, (3) the registration period in order to relate the exposure and effect to possible induction and latent periods, (4) data availability, accessibility, and expenses, (5) data format, and (6) the possibilities of linkage with other data sources. The validity may also vary between different settings, and validation studies are therefore essential when using registries as a data source.

Sørensen, H.T., Johnsen, S.P., Nørgård, B., 2009. Methodological issues in using prescription and other databases in pharmacoepidemiology. Norsk Epidemiol. 11 https://www.researchgate.net/publication/41758414_Methodological_issues_in_using_prescription_and_other_databases_in_pharmacoepidemiology

Types of registries

Different types of registries exist, some are listed below:

Clinical registries gather a defined minimum dataset from individuals undergoing a particular procedure, diagnosed with a disease or utilizing any healthcare resource, and capture data systematically from existing administrative databases, medical records or directly from clinical staff using data collection forms (Hoque et al., 2016).

Patient registries are often integrated into routine clinical practice with standardised, systematic and sometimes automated data capture in electronic health records, using observational methods for the recording of data on individual patients identified by a characteristic or an event, for example the diagnosis of a disease (disease registry), the occurrence of a condition (e.g., pregnancy registry), or a molecular or a genomic feature. They can provide a real-world view of clinical practice, medication safety, patient outcomes, and comparative effectiveness. They can be viewed as a collection of patient records on a particular subject.

Disease registries, as a special form of patient registry, contain data of patients who have or have had a disease or condition of interest. A disease registry is a tool used for tracking clinical care and outcomes of a defined patient population. Disease registries can also provide flexibility for collecting and reporting data from multiple data sources. Data collection can be facilitated either by merging with another data source such as administrative data, or by survey or interview methods.

Clinical quality registries (CQRs), initially coming from Sweden, they are described as clinical registries designed to improve the quality and safety of care. CQRs are defined as “An automated and structured collection of personal data initiated with the purpose to systematically and continuously develop and safeguard quality of care.”

Population registries, e.g., those in European Nordic countries, provide a comprehensive repository of data for a high proportion or all of the population allowing linkage between government-administered patient registries that may include hospital encounters, diagnoses and procedures, such as the Norwegian Patient Registry, the Danish National Patient Registry or the Swedish National Patient Register. They may however lack information on lifestyle factors, patient-related outcomes and laboratory data.

Special populations Registries Special populations can be identified based on specific characteristics, such as age (e.g., paediatric or elderly), pregnancy status, renal or hepatic function, race, or genetic differences. Some registries are focused on these particular populations; examples are:

• birth registries
• pregnancy registries (the Systematic overview of data sources for Drug Safety in pregnancy research for an inventory of pregnancy exposure registries)
• rare diseases registries (the European Platform on Rare Diseases Registration (EU RD Platform) for information on registries for rare diseases)
• the European network of registries for the epidemiologic surveillance of congenital anomalies (EUROCAT)
• paediatric registry (Pharmachild captures children with juvenile idiopathic arthritis undergoing treatment with methotrexate or biologic agents)
• Other registries that focus on special populations can be found in the ENCePP (European Network of Centres in Pharmacoepidemiology and Pharmacovigilance) Inventory of data sources.