Registries

Real world data can be accrued through prospective cohort studies and a registry is an established method for this type of study. A registry is a form of cohort study that

follows a large population of patients recruited with a specific disease and are used extensively to study the natural history of a condition, the predictors of key outcomes and effectiveness of treatments 234_{. The basic description of a registry is an}

observational, non-experimental database designed to reflect current patterns of practice without influencing the treatment or intervention being described 9_{. A treatment}

registry is designed to collect all cases of a particular disease or condition treated with a specified intervention or therapeutic class of drugs. The Agency for Healthcare Research and Quality defines a patient registry as ‘an organized system that uses

observational study methods to collect uniform data (clinical or other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical or policy purposes’ 226_{. A patient registry can be a powerful tool to observe the course of}

disease, to understand variations in treatment and outcomes, to examine factors that influence prognosis and quality of life, to describe care patterns including appropriateness of care and disparities in the delivery of care, to assess effectiveness, to monitor safety and harm and to measure quality of life 226_.

The potential for registries to collect real world data is considerable. A registry can address clinical questions on effectiveness, safety and compliance, information on disease and/or treatment-specific changes in qualify of life, and address regional and national variations in treatment patterns 9_{. Registry studies are often referred to as real}

world studies, to distinguish them from clinical trials 235_{. Many observational databases}

worldwide, most of which are electronic, were borne out of business process needs (e.g. claims databases); however, provider-led databases focusing on a specific disease and/or patient population have emerged 236_{. Database sources for}

mechanisms. Claims databases have the advantage of being large and capturing almost every interaction within the healthcare delivery system. However, because these data are used for claims and billing purposes, they lack detailed and complete clinical information. In addition, these databases make it difficult to differentiate between comorbid conditions and complications of care and they may only capture specific geographic markets or represent a subpopulation. On the other hand, clinical databases, although smaller, have the advantage of containing more detailed clinical data. However, their accuracy and completeness are dependent on the individual responsible for data entry 236_{. In general, databases are only as useful as the quality of}

the information that is collected, where the adage “bad data in, bad data out” applies.

The quality of the data and completeness can vary dependent on the source of data and assurance measures implemented. Missing, incorrectly coded and incomplete data can be problematic when developing an analytic dataset and the results are only valid if these problems are limited.

The importance of registries is increasingly recognised as they are used more frequently to fill important gaps in evidence and contribute to understanding how trial results can be applied in practice 235_{. Data from registries are also used to support}

timely decisions by regulatory agencies about safety. Information regarding patient characteristics, comorbidities, risk factors, treatment patterns and outcomes can be assessed. Observational registry data can be synergistic with RCTs for effectiveness evidence development 237_{. Alternatively, these data can be used to confirm the}

generalisability of RCT findings among a broader spectrum of patients and providers. Beyond consideration of therapeutic effectiveness and safety, registry data can also be used to assess the incremental healthcare costs associated with one treatment versus its comparator and can provide a broader and more accurate measure of true costs of treatment in real world practice 15, 236_.

Registries, claims-type databases and provider-led databases, offer the opportunity to provide insights into the outcomes and costs of existing and even new therapies by leveraging observational databases to inform decision-making. These registry datasets can address the effectiveness of therapies as they are used in practice, providing valuable insights into real world safety and costs 236_.

3.3.1 Classification of Patient Registries

The breadth of studies that can be included as patient registries is large. Patients included in a registry, are typically selected based on a particular disease, risk factor or exposure. Three general categories account for the majority of registries developed for evaluating patient outcomes. These include observational studies in which the patient has an exposure to a product or service, has a particular disease or risk factor or various combinations thereof 226_.

3.3.1.1 Product Registries

In this type of registry, the patient is exposed to a healthcare product, a drug or a medical device. Exposure may be brief (i.e. single dose) or may be for long-term use. They provide a mechanism for monitoring the long-term safety and effectiveness in the ‘natural environment’ 238_.

3.3.1.2 Disease Registries

A disease registry is a patient registry that tracks outcomes in a population of patients who have the same diagnosis (e.g. HCV infection) or who have undergone the same medical procedures. They can be used to estimate disease prevalence and incidence, to estimate healthcare resource utilisation and clinical outcomes and to track changes in these parameters over time 239_{. They may also serve as data sources for conducting}

allow for estimations of the demand for health services and may serve as sampling frames for selecting patients who fulfil specific study eligibility criteria. The use of disease registries is particularly beneficial for diseases affecting very small populations and for looking at specific populations, such as children 240_.