Reclaiming registries for integrated evidence generation throughout the product life cycle
Integrated Evidence Generation
Integrated evidence generation (IEG) is a framework for generating evidence to support decision-making in healthcare. IEG leverages an ensemble of existing real-world data sources and new data collection to generate evidence that is ‘fit-for-purpose’[i], meaning that the real-world data (RWD) and the evidence that will be generated from it will meet the evidentiary standard for the intended use case. A regulatory use case may have a different expectation for the rigor of the processes underlying IEG than a peer-reviewed research publication. For example, one may find that existing real-world data from electronic medical records (EMRs) and medical claims is sufficient to perform a retrospective analysis to answer a research question. However, if that analysis requires data elements not routinely collected in real-world practice, such as clinician or patient-reported outcomes, biomarkers or medical device identifiers, then ancillary data collection will be required to meet the purpose. Further, if the intent of IEG is to submit data for regulatory purposes, such as for an external control arm for a clinical trial or to meet a post-marketing commitment, then that evidence generation will need to meet additional requirements such as transparency of processes, traceability of data elements, compliance of data collection systems and auditability of data sources.[ii] Similar requirements may also become applicable for the collection and validation of outcomes for programs under the Inflation Reduction Act of 2022.
Patient Registries
In the widely used and cited Agency for Healthcare Research and Quality (AHRQ) handbook, “Registries for Evaluating Patient Outcomes: A User’s Guide”, a registry is defined as ‘an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes.’[iii] Traditionally, registries have been a critical tool for evaluating outcomes when interventional approaches were not practical or where complementary real-world or post-approval data was needed. Registries provide critical data that is useful throughout the product life cycle, from understanding the natural history of diseases to evaluating the safety, effectiveness and value of treatments. In current published FDA guidance on RWE, registries are increasingly prominent, including one document devoted entirely to the topic.[iv]
Yet, in recent years, registries have become less popular because they have been gradually overengineered to mimic clinical trials with similar data entry burden. These registries risk higher potential for bias in enrollment and become less reflective of the real-world they are intended to represent.
Registry Automation
Automation is emerging as the key to reclaiming the value of registries in IEG. A registry can be broken down into data collection that needs to be active, meaning collected specifically for the intended purpose because it does not exist in clinical records, and passive, meaning that data can be extracted from contemporaneous real-world sources such as EMRs and other systems. By leveraging automation, active data collection can be limited to the minimum data necessary, resulting in simpler registries from the provider and patient perspectives. However, these registries are far richer because they combine active data with EMR, claims, mortality, social determinants and other relevant data sources for the same patients. Further, these automated registries can meet the requirements for regulatory submission of data.
As an example, running more than seven years, a sponsored registry on the OM1 Aspen automation platform has enrolled more than 1 million patients, demonstrated comparative outcomes and value, including identifying healthcare access disparities.[v]
Conclusion
Manufacturers are beginning to recognize the benefits of an IEG strategy for most products in development through commercialization. As the bar is raised for quality, so too will the role of new and compliant evidence generation. Automated registries with minimal burden will be an increasingly important part of those strategies.
[i] https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence
[iii] Gliklich RE, Leavy MB, Dreyer NA, editors. Registries for Evaluating Patient Outcomes: A User’s Guide [Internet]. 4th edition. Rockville (MD): Agency for Healthcare Research and Quality (US); 2020 Sep. Chapter 1, Patient Registries. Available from: https://www.ncbi.nlm.nih.gov/books/NBK562581/
[v] https://pubs.rsna.org/doi/abs/10.1148/radiol.221571?journalCode=radiology
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