Abstract

BackgroundThe ability to apply standard and interoperable solutions for implementing and managing medical registries as well as aggregate, reproduce, and access data sets from legacy formats and platforms to advanced standard formats and operating systems are crucial for both clinical healthcare and biomedical research settings.PurposeOur study describes a reproducible, highly scalable, standard framework for a device registry implementation addressing both local data quality components and global linking problems.Methods and ResultsWe developed a device registry framework involving the following steps: (1) Data standards definition and representation of the research workflow, (2) Development of electronic case report forms using REDCap (Research Electronic Data Capture), (3) Data collection according to the clinical research workflow and, (4) Data augmentation by enriching the registry database with local electronic health records, governmental database and linked open data collections, (5) Data quality control and (6) Data dissemination through the registry Web site. Our registry adopted all applicable standardized data elements proposed by American College Cardiology / American Heart Association Clinical Data Standards, as well as variables derived from cardiac devices randomized trials and Clinical Data Interchange Standards Consortium. Local interoperability was performed between REDCap and data derived from Electronic Health Record system. The original data set was also augmented by incorporating the reimbursed values paid by the Brazilian government during a hospitalization for pacemaker implantation. By linking our registry to the open data collection repository Linked Clinical Trials (LinkedCT) we found 130 clinical trials which are potentially correlated with our pacemaker registry.ConclusionThis study demonstrates how standard and reproducible solutions can be applied in the implementation of medical registries to constitute a re-usable framework. Such approach has the potential to facilitate data integration between healthcare and research settings, also being a useful framework to be used in other biomedical registries.

Highlights

  • Over the past few years, the worldwide volume of healthcare and clinical research data generated has been significantly expanded [1,2,3]

  • These include missing data and poor data quality, which is related to how the research component of the registry is connected to clinical workflow and how personnel involved in the data collection are trained [4]

  • All clinical data stored will maintain full patient confidentiality according to Good Clinical Practices (GCP) and the Health Insurance Portability and Accountability Act (HIPAA) [25] and will be freely available to allow collaboration between researchers around the world

Read more

Summary

Introduction

Over the past few years, the worldwide volume of healthcare and clinical research data generated has been significantly expanded [1,2,3]. Despite its huge potential for both biomedical research as well as the potential to positively affect clinical practice and healthcare policies, medical registries are frequently surrounded by process problems that substantially decrease their value [4,15,16]. These include missing data and poor data quality, which is related to how the research component of the registry is connected to clinical workflow and how personnel involved in the data collection are trained [4]. The ability to apply standard and interoperable solutions for implementing and managing medical registries as well as aggregate, reproduce, and access data sets from legacy formats and platforms to advanced standard formats and operating systems are crucial for both clinical healthcare and biomedical research settings.

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call