Generalizable EHR-R-REDCap pipeline for a national multi-institutional rare tumor patient registry

Abstract

Objective To develop a clinical informatics pipeline designed to capture large-scale structured Electronic Health Record (EHR) data for a national patient registry. Materials and Methods The EHR-R-REDCap pipeline is implemented using R statistical software to remap and import structured EHR data into the Research Electronic Data Capture (REDCap)-based multi-institutional Merkel Cell Carcinoma (MCC) Patient Registry using an adaptable data dictionary. Results Clinical laboratory data were extracted from EPIC Clarity across several participating institutions. Laboratory values (Labs) were transformed, remapped, and imported into the MCC registry using the EHR labs abstraction (eLAB) pipeline. Forty-nine clinical tests encompassing 482 450 results were imported into the registry for 1109 enrolled MCC patients. Data-quality assessment revealed highly accurate, valid labs. Univariate modeling was performed for labs at baseline on overall survival (N = 176) using this clinical informatics pipeline. Conclusion We demonstrate feasibility of the facile eLAB workflow. EHR data are successfully transformed and bulk-loaded/imported into a REDCap-based national registry to execute real-world data analysis and interoperability.

The Smart Data Extractor, a Clinician Friendly Solution to Accelerate and Improve the Data Collection During Clinical Trials

“…proposed a pipeline to capture structured clinical data to a REDCap based registry. [9] Miller and al. provide a powerful application to abstract clinico-genomic data from EHR but this extraction solutions are limited to a predefined sets of data.…”

StoryboardR: an R package and Shiny application designed to visualize real-world data from clinical patient registries

“…StoryboardR is an R package with a Shiny application front-end that produces an interactive data visualization of patient-level data. When built around a core data capture system such as a cancer registry, R-based packages like GENETEX, 17 eLAB, 18 BodyMapR, 19 and StoryboardR can combine to form a powerful data informatics ecosystem to both augment data abstraction as well as facilitate data analysis with the goal of accelerating time-to-action for patients with rare tumors.…”

Developing Sentinel Surveillance for Chlamydia and Gonorrhea Using Test Results From Routine Screening During Pregnancy

“…EPIC is a widely used EHR in the United States, and the Clarity database has been used to collect data and improve patient care across multiple medical institutions. 25 Because of universality of the code, the SQL procedure we used for this analysis could be applied to other EHR databases to link data from multiple institutions. 20 (Appendix, http://links.lww.com/OLQ/A864) We expect our query code can be used by other organizations using EPIC EHR Stork Assuring accurate data collection from EHRs is important.…”

“…Electronic health records have largely replaced paper medical records in the American health care system 19 and can be used to monitor disease within a population as we have demonstrated in this analysis. EPIC is a widely used EHR in the United States, and the Clarity database has been used to collect data and improve patient care across multiple medical institutions 25 . Because of universality of the code, the SQL procedure we used for this analysis could be applied to other EHR databases to link data from multiple institutions 20 .…”