ROMOP: a light-weight R package for interfacing with OMOP-formatted electronic health record data

Author:

Glicksberg Benjamin S1ORCID,Oskotsky Boris1,Giangreco Nicholas2,Thangaraj Phyllis M2,Rudrapatna Vivek1,Datta Debajyoti1,Frazier Remi3,Lee Nelson3,Larsen Rick3,Tatonetti Nicholas P2,Butte Atul J1

Affiliation:

1. Department of Pediatrics Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, California, USA

2. Departments of Biomedical Informatics, Systems Biology, and Medicine, Columbia University, New York, New York, USA

3. Academic Research Systems, Department of Enterprise Data Warehouse University of California San Francisco, San Francisco, California, USA

Abstract

Abstract Objectives Electronic health record (EHR) data are increasingly used for biomedical discoveries. The nature of the data, however, requires expertise in both data science and EHR structure. The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) standardizes the language and structure of EHR data to promote interoperability of EHR data for research. While the OMOP CDM is valuable and more attuned to research purposes, it still requires extensive domain knowledge to utilize effectively, potentially limiting more widespread adoption of EHR data for research and quality improvement. Materials and methods We have created ROMOP: an R package for direct interfacing with EHR data in the OMOP CDM format. Results ROMOP streamlines typical EHR-related data processes. Its functions include exploration of data types, extraction and summarization of patient clinical and demographic data, and patient searches using any CDM vocabulary concept. Conclusion ROMOP is freely available under the Massachusetts Institute of Technology (MIT) license and can be obtained from GitHub (http://github.com/BenGlicksberg/ROMOP). We detail instructions for setup and use in the Supplementary Materials. Additionally, we provide a public sandbox server containing synthesized clinical data for users to explore OMOP data and ROMOP (http://romop.ucsf.edu).

Funder

National Center for Advancing Translational Sciences, National Institutes of Health

Bakar Computational Health Sciences Institute

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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