Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
Authors: Brouwer WP, Zhao Q, Hansen BE, Lau D, Khalili M, Terrault NA, Di Bisceglie AM, Perrillo RP, Fried MW, Wong D, Feld JJ, Belle SH, Janssen HLA
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
Authors: Breskin A, Westreich D, Hurt CB, Cole SR, Hudgens MG, Seaberg EC, Thio CL, Tien PC, Adimora AA
Nature medicine
Authors: Hannun AY, Rajpurkar P, Haghpanahi M, Tison GH, Bourn C, Turakhia MP, Ng AY
Nature microbiology
Authors: Peters JM, Koo BM, Patino R, Heussler GE, Hearne CC, Qu J, Inclan YF, Hawkins JS, Lu CHS, Silvis MR, Harden MM, Osadnik H, Peters JE, Engel JN, Dutton RJ, Grossman AD, Gross CA, Rosenberg OS
Journal of pain and symptom management
Authors: Wallhagen MI, Ritchie CS, Smith AK
Blood
Authors: Kwon HS, Logan AC, Chhabra A, Pang WW, Czechowicz A, Tate K, Le A, Poyser J, Hollis R, Kelly BV, Kohn DB, Weissman IL, Prohaska SS, Shizuru JA
Volume 2 of Issue 1 | JAMIA Open
Authors: Glicksberg BS, Oskotsky B, Giangreco N, Thangaraj PM, Rudrapatna V, Datta D, Frazier R, Lee N, Larsen R, Tatonetti NP, Butte AJ
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 Out-comes 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).
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PloS one
Authors: Chen M, Carmella SG, Sipe C, Jensen J, Luo X, Le CT, Murphy SE, Benowitz NL, McClernon FJ, Vandrey R, Allen SS, Denlinger-Apte R, Cinciripini PM, Strasser AA, al'Absi M, Robinson JD, Donny EC, Hatsukami D, Hecht SS
The oncologist
Authors: Dasari A, Bergsland EK, Benson AB, Cai B, Huynh L, Totev T, Shea J, Duh MS, Neary MP, Dagohoy CG, Shih BE, Maurer VE, Chan J, Kulke MH
Journal of neurovirology
Authors: Pulliam L, Sun B, Mustapic M, Chawla S, Kapogiannis D
