Natural Language Processing System
How often do prescribers include indications in drug orders? Analysis of 4 million outpatient prescriptions.
Citation:
Salazar A, Karmiy SJ, Forsythe KJ, Amato MG, Wright A, Lai KH, Lambert BL, Liebovitz DM, Eguale T, Volk LA, Schiff GD. How often do prescribers include indications in drug orders? Analysis of 4 million outpatient prescriptions. Am J Health Syst Pharm. 2019 Jun 18;76(13):970-979. doi: 10.1093/ajhp/zxz082. PMID: 31361884.
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Exploration and initial development of text classification models to identify health information technology usability-related patient safety event reports.
Citation:
Fong A, Komolafe T, Adams KT, Cohen A, Howe JL, Ratwani RM. Exploration and initial development of text classification models to identify health information technology usability-related patient safety event reports. Appl Clin Inform. 2019 May;10(3):521-527. doi: 10.1055/s-0039-1693427. Epub 2019 Jul 17. PMID: 31315139.
Principal Investigator:
Detecting clinically relevant new information in clinical notes across specialties and settings.
Citation:
Zhang R, Pakhomov SVS, Arsoniadis EG, Lee JT, Wang Y, Melton GB. Detecting clinically relevant new information in clinical notes across specialties and settings. BMC Med Inform Decis Mak. 2017 Jul 5;17(Suppl 2):68. doi: 10.1186/s12911-017-0464-y. PMID: 28699564.
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Usability evaluation of NLP-PIER: a clinical document search engine for researchers.
Citation:
Hultman G, McEwan R, Pakhomov S, Lindemann E, Skube S, Melton GB. Usability evaluation of NLP-PIER: a clinical document search engine for researchers. Stud Health Technol Inform. 2017;245:1269. PMID: 29295354.
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Health Information Technology in Heart Failure Care - Final Report
Citation:
Blecker S. Health Information Technology in Heart Failure Care - Final Report. (Prepared by the New York University School of Medicine under Grant No. K08 HS023683). Rockville, MD: Agency for Healthcare Research and Quality, 2018.
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Encoding and Processing Patient Allergy Information in EHRs - Final Report
Citation:
Zhou L. Encoding and Processing Patient Allergy Information in EHRs - Final Report. (Prepared by Brigham and Women's Hospital under Grant No. R01 HS022728). Rockville, MD: Agency for Healthcare Research and Quality, 2018.
Principal Investigator:
Drug hypersensitivity reactions documented in electronic health records within a large health system.
Citation:
Wong A, Seger DL, Lai KH, et al. Drug hypersensitivity reactions documented in electronic health records within a large health system. J Allergy Clin Immunol Pract. 2018 Dec 1. pii:S2213-2198(18)30751-7. doi: 10.1016/j.jaip.2018.11.023. [Epub ahead of print]. PMID: 30513361.
Principal Investigator:
Identifying electronic health record usability and safety challenges in pediatric settings.
Citation:
Ratwani RM, Savage E, Will A, et al. Identifying Electronic Health Record Usability And Safety Challenges In Pediatric Settings. Health Aff (Millwood). 2018 Nov;37(11):1752-1759. PMID: 30395517.
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Automated extraction of diagnostic criteria from electronic health records for autism spectrum disorders: development, evaluation, and application.
Citation:
Leroy G, Gu Y, Pettygrove S, et al. Automated extraction of diagnostic criteria from electronic health records for autism spectrum disorders: development, evaluation, and application. J Med Internet Res. 2018 Nov 7;20(11):e10497. PMID: 30404767.
Principal Investigator:
Natural Language Processing to Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department - Final Report
Citation:
Goss F. Natural Language Processing to Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department - Final Report. (Prepared by the University of Colorado under Grant No. R21 HS024541). Rockville, MD: Agency for Healthcare Research and Quality, 2018.
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