Natural Language Processing System

Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery.

Citation: 
Wissel BD, Greiner HM, Glauser TA, Holland-Bouley KD, Mangano FT, Santel D, Faist R, Zhang N, Pestian JP, Szczesniak RD, Dexheimer JW. Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery. Epilepsia. 2019 Nov 29. doi: 10.1111/epi.16398. [Epub ahead of print]. PMID: 31784992.
Principal Investigator: 
Dexheimer, Judith W.
Project Name: 
Optimal Methods for Notifying Clinicians About Epilepsy Surgery Patients

Investigation of bias in an epilepsy machine learning algorithm trained on physician notes.

Citation: 
Wissel BD, Greiner HM, Glauser TA, Mangano FT, Santel D, Pestian JP, Szczesniak RD, Dexheimer JW. Investigation of bias in an epilepsy machine learning algorithm trained on physician notes. Epilepsia. 2019 Sep;60(9):e93-e98. doi: 10.1111/epi.16320. Epub 2019 Aug 23. PMID: 31441044.
Principal Investigator: 
Dexheimer, Judith W.
Project Name: 
Optimal Methods for Notifying Clinicians About Epilepsy Surgery Patients

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.
Principal Investigator: 
Schiff, Gordon David
Project Name: 
Enhancing Medication CPOE Safety and Quality by Indications-Based Prescribing

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: 
Ratwani, Raj M.
Project Name: 
Developing Evidence-Based, User-Centered Design and Implementation Guidelines to Improve Health Information Technology Usability

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.
Principal Investigator: 
Melton-Meaux, Genevieve
Project Name: 
Discovery and Visualization of New Information from Clinical Reports in the Electronic Health Record

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.
Principal Investigator: 
Melton-Meaux, Genevieve
Project Name: 
Discovery and Visualization of New Information from Clinical Reports in the Electronic Health Record

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.
Principal Investigator: 
Blecker, Saul B.
Project Name: 
Health Information Technology in Heart Failure Care

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: 
Zhou, Li
Project Name: 
Encoding and Processing Patient Allergy Information in EHRs

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: 
Zhou, Li
Project Name: 
Encoding and Processing Patient Allergy Information in EHRs

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.
Principal Investigator: 
Ratwani, Raj M.
Project Name: 
Developing Evidence-Based, User-Centered Design and Implementation Guidelines to Improve Health Information Technology Usability