Goss, Foster R.

Building the evidence-base to reduce electronic health record-related clinician burden.

Citation: 
Dymek C, Kim B, Melton GB, Payne TH, Singh H, Hsiao CJ. Building the evidence-base to reduce electronic health record-related clinician burden. J Am Med Inform Assoc. 2021 Apr 23;28(5):1057-1061. doi: 10.1093/jamia/ocaa238. PMID: 33340326; PMCID: PMC8068419.
Principal Investigator: 
Singh, Hardeep
Melton-Meaux, Genevieve
Payne, Thomas H.
Goss, Foster R.
Dymek, Chris
Project Name: 
Decision Making and Clinical Work of Test Result Followup in Health Information Technology Settings
Discovery and Visualization of New Information from Clinical Reports in the Electronic Health Record
Improving Accuracy of Electronic Notes Using a Faster, Simpler Approach
Natural Language Processing To Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department

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.
Principal Investigator: 
Goss, Foster R.
Project Name: 
Natural Language Processing To Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department

Natural Language Processing To Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department

Description: 

This project developed a natural language processing electronic health record search tool that automatically identifies and ranks relevant clinical information based on a patient’s presenting complaint within the emergency department setting.

Principal Investigator: 
Foster R. Goss
Project Dates: 
September 1, 2016 to August 31, 2018