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AHRQ-Funded Projects
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Optimal Methods for Notifying Clinicians About Epilepsy Surgery Patients
This project will integrate an existing Natural Language Processing system into neurology clinical practice and develop a decision support mechanism to alert providers about patients with epilepsy who are potential surgical candidates with the goal to shorten the time to surgical evaluation for eligible patients.
Natural Language Processing To Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department
This project will develop a natural language processing search tool that will automatically identify and rank relevant clinical information in an electronic health record based on a patient’s presenting complaint.
Developing Evidence-Based, User-Centered Design and Implementation Guidelines to Improve Health Information Technology Usability
This project will provide an evidence base to better inform user-centered design and implementation processes to improve health information technology, usability, and safety.
NLP to Improve Accuracy and Quality of Dictated Medical Documents
This project will study the impact of errors in medical documents on quality of care and develop innovative natural language processing methods to automatically detect errors so that physicians can correct the documents before finalizing them in the electronic health record.
Improving Accuracy of Electronic Notes Using a Faster, Simpler Approach
This project aims to refine, use, and evaluate a new method for creating electronic physician notes in the electronic medical record that improves accuracy and timely availability of inpatient progress notes.
Health Information Technology in Heart Failure Care
This project will develop and test a clinical decision support tool to support the delivery of recommended care in hospitalized patients who have heart failure, regardless of the reason for hospitalization.
NLP-enabled Decision Support for Cervical Cancer Screening and Surveillance
This project will create a natural language processing-enabled clinical decision support system to pull patient information from an electronic health record to determine optimal recommendations for screening and surveillance for cervical cancer.
Phenotype Modeling and Outcome Mapping for Pain Management Decision Support
This project will explore whether the use of data from pain management practices can be used to develop more robust evidence-based approaches to chronic pain management.
Encoding and Processing Patient Allergy Information in EHRs
This project will develop and evaluate a natural language processing (NLP) system for allergy information and then assess its ability to enrich allergy terminology standards and improve patients’ allergy lists.
Integration of an NLP-based Application to Support Medication Management
The overall goal of this study was to develop and assess a natural language processing application to facilitate medication reconciliation at the point of care.
