AHRQ Funded Projects
Search the entire portfolio of AHRQ-funded digital healthcare research projects. Projects can be identified by technology studied, medical condition, population, status of the project, principal investigator, organization, funding mechanism and location.
- Description: This research explores using natural language processing and generative AI to capture and structure social determinants of health from patient narratives, aiming to improve data completeness and quality, enhance clinical decision support, and reduce the manual burden on clinical staff in routine care.Principal Investigator: Goss, Foster R., Zhou, LiProject Dates: September 01, 2024 to August 31, 2026
- Description: This study will develop and establish the efficacy of an actionable predictive model to identify pregnant individuals at high risk for postpartum hemorrhage which can be used in combination with a clinical decision support tool to reduce the risk of hemorrhage-related morbidity and improve maternal health outcomes.Principal Investigator: Clapp, Mark A.Project Dates: August 01, 2024 to July 31, 2026
- Description: The study will create, implement, and test a patient-centric web app to support older adults with chronic conditions in comprehending, managing, and acting upon their lab test results.Principal Investigator: He, Zhe, Lustria, Mia Liza A.Project Dates: April 01, 2024 to March 31, 2029
- Description: This research will use deep learning models to move a reactive full capacity protocol (FCP) for emergency department (ED) overcrowding interventions into a proactive FCP by predicting patient flow measures so that interventions may be activated to avoid ED overcrowding.Principal Investigator: Ahmed, Abdulaziz, Ozaydin, BunyaminProject Dates: September 30, 2023 to September 29, 2028
- Description: This research will develop and validate a clinician-facing longitudinal risk-prediction tool using self-reported data from US military service members and veterans, to assist clinicians in screening, evaluation, and timely intervention in suicide ideation and suicide attempts.Principal Investigator: Chiu, Chung-Yi, Gao, XiaotianProject Dates: September 30, 2023 to September 29, 2025
- Description: This research will design, implement, and evaluate an emergency department triage machine learning algorithm, with an emphasis on predicted patient acuity and complexity, and incorporate it into a clinician-facing clinical decision support tool to promote safer, higher quality, and more equitable care.Principal Investigator: Sax, DanaProject Dates: September 30, 2023 to July 31, 2028
A Decision Support Tool for the Discontinuation of Disease Modifying Therapies in Multiple Sclerosis
Description: This research will develop, validate, and evaluate a decision support tool using a machine learning algorithm to standardize the approach to discontinuing disease-modifying therapies for multiple sclerosis.Principal Investigator: McGinley, MarisaProject Dates: August 01, 2023 to July 31, 2028- Description: This research will develop a SMART on FHIR version of an existing pneumonia clinical decision support tool and evaluate it in a new setting with a different electronic health record.Principal Investigator: Dean, Nathan C., Langlotz, Curtis P., Ward, Michael J.Project Dates: August 01, 2023 to July 31, 2026
- Description: This research will evaluate the safety, usability, diagnostic, and triage accuracy of a popular symptom checker app and new diagnostic algorithms, and their ability to affect patients’ decisions to seek care, particularly for transient ischemic attacks and stroke.Principal Investigator: Fraser, Hamish S.F.Project Dates: July 01, 2023 to May 31, 2028
- Description: This research will enhance, refine, and evaluate an artificial intelligence-supported tool that collects patient-reported outcomes to inform care and improve glycemic control for patients with poorly controlled diabetes.Principal Investigator: Schoenthaler, Antoinette, Mann, Devin MProject Dates: July 01, 2023 to May 31, 2028