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.
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: To assist pregnant individuals with pre-pregnancy type 2 diabetes with Medicaid coverage in reaching and maintaining normal blood sugars, this research will develop, test, and evaluate a digital health solution called ACHIEVE that includes a mobile health application, a provider dashboard, continuous glucose monitoring, and team-based coaching for medical needs and nonmedical health-related social needs.Principal Investigator: Fareed, Naleef, Joseph, Joshua J, Venkatesh, Kartik KailasProject Dates: September 30, 2022 to July 31, 2027
- Description: This research will adapt a pain management virtual reality application for use on a smartphone to manage pain during dressing changes in pediatric burn patients.Principal Investigator: Xiang, HenryProject Dates: September 30, 2022 to July 31, 2027
- Description: In this study, researchers employed and analyzed an artificial intelligence tool to improve the motivational interviewing capacities of health workers.Principal Investigator: Hershberger, Paul J.Project Dates: August 01, 2019 to July 31, 2022
- Description: This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.Principal Investigator: Dexheimer, Judith W.Project Dates: September 30, 2016 to September 29, 2018
- Description: This research applied machine learning to develop a model predicting surgical cancellations among pediatric patients, and found the feasibility in using these algorithms as a cost-effective quality-improvement measure.Principal Investigator: Pratap, JayantProject Dates: September 01, 2016 to August 31, 2019
- Description: This research explored the effectiveness of integrating behavioral tools into an evidence-based software to improve access to behavioral treatment strategies for children with attention deficit hyperactivity disorder.Principal Investigator: Epstein, Jeff N.Project Dates: July 01, 2016 to April 30, 2021
- Description: This study assessed the usability and impact of inpatient portals on patient experience, engagement, and perceptions of care.Principal Investigator: McAlearney, Ann ScheckProject Dates: September 30, 2015 to September 29, 2017
- Description: This project developed and tested a tablet-based decision aid to assist primary care providers in applying patient-reported outcomes to smoking cessation and found that the tool facilitated more conversations about smoking cessation between patients and providers.Principal Investigator: Tubb, Matthew RobertProject Dates: June 01, 2015 to November 30, 2017
- Description: This project tested a pediatric voice therapy telehealth system and found that it was feasible to implement and well accepted by children and their families.Principal Investigator: Kelchner, LisaProject Dates: September 30, 2012 to September 29, 2014