Individuals with Chronic Care Needs

Patient Intestinal Failure-ECHO Project (PIF-ECHO)

Description

This study will evaluate the feasibility and effectiveness of providing chronic intestinal failure patients and their family caregivers with direct access to live, virtual, multi-disciplinary (multi-D) support and education on best practices from a team of experts and peers. Such support can improve patient outcomes by enhancing knowledge, increasing confidence in self-care, and fostering a support network where patients can share lived experiences.

Grant Number
R03 HS030321
Principal Investigator(s)
Iyer, Kishore R.

Incorporating Patient-Reported Outcomes into Shared Decision Making with Patients with Osteoarthritis of the Knee - Final Report

Citation
Bozic K., Tsevat J. Incorporating Patient-Reported Outcomes into Shared Decision Making with Patients with Osteoarthritis of the Knee – Final Report. (Prepared by University of Texas - Austin under Grant No. R21 HS027037). Rockville, MD: Agency for Healthcare Research and Quality, 2024.
Principal Investigator
Bozic, Kevin John
Tsevat, Joel
Project Name
Incorporating Patient-Reported Outcomes into Shared Decision Making with Patients with Osteoarthritis of the Knee

Conducting internet-based visits for onboarding populations with limited digital literacy to an mHealth intervention: Development of a patient-centered approach.

Citation
Hernandez-Ramos R, Aguilera A, Garcia F, Miramontes-Gomez J, Pathak LE, Figueroa CA, Lyles CR. Conducting internet-based visits for onboarding populations with limited digital literacy to an mHealth intervention: Development of a patient-centered approach. JMIR Form Res. 2021 Apr 29;5(4):e25299. doi: 10.2196/25299. PMID: 33872184; PMCID: PMC8086779.
Principal Investigator
Aguilera, Adrian
Project Name
Improving Diabetes and Depression Self-Management Via Adaptive Mobile Messaging

Effectiveness of a digital health intervention leveraging reinforcement learning: Results from the Diabetes and Mental Health Adaptive Notification Tracking and Evaluation (DIAMANTE) randomized clinical trial.

Citation
Aguilera A, Arévalo Avalos M, Xu J, Chakraborty B, Figueroa C, Garcia F, Rosales K, Hernandez-Ramos R, Karr C, Williams J, Ochoa-Frongia L, Sarkar U, Yom-Tov E, Lyles C. Effectiveness of a Digital Health Intervention Leveraging Reinforcement Learning: Results From the Diabetes and Mental Health Adaptive Notification Tracking and Evaluation (DIAMANTE) Randomized Clinical Trial. J Med Internet Res. 2024 Oct 8;26:e60834. doi: 10.2196/60834. PMID: 39378080; PMCID: PMC11496924.
Principal Investigator
Aguilera, Adrian
Project Name
Improving Diabetes and Depression Self-Management Via Adaptive Mobile Messaging

Automated, machine learning-based alerts increase epilepsy surgery referrals: A randomized controlled trial.

Citation
Wissel BD, Greiner HM, Glauser TA, Mangano FT, Holland-Bouley KD, Zhang N, Szczesniak RD, Santel D, Pestian JP, Dexheimer JW. Automated, machine learning-based alerts increase epilepsy surgery referrals: A randomized controlled trial. Epilepsia. 2023 Jul;64(7):1791-1799. doi: 10.1111/epi.17629. Epub 2023 May 27. PMID: 37102995; PMCID: PMC10524622.
Principal Investigator
Dexheimer, Judith W.
Project Name
Optimal Methods for Notifying Clinicians About Epilepsy Surgery Patients

i-Matter: Investigating an mHealth Texting Tool for Embedding Patient-Reported Data into Diabetes Management - Final Report

Citation
Schoenthaler A., Mann D. i-Matter: Investigating an mHealth Texting Tool for Embedding Patient-Reported Data into Diabetes Management – Final Report. (Prepared by New York University School of Medicine under Grant No. R01 HS026522). Rockville, MD: Agency for Healthcare Research and Quality, 2023.
Principal Investigator
Schoenthaler, Antoinette
Mann, Devin M
Project Name
i-Matter: Investigating an mHealth Texting Tool for Embedding Patient-Reported Data into Diabetes Management