i-Matter: Investigating an mHealth Texting Tool for Embedding Patient-Reported Data into Diabetes Management
Project Final Report (PDF, 916.17 KB) Disclaimer
The findings and conclusions in this document are those of the author(s), who are responsible for its content, and do not necessarily represent the views of AHRQ. No statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.
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Implementing an artificial intelligence–supported tool to collect patient-reported outcomes for patients with diabetes is expected to enable efficient delivery of high-quality patient-centered care and improve clinical outcomes.
Project Details -
Completed
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Grant NumberR01 HS026522
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Funding Mechanism(s)
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AHRQ Funded Amount$1,911,739
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Principal Investigator(s)
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Organization
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LocationNew York CityNew York
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Project Dates09/01/2018 - 06/30/2023
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Care Setting
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Medical Condition
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Type of Care
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Health Care Theme
Uncontrolled type 2 diabetes (T2D) is a significant cause of morbidity and mortality, particularly in vulnerable populations who continue to suffer disproportionately higher rates of diabetes complications. Despite the significant physical and psychosocial impact T2D has on patients’ behavioral, functional, and clinical outcomes, clinical practice often neglects patients’ perspectives of their T2D. There is a need to make patient-reported data actionable and meaningful to patients and providers alike. Integrating health information technology solutions such as mobile phones and electronic health records (EHRs) with evidence-based practices could create a seamless tool to support patients and enable efficient delivery of high-quality patient-centered care in primary care settings.
This project will evaluate the efficacy of a technology-based patient-reported outcome (PRO) system, the Modern Journal System for management of T2D (MJS DIABETES). MJS DIABETES is an innovative mobile platform that utilizes text-messaging to capture PRO data in real time, enhances patient engagement through data-driven feedback and motivational messages, and creates dynamic data visualizations of the PRO data that can be shared with providers through printed reports and integrated into the EHR.
The specific aims of the project are as follows:
- To compare the efficacy of MJS DIABETES versus usual care on hemoglobin A1c (HbA1c) reduction at 12 months.
- To compare the efficacy of MJS DIABETES versus usual care on adherence to self-care behaviors.
- To evaluate the potential mediators of the intervention effects, including diabetes knowledge, self-efficacy, outcome expectations, and patient-provider communication, on adherence to self-care behaviors and HbA1c reduction.
Patients will be randomized to an intervention arm or to usual care. Researchers hypothesize that at 12 months patients randomized to the intervention group will exhibit a greater mean reduction in HbA1c; report higher rates of adherence to self-care behaviors; and report greater improvement in diabetes knowledge, self-efficacy, and outcome expectation. They also hypothesize the intervention will lead to more collaborative patient-provider communication, which in turn will be associated with higher rates of adherence and higher mean reduction in HbA1c at 12 months.
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.
Link:
r01hs026522-schoenthaler-final-report-2023.pdf
(916.17 KB)
The findings and conclusions in this document are those of the author(s), who are responsible for its content, and do not necessarily represent the views of AHRQ. No statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.
Principal Investigator: Schoenthaler, Antoinette, Mann, Devin M
Project Name: i-Matter: Investigating an mHealth Texting Tool for Embedding Patient-Reported Data into Diabetes Management
Document Type: Report
Citation: Mandal S, Belli HM, Cruz J, Mann D, Schoenthaler A. Analyzing user engagement within a patient-reported outcomes texting tool for diabetes management: Engagement phenotype study. JMIR Diabetes. 2022 Nov 14;7(4):e41140. doi: 10.2196/41140. PMID: 36374531; PMCID: PMC9706388.
Principal Investigator: Schoenthaler, Antoinette
Project Name: i-Matter: Investigating an mHealth Texting Tool for Embedding Patient-Reported Data into Diabetes Management
Document Type: Journal Publication
Research Method: Quantitative, Randomized Controlled Trial (RCT)
Technology: Mobile Phone, Text Messaging
Citation: Schoenthaler A, Cruz J, Payano L, Rosado M, Labbe K, Johnson C, Gonzalez J, Patxot M, Patel S, Leven E, Mann D. Investigation of a mobile health texting tool for embedding patient-reported data into diabetes management (i-Matter): Development and usability study. JMIR Form Res. 2020 Aug 31;4(8):e18554. doi: 10.2196/18554. PMID: 32865505; PMCID: PMC7490676.
Principal Investigator: Schoenthaler, Antoinette, Mann, Devin M
Project Name: i-Matter: Investigating an mHealth Texting Tool for Embedding Patient-Reported Data into Diabetes Management
Document Type: Journal Publication
Research Method: Interview, Qualitative
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