Digital versions of diabetes prevention programs (dDPPs) offer an exciting opportunity to bring evidence-based DPPs to scale across the nation. dDPPs have been validated, CDC-recognized, commercialized, modernized on ubiquitous mobile platforms and are increasingly reimbursable. Automated sharing of dDPP patient- generated health data with the primary care team is now possible. However, no empiric data are available to guide the meaningful integration of this new data source within electronic health records (EHRs) or clinical workflows to support patient engagement in the dDPP. Healthcare providers need concise, actionable data to replace the large amounts of clinical data presented in the EHR that is increasingly scattered, conflicted, and poorly filtered, threatening patient safety and provider satisfaction. Our team, which built the first dDPP used in primary care, recently developed and tested a novel system that links this digital behavior change program with an EHR to create an enhanced visualization tool. This tool pushes meaningful visualizations of key dDPP data elements (e.g. weight, activity, lesson completion) directly into the complex EHR workflows of primary care to enhance patient engagement. Based on this prior work, we now seek to determine the impact of implementing our enhanced visualization tool in combination with other widely available EHR messaging and notification functionality (dDPP-EHR tool suite) for diabetes prevention in real-world primary care practice. To achieve this goal we propose 3 aims: 1) to adapt our suite of digital patient monitoring and engagement tools that will integrate patient dDPP data into the EHR workflow; 2) to conduct a pragmatic, clustered RCT in 40 primary care practices to observe the suite?s impact on patient engagement, weight loss, physical activity, and HbA1C among prediabetic patients enrolled in the dDPP; and 3) to evaluate the implementation process guided by the Technology Acceptance Model (TAM3) and Proctor?s Implementation Outcomes Framework. The dDPP-EHR tool suite adaptation phase is guided by a user-centered design process consisting of group feedback sessions, workflow analyses and agile design to refine the suite?s integration into existing clinical workflows. The suite of tools and optimized workflows will be linked to the dDPP from a collaborating commercial dDPP provider (Noom, Inc). Each primary care practice will then be randomly assigned to have (or not have) access to the tool while patients (10 per practice) are recruited via patient portal to receive a dDPP prescription from their provider. The main outcomes will be weight loss, physical activity, HbA1C and dDPP engagement over the 1-year intervention.
Aim 3 will use a theory driven implementation assessment framework to assess the acceptability, adoption, cost, and sustainability of implementing the dDPP-EHR tool. We have assembled an experienced, multi-disciplinary team that includes a leading commercial digital diabetes prevention program provider to determine if connecting patients and providers through our novel dDPP-EHR tool suite has a measurable impact on diabetes prevention-related outcomes.

Public Health Relevance

Digital versions of evidence-based health behavior change programs for diabetes prevention (dDPPs) are increasingly available to patients with prediabetes. These new dDPPs exist in relative isolation from the primary care teams taking care of prediabetic patients. This study seeks to determine the impact of digitally connecting prediabetic patients using a dDPP with their providers through a novel combination of tools available in the electronic health record.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Demonstration and Dissemination Projects (R18)
Project #
1R18DK118545-01A1
Application #
9815834
Study Section
Special Emphasis Panel (ZDK1)
Program Officer
Burch, Henry B
Project Start
2019-09-15
Project End
2024-06-30
Budget Start
2019-09-15
Budget End
2020-06-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
New York University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
121911077
City
New York
State
NY
Country
United States
Zip Code
10016