Adapt and Incorporate dDPP Into Clinical Workflows

NCT04049500 | Withdrawn

• 1 other identifier: 19-00758
• Study Type: observational
• Target: N/A
• Locations: 0 countries
• Sites: N/A

Brief Summary

This observational study will seek to adapt a digital diabetes prevention program (dDPP) tool suite into clinical workflows. This tool pushes key dDPP data elements (e.g. weight and daily step count) directly into EHR workflows of primary care to enhance patient engagement. It seeks to determine the impact of combining adapted visualizations and summaries of key dDPP data elements directly into the EHR with automated notifications and messaging designed to enhance patient engagement in the dDPP. The study will involve provider workflow analysis based on observation and facilitated group tool adaptation sessions.

Conditions

Physician-Patient Relations; Nurse-Patient Relations

Keywords

Physicians; Nurses; Practice assistants; Health coaches; Population health managers; Patient navigators

Outcome Measures

Primary Outcomes (1)

• Usability will be assessed using a 5-point Likert scale

  5 point likert scale is measured on a 5 point scale, 1 being "very unsatisfied" and 5 being "very satisfied." Higher scores mean more usability

  12 Months

Study Arms (1)

Clinicians

Five practices will be selected from NYULH ambulatory practice sites to represent the spectrum of provider settings within the system. These sites will be the clinical partners for the adaptation of the dDPP tool suite

Other: Digital Diabetes Prevention Program (dDPP)

Interventions

Digital Diabetes Prevention Program (dDPP) OTHER

dDPP tool suite to integrate with the EHR and clinical workflows

Clinicians

Eligibility Criteria

• Age: 18 Years - 100 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Five practices will be selected from NYULH ambulatory practice sites to represent the spectrum of provider settings within the system. These sites will be the clinical partners for the adaptation of the dDPP tool suite.

You may qualify if:

• Physicians
• Nurses
• Practice assistants
• Health coaches
• Population health managers
• Patient navigators

You may not qualify if:

• Practices will be ineligible for participation if they treat fewer than 100 adults with prediabetes.

Sponsors & Collaborators

• NYU Langone Health: lead
• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK): collaborator

Related Publications (2)

• Rodriguez DV, Lawrence K, Gonzalez J, Brandfield-Harvey B, Xu L, Tasneem S, Levine DL, Mann D. Leveraging Generative AI Tools to Support the Development of Digital Solutions in Health Care Research: Case Study. JMIR Hum Factors. 2024 Mar 6;11:e52885. doi: 10.2196/52885.

  PMID: 38446539 DERIVED

• Lawrence K, Rodriguez DV, Feldthouse DM, Shelley D, Yu JL, Belli HM, Gonzalez J, Tasneem S, Fontaine J, Groom LL, Luu S, Wu Y, McTigue KM, Rockette-Wagner B, Mann DM. Effectiveness of an Integrated Engagement Support System to Facilitate Patient Use of Digital Diabetes Prevention Programs: Protocol for a Randomized Controlled Trial. JMIR Res Protoc. 2021 Feb 9;10(2):e26750. doi: 10.2196/26750.

  PMID: 33560240 DERIVED

Study Officials

• Devin Mann, MD

  NYU Langone

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 1, 2019
• First Posted: August 8, 2019
• Study Start: September 1, 2021
• Primary Completion (Estimated): September 1, 2026
• Study Completion (Estimated): September 1, 2026
• Last Updated: October 21, 2021

Record last verified: 2021-10

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP
• Time Frame: Beginning 9 months and ending 36 months following article publication or as required by a condition of awards and agreements supporting the research.
• Access Criteria: The investigator who proposed to use the data.