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  5. Open-source Web Portal for Managing Self-reported Data and Real-world Data Donation in Diabetes Research: Platform Feasibility Study
 
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Open-source Web Portal for Managing Self-reported Data and Real-world Data Donation in Diabetes Research: Platform Feasibility Study

Author(s)
Cooper, Drew  
Ubben, Tebbe  
Knoll, Christine  
Ballhausen, Hanne  
O'Donnell, Shane  
Braune, Katarina  
Lewis, Dana  
Uri
http://hdl.handle.net/10197/24368
Date Issued
2022-03-31
Date Available
2023-04-28T16:02:39Z
Abstract
Background: People with diabetes and their support networks have developed open-source automated insulin delivery systems to help manage their diabetes therapy, as well as to improve their quality of life and glycemic outcomes. Under the hashtag #WeAreNotWaiting, a wealth of knowledge and real-world data have been generated by users of these systems but have been left largely untapped by research; opportunities for such multimodal studies remain open. Objective: We aimed to evaluate the feasibility of several aspects of open-source automated insulin delivery systems including challenges related to data management and security across multiple disparate web-based platforms and challenges related to implementing follow-up studies. Methods: We developed a mixed methods study to collect questionnaire responses and anonymized diabetes data donated by participants-which included adults and children with diabetes and their partners or caregivers recruited through multiple diabetes online communities. We managed both front-end participant interactions and back-end data management with our web portal (called the Gateway). Participant questionnaire data from electronic data capture (REDCap) and personal device data aggregation (Open Humans) platforms were pseudonymously and securely linked and stored within a custom-built database that used both open-source and commercial software. Participants were later given the option to include their health care providers in the study to validate their questionnaire responses; the database architecture was designed specifically with this kind of extensibility in mind. Results: Of 1052 visitors to the study landing page, 930 participated and completed at least one questionnaire. After the implementation of health care professional validation of self-reported clinical outcomes to the study, an additional 164 individuals visited the landing page, with 142 completing at least one questionnaire. Of the optional study elements, 7 participant-health care professional dyads participated in the survey, and 97 participants who completed the survey donated their anonymized medical device data. Conclusions: The platform was accessible to participants while maintaining compliance with data regulations. The Gateway formalized a system of automated data matching between multiple data sets, which was a major benefit to researchers. Scalability of the platform was demonstrated with the later addition of self-reported data validation. This study demonstrated the feasibility of custom software solutions in addressing complex study designs. The Gateway portal code has been made available open-source and can be leveraged by other research groups.
Sponsorship
European Commission Horizon 2020
Other Sponsorship
Marie Skłodowska-Curie Action Research and Innovation Staff Exchange
SPOKES Wellcome Trust Translational Partnership Program
German Research Foundation - Digital Clinician Scientist Program of the Berlin Institute of Health
German Research Foundation and the Open Access Publication Fund (Charité – Universitätsmedizin Berlin)
Type of Material
Journal Article
Publisher
JMIR Publications
Journal
JMIR Diabetes
Volume
7
Issue
1
Start Page
1
End Page
11
Copyright (Published Version)
2022 The Authors
Subjects

Automated insulin del...

Diabetes

Diabetes technology

Digital health

Insulin

Mixed methods

Open-source

Patient-reported outc...

Real-world data

Research methods

Type 1 diabetes

Web portal

DOI
10.2196/33213
Language
English
Status of Item
Peer reviewed
ISSN
2371-4379
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by/3.0/ie/
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Open-source Web Portal for Managing Self-reported Data and Real-world Data Donation in Diabetes Research Platform Feasibilit.pdf

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788.24 KB

Format

Adobe PDF

Checksum (MD5)

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Owning collection
Sociology Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
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