A case study in open source innovation: Developing the Tidepool Platform for interoperability in type 1 diabetes management
Open accessAbstract
OBJECTIVE: Develop a device-agnostic cloud platform to host diabetes device data and catalyze an ecosystem of software innovation for type 1 diabetes (T1D) management. MATERIALS AND METHODS: An interdisciplinary team decided to establish a nonprofit company, Tidepool, and build open-source software. RESULTS: Through a user-centered design process, the authors created a software platform, the Tidepool Platform, to upload and host T1D device data in an integrated, device-agnostic fashion, as well as an application ("app"), Blip, to visualize the data. Tidepool's software utilizes the principles of modular components, modern web design including REST APIs and JavaScript, cloud computing, agile development methodology, and robust privacy and security. DISCUSSION: By consolidating the currently scattered and siloed T1D device data ecosystem into one open platform, Tidepool can improve access to the data and enable new possibilities and efficiencies in T1D clinical care and research. The Tidepool Platform decouples diabetes apps from diabetes devices, allowing software developers to build innovative apps without requiring them to design a unique back-end (e.g., database and security) or unique ways of ingesting device data. It allows people with T1D to choose to use any preferred app regardless of which device(s) they use. CONCLUSION: The authors believe that the Tidepool Platform can solve two current problems in the T1D device landscape: 1) limited access to T1D device data and 2) poor interoperability of data from different devices. If proven effective, Tidepool's open source, cloud model for health data interoperability is applicable to other healthcare use cases.
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CGM data can be merged with information provided by other medical devices, mobile apps, clinical registries, electronic health records, and other wearable sensors such as activity trackers.
“For example, CGM data can be merged with information provided by other medical devices (SMBG, pumps, smart pens) [64], mobile apps, clinical registries, electronic health records, as well as other wearable sensors, such as activity trackers.”
From Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors (2020) · cites this paper as [64]
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Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors
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- Authors
- Neinstein, A., Wong, J., Look, H., Arbiter, B., Quirk, K., McCanne, S., Sun, Y., Blum, M., & Adi, S.
- Affiliations
- University of California, San Francisco (US)
- Tidepool (US)
- Corresponding author
- Neinstein, Aaron
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-09-02
- Volume
- 23
- Issue
- 2
- Pages
- 324-332
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC4784555
- OpenAlex
- W2140397432
- Cited by
- 66
- References
- 57
- Citations by year
- 2026: 6 · 2025: 5 · 2024: 11 · 2023: 6 · 2022: 3 · 2021: 5 · 2020: 14 · 2019: 5 · 2018: 4 · 2017: 4 · 2016: 2 · 2015: 1
- FWCI
- 3.18
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of the American Medical Informatics Association (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by-nc)
- HighWire Press Open Archive (submittedVersion)
- Funders
- Leona M. and Harry B. Helmsley Charitable Trust
- National Institutes of Health (5k12dk094726-05, NIH T32, T32 grant, NIH K12, DK094726)
- National Institute of Diabetes and Digestive and Kidney Diseases (K23DK107894, DK094726)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- type 1 diabetes, open source software, health data interoperability, diabetes apps, user-centered design, health data access
- MeSH terms
- Diabetes Mellitus, Type 1, Humans, Ownership, Software, Systems Integration
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