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Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

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A case study in open source innovation: developing the Tidepool Platform for interoperability in type 1 diabetes

Aaron Neinstein¹, Jenise Wong², Howard Look³

¹Department of Medicine and Center for Digital Health Innovation, University of California, San Francisco, CA, USA aaron.neinstein@ucsf.edu aneinstein@gmail.com.

Journal of the American Medical Informatics Association : JAMIA

|September 5, 2015

Summary

Tidepool developed an open-source cloud platform for type 1 diabetes (T1D) device data, improving data access and enabling innovative software applications. This device-agnostic approach enhances T1D management and research by integrating scattered data.

Keywords:

blood glucose self-monitoring computer-assisted decision making diabetes mellitus type 1 insulin infusion systems mobile applications

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Area of Science:

Biomedical Informatics
Software Engineering
Diabetes Technology

Background:

Type 1 diabetes (T1D) management is challenged by fragmented and siloed data from various devices.
Limited interoperability hinders efficient data access for patients and healthcare providers.
Lack of a centralized, device-agnostic platform restricts software innovation in diabetes care.

Purpose of the Study:

To develop a device-agnostic cloud platform for hosting type 1 diabetes (T1D) device data.
To foster an ecosystem of software innovation for improved T1D management.
To address data accessibility and interoperability issues in the T1D device landscape.

Main Methods:

Established a nonprofit company, Tidepool, and developed open-source software.
Employed a user-centered design process for platform development.
Utilized modular components, modern web design (REST APIs, JavaScript), cloud computing, and agile methodology.

Main Results:

Created the Tidepool Platform for integrated, device-agnostic hosting of T1D data.
Developed the Blip application for visualizing diabetes device data.
Implemented robust privacy and security measures within the platform.

Conclusions:

Consolidated scattered T1D device data into a single, open platform, improving data access for clinical care and research.
Decoupled diabetes applications from specific devices, enabling developers to create innovative apps without backend complexities.
Empowered individuals with T1D to use preferred applications irrespective of their diabetes devices, enhancing user choice and data utilization.