Practical Guidance on Open Source and Commercial Automated Insulin Delivery Systems: A Guide for Healthcare Professionals Supporting People with Insulin-Requiring Diabetes.
Diabetes Ther
; 13(9): 1683-1699, 2022 Sep.
Article
en En
| MEDLINE
| ID: mdl-35913655
Automated insulin delivery (AID) systems are a useful tool for people with insulin-requiring diabetes. AID systems include an insulin pump, continuous glucose monitor (CGM), and an algorithm embedded within the pump or a separate mobile device that can determine and automatically adjust insulin delivery in response to glucose levels. There are now a number of AID systems available, some which are made and distributed by commercial manufacturers and some that are available open source. Both open source and commercially developed automated insulin delivery systems have been proven to be safe and effective. Open source and commercially developed automated insulin delivery systems have also been proven to improve the quality of life of people with insulin-requiring diabetes. The choice of an AID system is not merely whether the system is open source or commercially developed. There are multiple criteria to assess when choosing an AID system: pump, CGM, smartphone connectivity and algorithm capabilities, flexibility of the system overall, and interoperability with connected platforms for real-time data access. Most importantly, the choices and preferences of the person living with diabetes should be at the center of any decision around the ideal automated insulin delivery system or any other diabetes technology. Healthcare providers will benefit from assessing and better understanding all available AID system options to enable them to best support each individual. This practical guide seeks to provide a conversational framework for healthcare providers to first understand and then jointly assess AID system options with users and caregivers.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Tipo de estudio:
Guideline
/
Prognostic_studies
Aspecto:
Patient_preference
Idioma:
En
Revista:
Diabetes Ther
Año:
2022
Tipo del documento:
Article
País de afiliación:
Estados Unidos
Pais de publicación:
Estados Unidos