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      Smart Insulin Pens: Advancing Digital Transformation and a Connected Diabetes Care Ecosystem

      1 , 1 , 2
      Journal of Diabetes Science and Technology
      SAGE Publications

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          Abstract

          With the first commercially available smart insulin pens, the predominant insulin delivery device for millions of people living with diabetes is now coming into the digital age. Smart insulin pens (SIPs) have the potential to reshape a connected diabetes care ecosystem for patients, providers, and health systems. Existing SIPs are enhanced with real-time wireless connectivity, digital dose capture, and integration with personalized dosing decision support. Automatic dose capture can promote effective retrospective review of insulin dose data, particularly when paired with glucose data. Patients, providers, and diabetes care teams will be able to make increasingly data-driven decisions and recommendations, in real time, during scheduled visits, and in a more continuous, asynchronous care model. As SIPs continue to progress along the path of digital transformation, we can expect additional benefits: iteratively improving software, machine learning, and advanced decision support. Both these technological advances, and future care delivery models with asynchronous interactions, will depend on easy, open, and continuous data exchange between the growing number of diabetes devices. SIPs have a key role in modernizing diabetes care for a large population of people living with diabetes.

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          Overall Survival Results of a Trial Assessing Patient-Reported Outcomes for Symptom Monitoring During Routine Cancer Treatment.

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            Is Open Access

            SMART on FHIR: a standards-based, interoperable apps platform for electronic health records

            Objective In early 2010, Harvard Medical School and Boston Children’s Hospital began an interoperability project with the distinctive goal of developing a platform to enable medical applications to be written once and run unmodified across different healthcare IT systems. The project was called Substitutable Medical Applications and Reusable Technologies (SMART). Methods We adopted contemporary web standards for application programming interface transport, authorization, and user interface, and standard medical terminologies for coded data. In our initial design, we created our own openly licensed clinical data models to enforce consistency and simplicity. During the second half of 2013, we updated SMART to take advantage of the clinical data models and the application-programming interface described in a new, openly licensed Health Level Seven draft standard called Fast Health Interoperability Resources (FHIR). Signaling our adoption of the emerging FHIR standard, we called the new platform SMART on FHIR. Results We introduced the SMART on FHIR platform with a demonstration that included several commercial healthcare IT vendors and app developers showcasing prototypes at the Health Information Management Systems Society conference in February 2014. This established the feasibility of SMART on FHIR, while highlighting the need for commonly accepted pragmatic constraints on the base FHIR specification. Conclusion In this paper, we describe the creation of SMART on FHIR, relate the experience of the vendors and developers who built SMART on FHIR prototypes, and discuss some challenges in going from early industry prototyping to industry-wide production use.
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              Mobile Devices and Health

              Ida Sim (2019)
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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Journal of Diabetes Science and Technology
                J Diabetes Sci Technol
                SAGE Publications
                1932-2968
                1932-2968
                May 2022
                January 12 2021
                May 2022
                : 16
                : 3
                : 596-604
                Affiliations
                [1 ]Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
                [2 ]Center for Digital Health Innovation, University of California, San Francisco, San Francisco, CA, USA
                Article
                10.1177/1932296820984490
                33435704
                062f8b6c-3dbf-467f-b7d6-4b15f6ecda0d
                © 2022

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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