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Introduction: This article provides an overview of presentations and discussions from the inaugural Healthcare Delivery Science: Innovation and Partnerships for Health Equity Research (DESCIPHER) Symposium. Methods: The symposium brought together esteemed experts from various disciplines to explore models for translating evidence-based interventions into practice. Results: The symposium highlighted the importance of disruptive innovation in healthcare, the need for multi-stakeholder engagement, and the significance of family and community involvement in healthcare interventions. Conclusions: The article concluded with a call to action for advancing healthcare delivery science to achieve health equity.
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The Fifth Artificial Pancreas Workshop: Enabling Fully Automation, Access, and Adoption was held at the National Institutes of Health (NIH) Campus in Bethesda, Maryland on May 1 to 2, 2023. The organizing Committee included representatives of NIH, the US Food and Drug Administration (FDA), Diabetes Technology Society, Juvenile Diabetes Research Foundation (JDRF), and the Leona M. and Harry B. Helmsley Charitable Trust. In previous years, the NIH Division of Diabetes, Endocrinology, and Metabolic Diseases along with other diabetes organizations had organized periodic workshops, and it had been seven years since the NIH hosted the Fourth Artificial Pancreas in July 2016. Since then, significant improvements in insulin delivery have occurred. Several automated insulin delivery (AID) systems are now commercially available. The workshop featured sessions on: (1) Lessons Learned from Recent Advanced Clinical Trials and Real-World Data Analysis, (2) Interoperability, Data Management, Integration of Systems, and Cybersecurity, Challenges and Regulatory Considerations, (3) Adaptation of Systems Through the Lifespan and Special Populations: Are Specific Algorithms Needed, (4) Development of Adaptive Algorithms for Insulin Only and for Multihormonal Systems or Combination with Adjuvant Therapies and Drugs: Clinical Expected Outcomes and Public Health Impact, (5) Novel Artificial Intelligence Strategies to Develop Smarter, More Automated, Personalized Diabetes Management Systems, (6) Novel Sensing Strategies, Hormone Formulations and Delivery to Optimize Close-loop Systems, (7) Special Topic: Clinical and Real-world Viability of IP-IP Systems. "Fully automated closed-loop insulin delivery using the IP route," (8) Round-table Panel: Closed-loop performance: What to Expect and What are the Best Metrics to Assess it, and (9) Round-table Discussion: What is Needed for More Adaptable, Accessible, and Usable Future Generation of Systems? How to Promote Equitable Innovation? This article summarizes the discussions of the Workshop.
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Diabetes Mellitus Tipo 1 , Pâncreas Artificial , Humanos , Diabetes Mellitus Tipo 1/tratamento farmacológico , Insulina/uso terapêutico , Glicemia , Inteligência Artificial , Sistemas de Infusão de Insulina , Insulina Regular Humana/uso terapêutico , Automação , Hipoglicemiantes/uso terapêuticoRESUMO
This commentary article discusses the benefits of utilizing telemedicine to conduct shared medical appointments for people with type 1 diabetes and type 2 diabetes. We conducted a literature review of articles about shared medical appointments or group medical visits in people with diabetes with associated clinical data. We identified 43 articles. Models of this approach to care have demonstrated positive outcomes in adults and children with type 1 diabetes. Shared telemedicine appointments also have the potential to improve diabetes self-management, reduce the treatment burden, and improve psychosocial outcomes in adults with type 2 diabetes. Ten key recommendations for implementation are presented to guide the development of shared telemedicine appointments for diabetes. These recommendations can improve care for diabetes.
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Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 3 to November 5, 2022. Meeting topics included (1) the measurement of glucose, insulin, and ketones; (2) virtual diabetes care; (3) metrics for managing diabetes and predicting outcomes; (4) integration of continuous glucose monitor data into the electronic health record; (5) regulation of diabetes technology; (6) digital health to nudge behavior; (7) estimating carbohydrates; (8) fully automated insulin delivery systems; (9) hypoglycemia; (10) novel insulins; (11) insulin delivery; (12) on-body sensors; (13) continuous glucose monitoring; (14) diabetic foot ulcers; (15) the environmental impact of diabetes technology; and (16) spinal cord stimulation for painful diabetic neuropathy. A live demonstration of a device that can allow for the recycling of used insulin pens was also presented.
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Diabetes Mellitus Tipo 1 , Humanos , Diabetes Mellitus Tipo 1/tratamento farmacológico , Glicemia , Automonitorização da Glicemia , Insulina/uso terapêutico , Sistemas de Infusão de Insulina , Tecnologia , Hipoglicemiantes/uso terapêuticoRESUMO
The digital health revolution is transforming the landscape of medicine through innovations in sensor data, software, and wireless communication tools. As one of the most prevalent chronic diseases in the United States, diabetes is particularly impactful as a model disease for which to apply innovation. As with any other newly developed technologies, there are three key questions to consider: 1) How can the technology benefit people with diabetes?, 2) What barriers must be overcome to further advance the technology?, and 3) How will the technology be applied in the future?. In this article, we highlight six areas of innovation that have the potential to reduce the burden of diabetes for individuals living with the condition and their families as well as provide measurable benefits for all stakeholders involved in diabetes care. The six technologies which have the potential to transform diabetes care are (i) telehealth, (ii) incorporation of diabetes digital data into the electronic health record, (iii) qualitative hypoglycemia alarms, (iv) artificial intelligence, (v) cybersecurity of diabetes devices, and (vi) diabetes registries. To be successful, a new digital health technology must be accessible and affordable. Furthermore, the people and communities that would most likely benefit from the technology must be willing to use the innovation in their management of diabetes.
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Diabetes Mellitus , Telemedicina , Humanos , Inteligência Artificial , Diabetes Mellitus/terapia , Software , Tecnologia BiomédicaRESUMO
BACKGROUND: Rates for Diabetes Mellitus continue to rise in most urban areas of the United States, with a disproportionate burden suffered by minorities and low income populations. This paper presents an approach that utilizes address level data to understand the geography of this disease by analyzing patients seeking diabetes care through an emergency department in a Los Angeles County hospital. The most vulnerable frequently use an emergency room as a common care access point, and such care is especially costly. A fine scale GIS analysis reveals hotspots of diabetes related health problems and provides output useful in a clinic setting. Indeed these results were used to support the work of a progressive diabetes clinic to guide management and intervention strategies. RESULTS: Hotspots of diabetes related health problems, including neurological and kidney issues were mapped for vulnerable populations in a central section of Los Angeles County. The resulting spatial grid of rates and significance were overlaid with new patient residential addresses attending an area clinic. In this way neighbourhood diabetes health characteristics are added to each patient's individual health record. Of the 29 patients, 4 were within statistically significant hotspots for at least one of the conditions being investigated. CONCLUSIONS: Although exploratory in nature, this approach demonstrates a novel method to conduct GIS based investigations of urban diabetes while providing support to a progressive diabetes clinic looking for novel means of managing and intervention. In so doing, this analysis adds to a relatively small literature on fine scale GIS facilitated diabetes research. Similar data should be available for most hospitals, and with due consideration for preserving spatial confidentiality, analysis outputs such as those presented here should become more commonly employed in other investigations of chronic diseases.