Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

BackgroundRates 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.ResultsHotspots 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.ConclusionsAlthough 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.

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 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.

Introduction:The electronic health record (EHR) has increased time spent outside of face-to-face encounters, with higher EHR burden associated with differences in provider sex, specialty, and rates of burnout. However, the EHR burden specific to gastroenterology (GI) providers is not fully understood. Methods: Measures of EHR use calculated through Epic Systems were retrospectively collected for GI providers from a tertiary referral center during a 6-month period starting January 1, 2021. Primary measures used to characterize EHR use included time spent performing clinical review, documentation, and in-basket management as well as quantification of efficiency, messaging, and time logged into the EHR, including time outside regularly scheduled hours (5:30 p.m. to 7:00 a.m. and weekends). EHR use patterns were compared across provider sex, sub-specialty (inflammatory bowel disease [IBD], motility/irritable bowel syndrome, advanced endoscopy [AE], and esophagus [ESO]), and training (physician vs non-physician provider [NPP]). Data was analyzed in aggregate using t-tests and analysis of variance with post-hoc Boniferri correction. Results: Data from 33 providers compromising 3,743 clinic days and 16,572 appointments was collected. Overall, 69.7% (23/33) were physicians, 30.3% (10/33) NPPs and 48.5% (16/33) were women, with women comprising all NPPs. Comparing EHR burden across sexes, women spent more daily time in clinical review than men (42.4 minutes vs 26.0, P 5 0.02), though this result lost statistical significance when excluding NPPs. Comparing sub-specialties, IBD specialists spent more daily time in clinical review per appointment than AEs or ESOs (13.7 minutes vs 3.9 and 3.7, respectively; P , 0.001) yet had higher efficiency scores compared to these sub-specialties (P , 0.001). Compared to AEs, IBD specialists spent more overall daily time in the EHR (131.5 minutes vs 39.7, P , 0.005) as well as more daily time outside of regular work hours (60.0 minutes vs 8.9, P , 0.01). Comparing provider training, NPPs spent more daily time in the in-basket (P 5 0.03), clinical review (P 5 0.02), and overall EHR (P , 0.001) than physicians. Additionally, NPPs received more patient medical advice request messages per day than physicians (P 5 0.03). Conclusion: IBD specialists and NPPs have an increased EHR burden. More work is needed to better understand sex, sub-specialty, and training-based differences in workload to combat factors contributing to provider burnout.

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.